Emerging optical techniques for sorting and detection of chiral particles

Emerging optical techniques for sorting and detection of chiral particles

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Yuzhi Shi¹^,²^,³^,⁴^,⁵^,⁶^,⁷^,^*, Chengfeng Li⁴^,⁵^,⁶^,⁷, Xiaolei Lin¹^,²^,³, Wenwen Xue¹^,²^,³, Chengxing Lai⁴^,⁵^,⁶^,⁷, Tao He⁴^,⁵^,⁶^,⁷, Qinghua Song⁸, Zhanshan Wang⁴^,⁵^,⁶^,⁷, Yulan Wang¹^,²^,³^,^*, Din Ping Tsai⁹^,^*, Xinbin Cheng⁴^,⁵^,⁶^,⁷^,^*, Haidong Zou¹^,²^,³^,^*

Opto-Electronic Advances | 2026, 9(6) : 250255-1 - 250255-34

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Opto-Electronic Advances | 2026, 9(6): 250255-1-250255-34

• Review •

Emerging optical techniques for sorting and detection of chiral particles

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Affiliations

¹Shanghai Eye Diseases Prevention & Treatment Center/Shanghai Eye Hospital, School of Medicine, Tongji University, Shanghai 200092, China

²National Clinical Research Center for Eye Diseases, Shanghai 200080, China

³Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China

⁴Institute of Precision Optical Engineering, School of Physics Science and Engineering, Tongji University, Shanghai 200092, China

⁵MOE Key Laboratory of Advanced Micro-Structured Materials, Shanghai 200092, China

⁶Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China

⁷Shanghai Frontiers Science Center of Digital Optics, Shanghai 200092, China

⁸Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China

⁹Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China

About Author:

^†

These authors contributed equally to this work.

Author contributions

Yuzhi Shi: Conceptualization, Formal analysis, Writing-review & editing, Project administration, Funding acquisition. Chengfeng Li, Xiaolei Lin and Wenwen Xue: Formal analysis, Writing–review & editing. Chengxing Lai, Tao He, Qinghua Song and Zhanshan Wang: Writing-review & editing. Yulan Wang, Din Ping Tsai, Xinbin Cheng and Haidong Zou: Formal analysis, Writing–review & editing, Project administration, Funding acquisition.

Published: 2026-06-08 doi: 10.29026/oea.2026.250255

Outline

Abstract

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Sorting and detection of enantiomers hold critical importance in biomedical, chemical, and pharmacological sciences due to their fundamental role in molecular interactions and therapeutic efficacy. Over the past two decades, diverse chemical, biophysical, and microfluidic methodologies have been developed for chiral enantiomer sorting and detection. While these approaches have demonstrated significant capabilities, optical techniques have attracted increasing interest due to their intrinsic advantages, including rapid analysis, minimal sample consumption, and non-invasive operation. This review comprehensively overviews recent advances in optical methods for chiral enantiomer sorting and detection. We focus on emerging optical concepts, including exotic optical forces and engineered light fields, such as bound states in the continuum and metasurfaces, and analyze their operational principles, capabilities, and inherent limitations. Furthermore, we investigate the growing impact of artificial intelligence in reshaping optical sorting and sensing strategies, particularly its role in improving analytical precision and enabling autonomous operation. The review concludes with a forward-looking perspective, discussing persistent challenges like system scalability and real-world implementation while outlining promising future directions, including integrated lab-on-chip platforms and advanced chiral metamaterials.

Key words

chiral molecules / optical sorting / optical detection / artificial intelligence / biochemical applications

Cite this Article

Yuzhi Shi, Chengfeng Li, Xiaolei Lin, Wenwen Xue, Chengxing Lai, Tao He, Qinghua Song, Zhanshan Wang, Yulan Wang, Din Ping Tsai, Xinbin Cheng, Haidong Zou. Emerging optical techniques for sorting and detection of chiral particles[J]. Opto-Electronic Advances, 2026 , 9 (6) : 250255-1 -250255-34 . DOI: 10.29026/oea.2026.250255

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1　Introduction

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Chiral molecules, existing as non-superimposable mirror images (enantiomers), are fundamental building blocks of life and pervasive throughout nature and technology^1,2. Their significance stems from the profound fact that enantiomers often exhibit drastically different biological, chemical, and physical properties. In pharmaceuticals, one enantiomer may be a life-saving drug while its mirror image could be inactive or even toxic³. In agrochemicals, enantiomeric purity dictates pesticide effectiveness and environmental safety. In biology, the homochirality of amino acids and sugars (L- and D-forms, respectively) is essential for the structure and function of proteins, DNA, and cellular processes⁴. Furthermore, chiral molecules play vital roles in flavours, fragrances, and as components in advanced materials like liquid crystals⁵ and catalysts. Consequently, the ability to detect and separate chiral molecules is indispensable across diverse fields, including medicine⁶, biochemistry⁷, pharmacology⁸, materials science⁹, and food science¹⁰.

Non-optical techniques offer diverse approaches for sorting and detecting chiral molecules. Chromatography¹¹⁻¹³, particularly using chiral stationary phases (CSPs), serves as a cornerstone, where enantiomers are separated based on differential interactions with immobilized chiral selectors (such as cyclodextrins and proteins) within a column, resulting in distinct retention times. Capillary electrophoresis achieves high-resolution separation by incorporating chiral additives into the buffer, exploiting differences in electrophoretic mobility. Crystallization-based methods^14,15, such as classical resolution via diastereomeric salt formation, leverage disparities in solubility or crystallization kinetics between enantiomerically pure compounds or their diastereomeric derivatives. For the detection, approaches include enzymatic assays, electrochemical sensors, immunoassays, and colorimetric methods. However, these non-optical methods could generally suffer from several limitations, including the need for sample derivatization (e.g., for colorimetry or diastereomer formation), destructive analysis, limited throughput, high cost, and system complexity. These limitations highlight the demand for advanced optical techniques^16,17, such as optical forces, polarimetry, circular dichroism (CD) spectroscopy, and so forth. These optical methods provide non-destructive analysis, real-time monitoring capabilities, higher potential throughput, and normally require minimal sample preparation, offering a vital alternative for comprehensive chiral analysis.

Despite sustained progress, chiral separation and detection remain fundamentally challenging from a physical perspective. The intrinsic weakness of chiroptical interactions, which typically arising from electromagnetic dipole coupling, severely limits enantioselectivity and signal strength. For optical sorting, generating sufficiently strong and selective chiral optical forces is nontrivial due to their subtle dependence on field helicity, momentum, and near field gradients. For optical detection, reliably distinguishing weak chiral signatures from background remains a central bottleneck, particularly at low concentrations. These theoretical and practical challenges have motivated the rapid development of engineered light fields, nanophotonic platforms, and artificial intelligence (AI)-assisted strategies, which together form the core focus of this review.

While numerous reviews have summarized developments in chiral optical sensing and chiral-light interactions in recent years¹⁸⁻²⁰, most were published over five years ago and thus miss significant recent advances. Concurrently, optical sorting of chiral molecules has attracted substantial attention, generating numerous novel approaches that now stimulate a comprehensive review. Motivated by these factors, we herein provide a comprehensive review of the optical sorting and detection of chiral molecules. Specifically, we focus on the recent advances and newly emerged optical techniques. We discuss various platforms for optical sorting, including both far-field and near-field systems. These systems enable the exploration of new physical phenomena. Meanwhile, novel techniques have emerged for the optical detection of a great diversity of chiral molecules.

1.1　Overview of optical sorting and detection of chiral particles

This review first offers a brief introduction to established non-optical techniques for chiral sorting and detection, such as chemical, biophysical, and microfluidic methods. We highlight their essential characteristics and principal limitations, whereas in-depth analyses are available in other dedicated reviews. Next, two major areas of this paper will be explored, namely, optical sorting and detection of chiral particles. We introduce the underlying physics, platforms, and techniques in these two areas. The feasibility and limitations of various approaches are also compared and examined, which may handle specific types of chiral molecules. We note that there are some ongoing issues that need to be solved shortly. Thus, the review concludes with a discussion of future prospects for these two rapidly growing and promising research fields.

1.2　Milestones of optical sorting and detection of chiral particles

The backbone of this paper is illustrated in Fig. 1. Platforms for the optical sorting include single interfaces, metasurfaces²¹⁻²³, vector beams²⁴, slot waveguides, optofluidics^25,26, etc. New physics and ideas can be explored using these platforms. Notable examples include the bound state in the continuum (BIC)²⁷, exceptional point (EP)^28,29, interference fields, multipoles³⁰ and toroidals³¹. Specifically, the optical sorting relies on the generation of optical forces, ranging from conventional to exotic ones. Recent detection techniques for the detection of chiral molecules mainly focus on engineering superchiral light fields, which can be configured through various designs, such as nanocavities, metasurfaces, plasmonics³², and surface-enhanced Raman scattering (SERS)³³. Specific chiral molecules can also be probed in a complex sample via machine learning (ML)^34,35. The advances of those techniques have enabled the detection of numerous chiral molecules, including synthesized metallic nanoparticles, complex-shaped ones, particle-biomolecule complexes, chemical molecules, and biomolecules.

The milestones for optical sorting and detection are plotted in Fig. 2. The history of optical sorting dates back to 2013, when Tkachenko et al. proposed the idea to utilize the optical radiation pressure (ORP) for sorting chiral particles³⁶. Experiments of optical sorting using the optical gradient force (OGF) were reported in 2014³⁷. The optical lateral force (OLF) represents a typical force transverse to the light propagation direction and has no contributions from light gradients. This force was born with strong capabilities for sorting with left- and right-handedness chiral particles in 2014³⁸. Much later, in 2019, Kravets et al. reported the chiral optical Stern-Gerlach Newtonian experiment, which can be utilized for optical sorting³⁹. Though the optical pulling force (OPF) was proposed earlier than the OLF, early-stage sorting applications using the OPF mainly focus on achiral particles⁴⁰. In 2021, Ali et al. used the OPF for sorting chiral particles⁴¹.

Leveraging those forces, various light fields and mechanisms have been used for chiral sorting. Notable examples include the surface-based sorting in 2014³⁸, Airy beam in 2018, vector beam in 2019⁴², metasurface in 2020¹⁷, waveguide in 2021⁴³, BIC in 2022⁴⁴, and toroidals in 2025⁴⁵.

For the optical detection, the earliest works addressing natural and synthesized chiral particles date back to 1848⁴⁶ and 2000⁴⁷, respectively. In the early stage, circularly polarized light with limited optical chirality was used for the detection, resulting in limited sensitivity. In 2010, Hendry et al. achieved the ultrasensitive detection of biomolecules using superchiral fields⁴⁸. After that, numerous approaches have been adopted for the generation of superchiral light. For instance, chiral particles can be detected using standing waves in 2011⁴⁹, nanocavities in 2015⁵⁰, plasmonics in 2016⁵¹, SERS in 2016⁵², metasurface in 2018⁵³, membrane in 2019⁵⁴, AI in 2019⁵⁵, and BIC in 2020⁵⁶. With the advances of nanophotonics, current techniques have achieved a remarkable sensitivity down to 10⁻¹⁵ M⁵⁷.

2　Chiral sorting

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2.1　Non-optical techniques for chiral sorting

Before delving into optical strategies for chiral sorting, it is instructive to briefly survey the diverse chemical, biophysical, and microfluidic methodologies that have been traditionally employed for enantioseparation. Considering that the present review primarily focuses on optical technologies, we provide here only a brief overview of non-optical methods. More comprehensive discussions can be found in various review papers⁵⁸⁻⁷⁰.

Traditional chemical chiral molecular separation encompasses a variety of techniques, primarily including chromatography¹¹⁻¹³, crystallization and kinetic resolution^14,15, membrane-based enantioseparation techniques⁷¹⁻⁷³, adsorption and fixed-bed processes, as well as emerging synergistic methods^13,74,75.

Chromatography remains the most established strategy for enantioseparation. It includes high-performance liquid chromatography (HPLC)¹¹, gas chromatography (GC), capillary electrophoresis (CE)⁷⁶, and supercritical-fluid chromatography (SFC)⁷⁷, all of which exploit CSPs for enantiomeric resolution. HPLC is the most widely used, but its application is limited by high solvent consumption, costly CSPs, and lengthy optimization^11,13. GC works well for volatile and thermally stable compounds, but is constrained by the scarcity of chiral columns. SFC, a newer chiral separation technology employing CO₂ as the mobile phase, enables tunable polarity via temperature, pressure, or solvent modifiers (Fig. 3(a))⁷⁷. It combines the high diffusivity of GC with the solubilizing capacity of HPLC to deliver efficient, rapid, and more sustainable separations. Recent efforts have primarily focused on developing novel CSPs with enhanced selectivity and broader applicability⁷⁸.

Beyond chromatography, crystallization provides a classical industrial approach for bulk production of single enantiomers. It relies on solubility differences and dynamic crystallization strategies to selectively enrich one enantiomer^14,15,79. Complementarily, kinetic resolution employs chiral catalysts such as enzymes to preferentially convert one enantiomer from a racemic mixture, often coupled with rapid racemization to reach high enantiomeric excess⁸⁰.

Membrane-based strategies⁸¹ offer a continuous and energy-efficient alternative. Chiral membranes constructed from frameworks such as Metal-Organic Frameworks (MOFs)⁸², chiral Covalent Organic Frameworks (COFs) (Fig. 3(b))^71,74,83, and chiral nanosheets enable enantioselective transport. MOFs offer high surface area and tunable pore chemistry, while COFs provide superior chemical stability and uniform, scalable pores. Compared with chromatography, membrane-based processes deliver higher throughput and continuous operation, promising broad pharmaceutical applications.

In addition, emerging synergistic technologies are also gaining traction. Chiral aggregation-induced emission (AIEgen) aggregation-precipitation enables enantiomeric excess (ee) values up to 90% (Fig. 3(c))⁸⁴. Electrochemical methods allow redox-controlled selective adsorption-desorption of enantiomers⁸⁵. Chiral medium-entropy ceramics have further demonstrated stable and selective amino acids separation (Fig. 3(d))⁸⁶. These approaches remain at an early stage but offer promising routes for high-throughput and green processes.

Although chemical and optical approaches dominate the field of enantioseparation, a smaller body of work has explored alternative strategies such as microfluidic and biological methods⁷⁰.

Microfluidic technology, as an interdisciplinary field integrating chemistry, fluid physics, and biomedical engineering, enables precise manipulation of nanoliter-to-attoliter fluids in microscale channels and chambers with the chip serving as the core functional carriers⁸⁷, as shown in Fig. 4(a). Various mechanisms have been developed for chiral separation⁷⁰: electrophoretic mode⁸⁸ employs cross-channels and chiral selectors such as cyclodextrins to separate specially-labeled amino acids; chiral microvortex⁸⁹ regulation generates helical microvortices for racemic amino acids quantification via circular dichroism without chiral reagents; antisolvent crystallization⁸⁷ achieves complete chiral symmetry breaking (100% ee) in nanoliter volumes via coaxial capillaries; and the shear flow⁹⁰ mode efficiently separates helical bacteria in serpentine channels. Overall, microfluidics offers high speed, minimal sample consumption, and high-throughput potential, though challenges remain in terms of equipment costs, resolution for small molecules, and system stability.

Biological methods exploit the inherent chiral recognition of biomolecules such as enzymes, antibodies, and microorganisms, as shown in Fig. 4(b). Enzymatic approaches leverage stereospecific catalysis, converting one enantiomer while leaving the other unreacted, enabling rapid and selective quantification⁷⁰. Target enantiomers can then be separated and quantified by detecting either product signals or residual substrates. For example, glucose oxidase exclusively catalyzes D-glucose to produce hydrogen peroxide, which can be measured via fluorescence imaging. Immunoaffinity chromatography⁹¹ achieves separation using antibodies against a specific chiral configuration. These biological strategies offer mild conditions, environmental compatibility, and high selectivity, but are constrained by enzyme stability, substrate scope, and limited throughput.

In contrast to above non-optical approaches, optical strategies offer several distinctive advantages for chiral sorting. Optical methods enable contactless and non-destructive manipulation, real-time and in situ control, and flexible programmability through engineered light fields, without the need for chemical derivatization or specific material functionalization. More importantly, optical forces and chiroptical interactions provide access to enantioselective manipulation at the single-particle or even single-molecule level, which is difficult to achieve using conventional chemical or biological routes. These unique features have stimulated growing interest in optical sorting of chiral molecules, which is the primary focus of the following sections.

2.2　Optical techniques for chiral sorting

Optical sorting of chiral molecules has evolved along a clear progression in both underlying physical mechanism and optical field complexity. In this section, the discussion is organized starting from fundamental theoretical formulations and advancing toward increasingly sophisticated optical platforms. We first introduce the basic expressions of chiral optical forces derived from light-matter interaction theory, which establish the physical foundation for enantioselective manipulation. Based on these formulations, early demonstrations of optical chiral sorting using relatively simple optical fields, including ORP, OGF, OPF and OLF, are reviewed. Building upon these foundational schemes, the discussion then moves to structured light beams, such as vector beams and tightly focused high-NA fields. Finally, we review near-field and nanophotonic approaches, where strong field confinement and resonant enhancement play a dominant role. Novel platforms including waveguides and metasurfaces are discussed, as they offer orders-of-magnitude enhancement of chiral light-matter interactions and open new routes toward practical, miniaturized, and integrable chiral sorting devices.

ORP, OGF, OPF and OLF for chiral sorting. In the next section, we will discuss in detail different optical sorting mechanisms, beginning with some classical works based on the ORP, OGF, OPF, and optical OLF. These formulations provide a unified basis for classifying optical sorting mechanisms according to the physical origin of the chiral force.

The constitutive relation of chiral particles is well established and is given by^20,92:

$ \left\{\begin{array}{l} \boldsymbol{D}={\epsilon }_{{\mathrm{p}}}\boldsymbol{E}+{\mathrm{i}}\kappa \sqrt{{\epsilon }_{0}{\mu }_{0}}\boldsymbol{H}\\\boldsymbol{B}=-{\mathrm{i}}\kappa \sqrt{{\epsilon }_{0}{\mu }_{0}}\boldsymbol{E}+{\mu }_{{\mathrm{p}}}\boldsymbol{H}\end{array}\right.\;, $

(1)

where

$ {\epsilon }_{{\mathrm{p}}} $

and

$ {\mu }_{{\mathrm{p}}} $

are permittivity and permeability of the particle, respectively and

$ \kappa $

is the chirality parameter constrained by

$ \kappa \lt \sqrt{\epsilon \mu } $

. Here,

$ \epsilon $

and

$ \mu $

represent the permittivity and permeability of the medium^93,94.

The induced electromagnetic dipole moments in chiral particles are determined by the incident electromagnetic field and the corresponding polarizabilities^38,95−97:

$ \left\{\begin{array}{l} \boldsymbol{d}={\alpha }_{{\mathrm{ee}}}\boldsymbol{E}+{\alpha }_{{\mathrm{em}}}\boldsymbol{B}\\\boldsymbol{m}=-{\alpha }_{{\mathrm{em}}}\boldsymbol{E}+{\alpha }_{{\mathrm{mm}}}\boldsymbol{B}\end{array}\right. \;,$

(2)

where

$ \boldsymbol{E} $

and

$ \boldsymbol{B} $

represent the incident electric and magnetic fields, respectively,

$ {\alpha }_{{\mathrm{ee}}} $

$ {\alpha }_{{\mathrm{mm}}} $

, and

$ {\alpha }_{{\mathrm{em}}} $

are the electric, magnetic, and magnetoelectric polarizabilities of the particles. The polarizability

$ {\alpha }_{{\mathrm{em}}} $

is related to the chirality parameter

$ \kappa $

of the particles, and varies with the sign of

$ \kappa $

. For achiral particles,

$ {\alpha }_{{\mathrm{em}}}=0 $

. The polarizabilities

$ {\alpha }_{{\mathrm{ee}}} $

$ {\alpha }_{{\mathrm{mm}}} $

, and

$ {\alpha }_{{\mathrm{em}}} $

are related to the Mie coefficients

$ {a}_{1} $

$ {b}_{1} $

, and

$ {c}_{1} $

$ {\alpha }_{{\mathrm{ee}}}=\frac{{\mathrm{i}}6{\mathrm{\pi}} \epsilon {\epsilon }_{0}}{{k}^{3}}{a}_{1}, {\alpha }_{{\mathrm{mm}}}=\frac{{\mathrm{i}}6{\mathrm{\pi}} \mu {\mu }_{0}}{{k}^{3}}{b}_{1}, {\alpha }_{{\mathrm{em}}}=\frac{6{\mathrm{\pi}} }{\omega {k}^{2}}{c}_{1}\;. $

(3)

The scattering coefficients are defined as:

$ \left\{\begin{array}{l} {a}_{n}=\dfrac{{V}_{n}({\mathrm{R}}){A}_{n}({\mathrm{L}})+{V}_{n}({\mathrm{L}}){A}_{n}({\mathrm{R}})}{{W}_{n}({\mathrm{L}}){V}_{n}({\mathrm{R}})+{W}_{n}({\mathrm{R}}){V}_{n}({\mathrm{L}})}\\{b}_{n}=\dfrac{{W}_{n}({\mathrm{L}}){B}_{n}(R)+{W}_{n}({\mathrm{R}}){B}_{n}({\mathrm{L}})}{{W}_{n}({\mathrm{L}}){V}_{n}({\mathrm{R}})+{W}_{n}({\mathrm{R}}){V}_{n}({\mathrm{L}})}\\{c}_{n}={\mathrm{i}}\dfrac{{W}_{n}({\mathrm{R}}){A}_{n}({\mathrm{L}})-{W}_{n}({\mathrm{L}}){A}_{n}({\mathrm{R}})}{{W}_{n}({\mathrm{L}}){V}_{n}({\mathrm{R}})+{W}_{n}({\mathrm{R}}){V}_{n}({\mathrm{L}})}\end{array}\right.\;,$

(4)

with

$ \left\{\begin{array}{l} {W}_{n}(J)=m{\psi }_{n}\left({m}_{J}X\right)\xi _{n}'(X)-{\xi }_{n}(X)\psi _{n}'\left({m}_{J}X\right)\\{V}_{n}(J)={\psi }_{n}\left({m}_{J}X\right)\xi _{n}'(X)-m{\xi }_{n}(X)\psi _{n}'\left({m}_{J}X\right)\\{A}_{n}(J)=m{\psi }_{n}\left({m}_{J}X\right)\psi _{n}'(X)-{\psi }_{n}(X)\psi _{n}'\left({m}_{J}X\right)\\{B}_{n}\left(J\right)={\psi }_{n}\left({m}_{J}X\right)\psi _{n}'\left(X\right)-m{\psi }_{n}\left(X\right)\psi _{n}'\left({m}_{J}X\right)\end{array}\right.\;,$

(5)

here,

$ X=ka $

, with

$ a $

representing the particle's radius and

$ J={\mathrm{L}},{\mathrm{R}} $

stands for left and right chirality, respectively;

$ {\psi }_{n}\left(\rho \right)=\rho {j}_{n}\left(\rho \right) $

$ {\xi }_{n}\left(\rho \right)=\rho h_{n}^{(1)}\left(\rho \right) $

$ {j}_{n}\left(\rho \right) $

and

$ h_{n}^{(1)}\left(\rho \right) $

denote the spherical Bessel function and the first kind of spherical Hankel function. The relative refractive indices

$ {m}_{{\mathrm{L}}} $

$ {m}_{{\mathrm{R}}} $

and the averaged refractive index

$ m $

can be expressed as

$ {m}_{{\mathrm{L}}}=\sqrt{{\epsilon }_{{\mathrm{p}}}{\mu }_{{\mathrm{p}}}/\epsilon \mu }+\kappa $

$ {m}_{{\mathrm{R}}}=\sqrt{{\epsilon }_{{\mathrm{p}}}{\mu }_{{\mathrm{p}}}/\epsilon \mu }-\kappa $

, and

$ m= ({m}_{{\mathrm{L}}}+ {m}_{{\mathrm{R}}})/2 $

, respectively.

The time-averaged optical force exerted by an electromagnetic field

$ \boldsymbol{E} $

and

$ \boldsymbol{B} $

on a dipolar particle is given by^94,98,99:

$ \boldsymbol{F}=\frac{1}{2}\mathrm{Re} \left[\boldsymbol{d}\cdot (\nabla ){\boldsymbol{E}}^{\boldsymbol{*}}+\boldsymbol{m}\cdot (\nabla ){\boldsymbol{B}}^{\mathbf{*}}-\frac{{k}^{4}}{6\pi \epsilon c}(\boldsymbol{d}\times {\boldsymbol{m}}^{\mathbf{*}})\right]\;. $

(6)

Then, the expression for the optical force on chiral particles can be derived as follows^95,100:

$ \begin{split} \left\langle \boldsymbol{F}\right\rangle =&{\boldsymbol{F}}_{\mathrm{grad}}+{\boldsymbol{F}}_{\mathrm{rad}}+{\boldsymbol{F}}_{\mathrm{curl}}+{\boldsymbol{F}}_{\mathrm{vor}}+{\boldsymbol{F}}_{\mathrm{spin}}+{\boldsymbol{F}}_{\mathrm{flow}} \\=&-\nabla \left\langle U\right\rangle +\frac{1}{c}({C}_{\mathrm{ext}}+{C}_{\mathrm{recoil}})\left\langle \boldsymbol{P}\right\rangle +{C}_{{\mathrm{p}}}c\nabla \times \left\langle {\boldsymbol{S}}_{{\mathrm{e}}}\right\rangle \\&+{C}_{{\mathrm{m}}}c\nabla \times \left\langle {\boldsymbol{S}}_{{\mathrm{m}}}\right\rangle+\mu {\mathrm{Re}}\left({{{\alpha}} }_{{\mathrm{em}}}\right)\nabla \times \left\langle \boldsymbol{P}\right\rangle \\&+ \left[{\gamma }_{{\mathrm{e}}}\left\langle {\boldsymbol{S}}_{{\mathrm{e}}}\right\rangle + {\gamma }_{{\mathrm{m}}} \left\langle {\boldsymbol{S}}_{{\mathrm{m}}}\right\rangle \right] + \frac{c{k}^{4}{\mu }^{2}}{12{\mathrm{\pi}} }{\mathrm{Im}}({{{\alpha}} }_{{\mathrm{em}}}{{\alpha}} _{{\mathrm{mm}}}^{*}){\mathrm{Im}}\left(\boldsymbol{E} \times {\boldsymbol{H}}^{\boldsymbol{*}}\right) .\end{split} $

(7)

From Eq. (7), the optical force on chiral particles can be categorized into six components based on their origins. Here,

$ {\boldsymbol{F}}_{\mathrm{grad}} $

denotes the OGF, with its potential given by

$ \left\langle U\right\rangle = - \dfrac{1}{4}{\mathrm{Re}}\left({\alpha}_{{\mathrm{ee}}}\right){\left| \boldsymbol{E}\right| }^{2} - \dfrac{1}{4}{\mathrm{Re}}\left({\alpha}_{{\mathrm{mm}}}\right){\left| \boldsymbol{H}\right| }^{2} - \dfrac{1}{2}{\mathrm{Re}}\left( {\alpha} _{{\mathrm{em}}} \right){\mathrm{Im}}\left(\boldsymbol{E} \cdot {\boldsymbol{B}}^{*} \right); $

$ {\boldsymbol{F}}_{\mathrm{rad}} $

is the ORP, proportional to the time-averaged Poynting vector

$ \left\langle \boldsymbol{P}\right\rangle $

. The cross-section

$ {C}_{{\mathrm{ext}}}={C}_{{\mathrm{p}}}+{C}_{{\mathrm{m}}} $

is a summation of the electric- and magnetic-dipole part, written as

$ {C}_{{\mathrm{p}}}=k{\mathrm{Im}}({{\alpha} }_{{\mathrm{ee}}})/\epsilon $

and

$ {C}_{{\mathrm{m}}}=k\mu {\mathrm{Im}}({{\alpha} }_{{\mathrm{mm}}}) $

. The term

$ {C}_{{\mathrm{recoil}}}=-\dfrac{{k}^{4}\mu }{6{{\mathrm{\pi}}} \epsilon }\left[{\mathrm{Re}}\left({{\alpha} }_{{\mathrm{ee}}}{\alpha} _{{\mathrm{mm}}}^{*}\right)+{\left| {\alpha}_{{\mathrm{em}}}\right| }^{2}\right] $

is the cross-section directly associated with the recoil force¹⁰¹; the force

$ {\boldsymbol{F}}_{\mathrm{curl}} $

originate from

$ \nabla \times \left\langle \boldsymbol{S}\right\rangle $

(

$ \boldsymbol{S} $

is the spin angular momentum (SAM)) while the force

$ {\boldsymbol{F}}_{\mathrm{vor}} $

originates from

$ \nabla \times \left\langle \boldsymbol{P}\right\rangle $

which is also known relevant to optical torques on achiral particles^102−104;

$ {\boldsymbol{F}}_{\mathrm{spin}} $

results from the contributions of

$ {\boldsymbol{S}}_{{\mathrm{e}}} $

, and

$ {\boldsymbol{S}}_{{\mathrm{m}}} $

, where

$ {\boldsymbol{S}}_{{\mathrm{e}}} $

, and

$ {\boldsymbol{S}}_{{\mathrm{m}}} $

representing the electric and magnetic SAM, respectively.

$ {\gamma }_{{\mathrm{e}}}=2{\omega }^{2}\mu {{{\mathrm{Re}}}}\left({\alpha }_{{\mathrm{em}}}\right)-\dfrac{{k}^{5}}{3{\mathrm{\pi}} {\epsilon }^{2}}{{{\mathrm{Im}}}}\left({\alpha }_{{\mathrm{ee}}}\alpha _{{\mathrm{em}}}^{*}\right) $

and

$ {\gamma }_{{\mathrm{m}}}=2{\omega }^{2}\mu {{{\mathrm{Re}}}}\left({\alpha }_{{\mathrm{em}}}\right)-\dfrac{{k}^{3}\mu }{3{\mathrm{\pi}} \epsilon }{{{\mathrm{Im}}}}\left({\alpha }_{{\mathrm{mm}}}\alpha _{{\mathrm{em}}}^{*}\right) $

;

$ {\boldsymbol{F}}_{\mathrm{flow}} $

is associated with the imaginary component of the Poynting vector, which is widely studied recently^105,106. Together, these forces describe fundamental mechanisms of optical sorting for chiral particles, and form the basis for subsequent developments in enantioselective manipulation using light.

Light carries both linear and angular momentum, which can be transferred to particles, enabling light-matter interactions and underpinning a wide range of optical manipulation strategies. ORP, the mechanical effect of linear momentum transfer from light to matter, occurs when light is refracted, reflected, scattered, or absorbed. This phenomenon is prominently applied in atomic cooling^107−109, optical sorting, particle propulsion, and related areas. Chiral particles of opposite handedness experience distinct ORPs under illumination with circularly polarized light of opposite helicity³⁶. After the conceptual proposal of optical sorting using the ORP in 2013³⁶, two teams from Brasselet's and Cipparrone's groups conducted experiments in 2014^110,111. Using two counter-propagating beams with opposite helicity, left- and right-handed chiral particles can be pushed to the right and left sides, respectively, resulting in the efficient sorting, as shown in Fig. 5(a). Abujetas et al. investigated the transverse spin in the guided mode, which can exert the ORP on chiral particles and enable efficient sorting¹¹².

The OGF is another efficient force correlated strongly to the chirality parameter¹¹³ arising from the inhomogeneous intensity of the optical field and is directed along the gradient of light intensity. This force either attracts particles toward regions of higher intensity or repels them from such regions. The OGF is fundamental in optical tweezers, which have a wide range of applications, including optical trapping¹¹⁴, bioprospecting, particle sorting, biomolecule stretching, and the study of interactions between biological entities. Specifically, the chiral OGF refers to the component of the gradient force that is influenced by the chirality of the particles. Unlike conventional OGF components, which depend on the intensity inhomogeneity of the incident light field, the chiral OGF can be generated even in an optical field with uniform light intensity¹¹⁵. Chiral particles can be selectively trapped or repelled from a tightly focused trap, which is principally feasible for chiral sorting^{37,111,116−120}. Helicity gradient serves as another interesting toolkit for sorting chiral particles. For instance, Kravets et al. reported the selective displacement of chiral particles with different handedness in a line-shaped light field with helicity gradient³⁹, as shown in Fig. 5(b). Though physically interesting, this type of optical force is exceedingly small, at least two orders of magnitude smaller than the conventional optical gradient force.

Recently, the OLF has been utilized for chiral sorting. The OLF, a unique force acting perpendicular to the direction of light propagation and independent of both intensity and phase gradients, has garnered significant attention due to its intriguing underlying physics and potential applications in enantiomer sorting. The generation of an OLF relies on breaking the symmetry of the system, allowing light to transfer lateral momentum to an object. Various mechanisms can produce OLFs, including the coupling of light with the object's chirality^121,122, spin-orbit interaction^123−125, and surface plasmon polaritons (SPPs)^126−128. The generation of an OLF relies on breaking the symmetry of the system, allowing light to transfer lateral momentum to an object. In a plane wave, Wang and Chan proposed the fundamental mechanism of the leverage of the OLF for sorting chiral particles with opposite handedness³⁸. The experimental demonstration has been hugely lagging behind. In 2021, Shi et al. placed chiral particles at the interface of air and water and illuminated them with a linearly polarized light wave, as shown in Fig. 6(a)⁹². Through the transverse transfer of momentum of light and particle, an OLF is generated to separate chiral particles. A simple plane wave requires the assistance of the interface for chiral sorting. A constructive beam, such as standing waves from two wave interference can generate OLFs directly. Chen et al. achieved the chiral sorting using a standing wave from two linearly polarized beams⁹⁵, as shown in Fig. 6(b). The mechanism relies on the generation of transverse spin, as shown in Eq. (7). The standing wave can also be configured from two waves with different polarizations⁹⁶, such as linearly and elliptically polarized light beam (Fig. 6(c)). In this case, multiple forces can coordinate, such as forces from the transverse spin and spin momentum, making this method more efficient and dynamic than the linear case in Fig. 6(b). Recently, Shi et al. observed the intricate chiral optical force on a chiral sphere in a spin-curl light field, as shown in Fig. 6(d)¹²⁹. A chiral particle is placed on a surface and illuminated with an elliptically polarized focused beam. In this system, multiple parameters, such as the transverse spin, Belinfante spin momentum and energy vortex (curl of the energy flow), all could have profound effects on the chiral OLF. In their work, they have achieved sorting of chiral particles with different sizes and handedness. By switching different polarizations of light, the direction of OLF on the chiral particles can be switched.

Apart from the intriguing OLF, the counterintuitive OPF can also be employed for chiral sorting. Previous studies have successfully demonstrated optical manipulation techniques, such as pushing, trapping, and rotating tiny objects ranging from nanometers to tens of micrometers in size. However, manipulating objects through backward pulling has remained elusive and counterintuitive. Generally, with a standard beam lacking a longitudinal gradient, it is expected that an object illuminated by light would be pushed forward. Yet, about a decade ago, researchers discovered a new and counterintuitive phenomenon known as the OPF, which pulls an object toward the light source^{101,130−132}. Ali et al. used two circularly polarized beam to construct an interference field and control the incident angle for selectively generate an OPF on a specific chiral particle⁴¹, as shown in Fig. 6(e). When the number of light beams becomes three, an OPF can also be generated (Fig. 6(f))¹³³. Zheng et al. designed an interferential optical field which is composed of three plane waves with the same circular polarization, to sort chiral particles, which obviously improves the experimental feasibility attributing to the relatively wide tunable range of the directions of wave vectors. In this system, particles with certain chirality will be stably trapped in the periodic intensity maximum spot, exerted by an optical pulling force along the −z direction.

Structured light beams for chiral sorting. The force magnitude and spatial selectivity achievable with simple optical fields remain limited. We then focus on the discussion of the structured light beams with additional degrees of freedom for chiral force engineering. A typical example is the vector beam. Li et al. reported a fundamental scheme to selectively trap and repel chiral particles with opposite real parts of the chirality parameter⁴². By controlling the imaginary parts of the chirality parameter, different particles can rotate clockwise or counter-clockwise in the vector beam. Later, the same team utilized a focused vector beam with orbital angular momentum for particle manipulation^134,135, as shown in Fig. 7(a). Focused vector vortex beams carrying radial-splitting optical chirality can electively trap one chiral particle inside or outside the intensity maxima depending on the sign of the orbital angular momentum. Chiral particles with different handedness can be trapped on different orbits and experience enhanced optical forces. Vector beams carrying different topological charges transfer angular momentum to chiral particles with opposite handedness differently, resulting in an enantioselective optical force to either push or repel certain chiral particles¹³⁶.

As shown in Fig. 7(b), Xiong et al. proposed an optical method that selectively traps enantiomers by using tightly focused fractional vector beams¹³⁷. In their proposed model, such a focused beam forms multiple local optical CDs with opposite signs at the focal plane. They found that focused fractional vector beams can stably trap the enantiomers at the local positions with the minimum or maximum CDs according to the handedness of enantiomers. Their work may find applications in achieving precise and stable capture of multiple pairs of enantiomers.

In addition to these methods, Li et al. designed a controllable chiral optical field by tightly focusing two tailored vector beams in a 4π optical microscopic system with two high-NA objective lenses, as shown in Fig. 7(c)¹³⁸. By modulating the wavefronts of the incident vector beams with appropriately designed phase masks, a chiral optical field with multiple spots carrying switchable handedness or controllable chirality can be generated. The location, the number and the handedness of such chiral spots can be arbitrarily adjusted depending on the actual application requirements. This controllable chiral field has practical application value for achieving precise and stable enantioselective separation, chiral detection and chiral sensing at the nanoscale.

Recently, Li et al. developed a novel optical method for chiral enantiomer sorting by inversely designing the polarization state of an input Gaussian beam focused through a high-NA objective lens (Fig. 7(d))¹³⁹. The technique employs orthogonal circular polarization bases with a spatially varying phase to generate tailored chiral optical fields. This creates twin foci with opposite optical chirality densities in the focal plane, enabling simultaneous trapping of left- and right-handed enantiomers at predetermined positions. The approach achieves non-contact separation of chiral particles with freely adjustable trapping positions, offering significant value for pharmaceutical research and chiral sensing applications.

Other attempts include the utilization of structured caustic vector vortex field¹⁴⁰, multiple longitudinal polarization vortex structures¹⁴¹, focused vector polarized hollow beams¹⁴², coordination of two vector beams¹³⁸, vector Lissajous beams¹⁴³, etc.

Near-field and nanophotonic for chiral sorting. Free-space methods normally generate relatively small optical forces due to loosely confined light fields. A further leap in force enhancement requires the subwavelength field confinement, naturally leading to near-field and nanophotonic platforms. Near-field configures with a diversity of mechanisms show promising in enhancing optical forces and enabling efficient chiral sorting¹⁴⁴. The chiral polarizability and optical force in the near field are much greater than the far field¹¹³. Typical examples include evanescent waves, optical fibers and waveguides. Shortly after the introduction of the OLF in 2014, Hayat et al. excited the transverse spin in an evanescent wave via the total internal reflection in 2015¹⁴⁵. Linearly polarized light generates the transverse spin perpendicular to the incident plane and generate the OLF, as shown in Fig. 8(a). This force is demonstrated to be greater than that generated by placing the chiral particle on a surface and illuminating it using a linearly polarized plane wave³⁸. Cao et al. proposed a graphene-coated chalcogenide nanowire to produce mid-infrared, chiral surface plasmon polaritons, which can be switched on and off by non-volatile structural state transitions in the dielectric constants of the chalcogenide glass. Chiral particles with size of sub-10 nm and having opposite handedness experience OLFs that differ in magnitude and sign, resulting efficient chiral sorting¹⁴⁶, as shown in Fig. 8(b).

Compared with reconfigurable nanowires, waveguides are more common with standard fabrication process. Fang et al. reported an intriguing chiral sorting configuration using the slot waveguide⁴³, as shown in Fig. 8(c). The counter-propagating slot waveguides generate strongly enhanced electromagnetic chirality gradient that is confined in the slot. Chiral particles with opposite handedness can be trapped in two potential wells in different positions, paving the way for large-scale chiral sorting in optofluidic systems. Martínez-Romeu et al. systematically investigated the chiral optical forces on dielectric waveguides for chiral sorting¹⁴⁷, as shown in Fig. 8(d). Chiral optical forces under the quasi-TE modes at 405 nm and combined effect from the quasi-TE and quasi-TM modes at 1310 nm, demonstrating the efficient separation of chiral nanoparticles in two seconds. This method shows that the SiN waveguides have a great efficiency in chiral sorting, greatly reducing the consumed sorting time.

Recently, optical sorting using metasurfaces has raised a great diversity of attention in the past few years¹⁴⁸. Those methods leverage the strong capabilities of metasurfaces in manipulating the intensity, phase and polarization distributions of light and versatile near-field manipulation configurations. Metasurfaces have been utilized to sort achiral particles with sizes down to 10 nm^149,150. They have also shown great efficiency in sorting chiral particles. This particular research direction starts when Solomon et al. utilized the high-index pillar array to enhance the optical chirality⁵³, which also paves the way for the high-precision detection of chiral molecules.

Cao et al. proposed the Fano-enhanced chiral optical force with visible light using a plasmonic nanoaperture¹⁵¹, as shown in Fig. 9(a). Multipolar interference Fano resonances are excited under circularly polarized light illumination by the modal energy splitting resulting from the interaction between resonant modes in symmetric outer and asymmetric inner Au split-rings. The lateral chiral and non-chiral gradient forces enable helicity-dependent transverse deflection of chiral nanoparticles above the aperture. This mechanism offers a promising platform for all-optical efficient chiral sorting. Later, Cao et al. also reported another configuration for the generation the combined dipole-octupole Fano resonance for chiral sorting¹⁵², as shown in Fig. 9(b). Such Fano resonance significantly enhances the chiral gradient force, being capable for sorting sub-10 nm chiral nanoparticles with distinct potential wells. Those approaches sort chiral particles in a static environment, which results in a relatively low throughput. Recently, Zhang et al. reported an architecture with metasurface on top of a multi-layer thin film⁴⁵, as shown in Fig. 9(c). This metasurface excites a toroidal dipole mode, which generates enhanced optical forces on sub-20 nm chiral particles. Chiral particles with opposite handedness have potential wells in different locations. They can be sorted in a fast flow velocity of 800 µm/s under the synergy of optical and fluidic forces. This is the first demonstration of sorting chiral particles in a fast flow stream, opening the gate for practical biochemical applications.

There have been quite a few other examples of metasurface-enabled chiral sorting. For instance, Safkat et al. presented a novel all-optical technique for distinguishing classes of nanoscale Mie objects by placing them over a metasurface of double-lined gold nanostructures. This configuration enables efficient on-chip sorting of silica (dielectric), gold (plasmonic), and chiral nanospheres¹⁵³. Tang et al. proposed an on-chip platform using surface plasmon polaritons to generate five transformable topological optical lattices via tunable polarization and phase vortices, overcoming limitations of traditional complex systems¹⁵⁴. Through dipolar analysis and simulations, they show that the spin density force is the key mechanism for out-of-plane sorting of large chiral particles (radius > 100 nm) and introduce a dual-function microflow system for trapping and sorting.

Notably, recent years have witnessed the fast development of fascinating new physics using metasurfaces. Well-known examples are BICs^155−163 and EPs^28,164−172. Recently, Mao et al. presented a silicon metasurface featuring nanodisks with offset holes, which supports a sharp quasi-BIC (qBIC) magnetic dipolar resonance originating from symmetry breaking. This qBIC MD resonance significantly enhances the chiral lateral force on sub-2 nm enantiomers under linear polarization by generating a strong chirality density gradient with alternating sign around the disk, while exhibiting minimal electromagnetic density gradient⁴⁴, as shown in Fig. 10(a). It also creates four pairs of deep optical potential wells (∼13 k_BT) uniformly distributed around the resonator edge, enabling simultaneous separation of four enantiomer pairs, thereby advancing all-optical enantioseparation. Based on similar principles, left-handed and right-handed nanoparticles could experience distinct potential wells with different positions or depths using BICs^173,174.

Recently, Jin et al. designed metasurfaces based on asymmetric silicon dimers supporting dual qBICs¹⁷⁵ (Fig. 10(b)). These qBICs were engineered to achieve near-perfect spatial overlap of electric and magnetic fields near their anti-crossing point, resulting in a remarkable 10⁴-fold enhancement of the superchiral field. Enantioselective optical forces on single molecules reaching magnitudes of pN/mW·μm² were thus generated. Furthermore, switching of the superchiral field's handedness and the resulting force direction was enabled by encircling the anti-crossing point. Analysis of the qBIC-assisted chiral separation dynamics highlights the promising potential of this approach for applications in chiral sensing and sorting with profound precision.

An exceptional point is a special type of degeneracy occurring in non-Hermitian systems (like those with loss or gain) where not only eigenvalues (frequencies) but also the corresponding eigenvectors (modes) of the system coalesce. A two-mode non-Hermitian system can be described by the Hamiltonian:

$ {{\boldsymbol{H}}}=\left[\begin{matrix}{\omega }_{1}-{\mathrm{i}}{\gamma }_{1} & \kappa \\ \kappa & {\omega }_{2}-{\mathrm{i}}{\gamma }_{2} \end{matrix}\right]\;, $

(8)

where

$ {\omega }_{1{,}2} $

and

$ {\gamma }_{1{,}2} $

denote the resonance frequencies and the gain/loss rate of the two modes, respectively, and

$ \kappa $

is the coupling strength. The eigenvalues are obtained as:

$ {E}={\omega }_{{\mathrm{ave}}}-{\mathrm{i}}{\gamma }_{{\mathrm{ave}}}\pm \sqrt{{\left({\omega }_{{\mathrm{diff}}}-{\mathrm{i}}{\gamma }_{{\mathrm{diff}}}\right)}^{2}+{\kappa }^{2}}, $

(9)

where

$ {\omega }_{{\mathrm{ave}}}=({\omega }_{1}+{\omega }_{2})/2 $

$ {\gamma }_{{\mathrm{ave}}}=({\gamma }_{1}+{\gamma }_{2})/2 $

$ {\omega }_{{\mathrm{diff}}}= ({\omega }_{1}- {\omega }_{2})/2 $

, and

$ {\gamma }_{{\mathrm{diff}}}=({\gamma }_{1}-{\gamma }_{2})/2 $

. For a PT-symmetric system, where

$ {\omega }_{1}={\omega }_{2}={\omega }_{0} $

and

$ {\gamma }_{1}=-{\gamma }_{2}={\gamma }_{0} $

, the eigenvalues simplify to

$ {E}={\omega }_{0}\pm \sqrt{{\kappa }^{2}-\gamma _{0}^{2}} $

. Here, the system exhibits a phase transition: when

$ \kappa \gt {\gamma }_{0} $

, the eigenvalues remain real (unbroken PT phase), while for

$ \kappa \lt {\gamma }_{0} $

, they form complex-conjugate pairs (broken PT phase). At the critical condition

$ \kappa ={\gamma }_{0} $

, the two eigenvalues and eigenvectors simultaneously merge, giving rise to an EP. This coalescence leads to unique properties, such as extreme sensitivity to perturbations and topological features, making EPs valuable for designing sensors, lasers, and devices controlling light in novel ways^176,177. Though interesting, this topic only has a few works at present. Zhang et al. demonstrated enhanced optical forces on chiral particles positioned within a non-Hermitian waveguide lattice¹⁷⁸, achieving EPs through unidirectional coupling under linear plane wave excitation, as confirmed by full-wave simulations. Furthermore, they found that higher-order EPs generally yield stronger forces, which exhibit a distinct skin effect, maximizing at one end of the particle lattice. Recently, Liu designed a silicon microfluidic chip leveraging a vector EP, formed by breaking mirror-symmetry in lossy waveguides to couple orthogonal modes, to achieve highly efficient chiral nanoparticle separation¹⁷⁹, as shown in Fig. 10(c). This vector EP generates a powerful superchiral gradient field within the chip, inducing strong chiral gradient forces that drive nanoparticles of opposite handedness to opposite sides of an extended slot. Furthermore, cascaded vector EPs in a single chip are implemented to significantly increase the spatial separation distance, demonstrating the feasibility and efficiency of this approach through particle tracking simulations accounting for nanoparticle thermal motion.

Beyond optomechanical interactions, it is worth noting that chiral separation can also be achieved using other physical field-based approaches, such as electric¹⁸⁰, magnetic¹⁸¹, and acoustic¹⁸² fields. For example, chiral particles placed in rotating electric fields may experience enantioselective transport, resulting in opposite motion depending on their handedness. Similarly, enantiospecific interactions have been demonstrated for chiral molecules coupled to perpendicularly magnetized substrates. While these approaches offer valuable complementary pathways for chiral separation, they typically depend on material-specific responses, complex device configurations, or additional operation steps. In contrast, optical sorting enables contactless, non-destructive, and highly tunable manipulation through engineered light-matter interactions, allowing chiral selectivity to be flexibly programmed using optical fields alone.

3　Chiral detection

Less

In this section, we first briefly review representative non-optical methods for chiral detection, and then systematically survey optical approaches, with an emphasis on recent advances in chiral detection enabled by enhanced superchiral electromagnetic fields.

3.1　Non-optical techniques for chiral detection

For non-optical detections, electrochemical methods are particularly powerful, where chiral discrimination is achieved by modifying electrodes with chiral selectors (e.g., cyclodextrins, amino acids, quinidine derivatives, or chiral polymers) or employing chiral ionic liquids. Enantiomers exhibit different redox potentials or electron transfer kinetics at these chiral interfaces, allowing their differentiation via voltammetric techniques like cyclic voltammetry or differential pulse voltammetry. The mass spectrometry coupled with chiral separation techniques like chromatography or electrophoresis provides another potent non-optical route. While the mass spectrometry itself is not inherently chiral, it becomes a chiral detector when paired with methods that separate enantiomers before ionization, or by using chiral matrices or ion-mobility separation that can exploit subtle differences in ion-mobility cross-sections or fragmentation patterns between enantiomers. Other non-optical strategies leverage the principles of separation science and specific interactions at chiral interfaces. High-performance liquid chromatography and gas chromatography equipped with CSPs remain workhorses for chiral analysis and preparative separation. These CSPs, composed of materials like derivatized cyclodextrins, macrocyclic glycopeptides (e.g., vancomycin), or Pirkle-type phases, selectively retain one enantiomer over the other based on diastereomeric complex formation, enabling detection via universal detectors like refractive index or evaporative light scattering, avoiding the need for chromophores. Nuclear Magnetic Resonance (NMR) spectroscopy, while technically involving electromagnetic radiation, detects chirality through chemical shifts rather than optical activity; chiral solvating agents or chiral shift reagents form transient diastereomeric complexes with enantiomers, causing their NMR signals to split, allowing quantification. Additionally, sensor technologies like quartz crystal microbalances or field-effect transistors functionalized with chiral recognition elements can transduce the selective binding of one enantiomer into measurable electrical or mass signals. These diverse non-optical approaches provide crucial tools for chiral analysis, especially for molecules lacking strong chromophores or when high-throughput analysis is required. For more detailed overview of chiral detection using non-optical methods, one can refer to abundant review papers^70,183−191. While non-optical techniques provide mature and accurate chiral detection, they typically rely on chemical or separation-based processes, normally lack real-time and in-situ capabilities, and largely limited to ensemble-averaged measurements. In contrast, optical approaches enable contactless, non-destructive, and real-time detection with minimal sample preparation, and recent nanophotonic and superchiral field engineering have made them particular powerful for detecting weak chiral signals.

3.2　Optical techniques for chiral detection

Prior to 2020, the detection and structural characterization of chiral molecules relied heavily on advanced spectroscopic techniques exploiting their intrinsic chiroptical responses. CD spectroscopy stands as the gold standard, directly probing the differential absorption of left- and right-circularly polarized light. This provides unparalleled insights into the absolute configuration of small molecules, conformational dynamics, and the secondary structure of critical biomolecules like proteins and nucleic acids, cementing its role as an indispensable tool across chemistry, biochemistry, and pharmaceutical research. Optical rotatory dispersion^18,192,193 (ORD) measures how much a chiral molecule rotates the plane of linearly polarized light, and how this rotation changes with the light's wavelength (or colour). Although CD spectroscopy largely replaced ORD for routine quantitative analysis, ORD still provides valuable insights that complement CD data. It is also historically one of the major techniques for studying chirality with light. Furthermore, ORD remains essential for applying specific rules (like the octant rule) that connect spectral patterns to molecular structure, and for fundamental research in chiroptical phenomena. Both techniques primarily operate in the ultraviolet-visible range, requiring suitable chromophores. Significantly, by 2020, vibrational counterparts had matured into powerful, complementary methodologies: Vibrational Circular Dichroism^193,194 (VCD) measured analogous differential absorption in the infrared region, arising from vibrational transitions. This provided atomic-level resolution of stereochemistry and conformation, uniquely enabling the analysis of molecules lacking UV-Vis chromophores. Raman Optical Activity¹⁹⁵, detecting the differential scattering intensity of right- versus left-circularly polarized light, emerged as a particularly robust probe for biomolecular structure in aqueous environments, delivering rich information on dynamic conformational ensembles. Photoelectron circular dichroism^196,197 (PECD) represents another powerful and well-established technique for chiral detection, particularly in the gas phase. Unlike conventional optical circular dichroism, PECD arises from the forward-backward asymmetry in the angular distribution of photoelectrons emitted from chiral molecules under circularly polarized light, leading to significantly enhanced chiral sensitivity. Importantly, PECD does not rely on magnetic dipole transitions and can yield asymmetries of several percent even for randomly oriented molecules, making it an important complementary technique for probing molecular chirality.

Superchiral light refers to an electromagnetic field whose local optical chirality density significantly exceeds that of circularly polarized plane waves. These plane waves are the standard source of chirality in traditional techniques like CD. The mathematical formulation of optical chirality can be traced back to 1964 by Lipkin¹⁹⁸ in the context of electromagnetic conservation laws. However, this quantity was long regarded as mathematically elegant but physically insignificant. Optical chirality C is formally defined as:

$ C=\frac{{\epsilon }_{0}}{2}\boldsymbol{E}\cdot \nabla \times \boldsymbol{E}+\frac{1}{2{\mu }_{0}}\boldsymbol{B}\cdot \nabla \times \boldsymbol{B}\;, $

(10)

which can be simplified to the more widely adopted form¹⁹⁹:

$ C=-\frac{\omega }{2{c}^{2}}{\mathrm{Im}}\left({\boldsymbol{E}}^{\mathbf{*}}\cdot \boldsymbol{H}\right)=-\frac{\omega }{2{c}^{2}}\left| \boldsymbol{E}\right| \left| \boldsymbol{H}\right| {{\mathrm{cos}}}({\beta }_{{\mathrm{i}}\bf\boldsymbol{E},\boldsymbol{H}})\;, $

(11)

where

$ {\epsilon }_{0} $

and

$ {\mu }_{0} $

are the permittivity and permeability of free space,

$ \omega $

is the angular frequency,

$ c $

is the speed of light, and E, B, H denote the complex electric, magnetic and auxiliary magnetic field vectors, respectively. The term

$ {\beta }_{{\mathrm{i}}\boldsymbol{E},\boldsymbol{H}} $

denotes the phase angle between

$ {\mathrm{i}}\boldsymbol{E} $

and H. This quantity effectively characterizes both the handedness and the strength of chirality in an electromagnetic field. Therefore, maximizing optical chirality requires simultaneously satisfying three key conditions for electric and magnetic field components: (i) strong and spectrally overlapping amplitudes, (ii) parallel and spatially coincident field distributions, and (iii) a phase difference of π/2 between them.

The physical relevance of optical chirality was revitalized in 2010²⁰⁰, when Tang et al. first proposed the concepts of "superchiral light" and "optical chirality". They demonstrated that the absorption rate of chiral molecules is governed not only by their intrinsic chiral polarizabilities but also by the optical chirality of the surrounding electromagnetic field. Specifically, the absorption rate of enantiomers under left- and right-circularly polarized light can be expressed as:

$ {A}^{\pm }=\frac{\omega }{2}\left(a_{{\mathrm{ee}}}^{{\mathrm{''}}}{\left| \boldsymbol{E}\right| }^{2}+\mu _{0}^{2}a_{{\mathrm{mm}}}^{{\mathrm{''}}}{\left| \boldsymbol{H}\right| }^{2}\right)\mp \frac{2}{{\epsilon }_{0}}a_{{\mathrm{em}}}^{{\mathrm{''}}}C, $

(12)

where

$ a_{{\mathrm{ee}}}^{{\mathrm{''}}} $

$ a_{{\mathrm{mm}}}^{{\mathrm{''}}} $

, and

$ a_{{\mathrm{em}}}^{{\mathrm{''}}} $

represent the imaginary parts of electric, magnetic, and magnetoelectric (chiral) polarizabilities of the chiral molecule, respectively. Since the CD arises from the differential absorption of left- and right-circularly polarized light, this yields a direct relationship between CD and optical chirality:

$ \mathrm{CD}={A}^+-{A}^-=-\frac{4}{{\epsilon }_{0}}a_{{\mathrm{em}}}^{{\mathrm{''}}}C . $

(13)

This finding highlights that CD is not an inherent molecular property alone but a coupled effect between molecular characteristics and the electromagnetic environment. By revealing this dependence, this work reshaped the theoretical framework of chiral detection enhancement and inspired extensive efforts aimed at engineering electromagnetic responses to generate optimal superchiral fields. Furthermore, their proposal of a standing-wave configuration offered an initial conceptual strategy for improving chiral detection sensitivity, which laid the foundation for subsequent experimental validations of superchiral light and related chiral detection enhancement schemes.

The chiral sensing using superchiral light was proposed in the same year (2010) using the metasurface⁴⁸, which will be introduced in detail in the metasurface part. Later in 2011, Tang et al. introduced fundamental research on the superchiral light, achieving an 11-fold enhancement in chiral discrimination over conventional circularly polarized light⁴⁹, as shown in Fig. 11. By reflecting circularly polarized light off a partially reflective mirror, the team generated standing waves with localized regions of extreme optical chirality density, amplifying the dissymmetry factor g for chiral molecule excitation. Experimental validation used a nanofabricated sandwich structure to position chiral biperylene derivatives with sub-ångström stability, confirming enhanced dissymmetry (g ≈ 0.015 vs. CPL's 0.0014) that aligned with theoretical predictions within 15%. This tunable technique enables stronger chiral sensing without near-field optics, with significant applications in pharmaceuticals and asymmetric synthesis.

Successively, various mechanisms to enhance the superchiral light have been proposed. Notable examples include plasmonics, nanocavities, metasurfaces, etc. Conventional methods such as SERS^201,202, have also evolved recently for chiral biomolecule detection. Especially, recent years have seen the integration of artificial intelligence in chiral sensing. In the next section, we will discuss these issues separately.

Plasmonic-based chiral detection. Plasmonics, the science of light manipulation at the nanoscale using metallic nanostructures, enables the generation of superchiral electromagnetic fields. These fields dramatically amplify chiral light matter interactions beyond conventional circularly polarized light, achieving significantly higher sensitivity for biomolecular detection. Plasmonics leverages metallic nanostructures (gold/silver nanoparticles, nanorods, dimers) as optical antennas to concentrate incident light into nanoscale hotspots, generating intense localized electromagnetic fields. Through deliberate geometric engineering, such as asymmetric gaps in nanoparticle dimers or chiral configurations, these structures manipulate the spatial relationship and relative phase between enhanced electric and magnetic field components. This precise phase control enables constructive interference that maximizes the vector product E·H, directly amplifying optical chirality density (

$ C=-\omega {\mathrm{Im}}({\boldsymbol{E}}^{\mathbf{*}}\cdot \boldsymbol{H})/2{c}^{2} $

) beyond conventional circularly polarized light. Unlike plane waves with fixed E-H relationships, plasmonic hotspots create spatially varying superchiral fields where the localized optical chirality can exceed reference values for circularly polarized light in free space,

$ {C}_{0}=\pm \omega {\epsilon }_{0}\boldsymbol{E}_{0}^{2}/2{c}^{2} $

, by several orders of magnitude, fundamentally enabling nanoscale chirality manipulation unattainable with traditional sources.

Plasmon-enhanced chiral sensing offers transformative capabilities: massive signal amplification (enabling single-molecule detection and trace analysis of biomolecules), ultra-local probing below the diffraction limit (permitting spatial mapping of chirality in cellular microdomains or surface-confined systems), and versatile spectral tuning via nanostructure design. Critically, these plasmonic substrates integrate seamlessly with spectroscopic techniques such as SERS-enhanced circular dichroism and microfluidic lab-on-a-chip platforms, facilitating applications in pharmaceutical screening, amyloid disease diagnostics. This synergy of sensitivity, resolution, and compatibility establishes plasmonic superchiral light as a paradigm-shifting tool for advanced chiral biosensing.

Funck et al. engineered a DNA origami-based nanosensor functionalized with chiral gold nanorods to selectively bind and detect target RNA molecules via plasmonic CD modulation²⁰³, as shown in Fig. 12(a). Enhanced chiral optical activity was observed when the sensor interacted with complementary RNA sequences, with a detection limit of 100 pM achieved under physiological conditions. This passive, amplification-free method^204−207 holds transformative potential for point-of-care diagnostics, enabling rapid, label-free detection of low-abundance viral RNAs (e.g., hepatitis C virus) in clinical samples with minimal sample preprocessing.

Rodier et al. demonstrated a novel method using chiral plasmonic nanostructures to detect the previously "invisible" chiral surface charge distributions of biomacromolecules like proteins²⁰⁸, as shown in Fig. 12(b). This method successfully discriminates between structurally homologous proteins (type II dehydroquinase from different organisms), which are indistinguishable by conventional circular dichroism spectroscopy, by sensing differences in their chiral surface charge signatures manipulated via pH. It is a powerful tool for distinguishing between structurally homologous biomaterials and provides insights into macromolecular interactions.

Conventional plasmonic sensing faces challenges in achieving single-molecule chiral detection due to difficulties in gap size control, molecular orientation constraints, and the detrimental impact of quantum tunnelling on local field enhancement. To overcome these limitations, Zhang et al. designed a tunable chiral supramolecular plasmonic system combining helical oligoamide sequences and a nanoparticle-on-mirror resonator²⁰⁹, as shown in Fig. 12(c). This system operates across classical and quantum regimes and significantly enhances chiral sensitivity in the quantum tunnelling regime, despite reduced local E-fields, due to strong Coulomb interactions between the chiral and light in the resonator and additional enhancement from tunnelling electrons. Consequently, the detection of a minimum of four molecules per single Au particle and the resolution of local enantiomeric excess within monolayers are demonstrated, pushing chiral sensing towards the ultimate single-molecule limit.

Plasmonics offers revolutionary advantages for chiral sensing, primarily through massive local field enhancement generated by nanostructures like nanoparticles, dimers, chiral structures, core-shells, or cavities^51,210−220. This enables detection of ultra-low analyte concentrations (down to attomolar levels) and significantly amplifies weak intrinsic chiroptical signals (e.g., CD, ORD) via plasmon-coupled chirality. Plasmonic platforms also provide label-free, real-time detection and can discriminate structurally homologous biomolecules, which are inaccessible to conventional spectroscopy. Despite its high sensitivity, plasmonic chiral sensing faces critical challenges: quantum tunnelling effects in sub-nm gaps reduce local electric fields, diminishing signal enhancement; the nanostructures are difficult to fabricate and reproduce; background interference from non-specific binding disturbs measurement; a significant heating effect may do huge harm to biosamples and hinders practical biomedical applications. In contrast, a dielectric metasurface serves as a promising candidate for bio-friendly chiral sensing. In the following section, we will elaborate on this issue in detail.

Nanophotonic and metasurface-based chiral detection. A metasurface exploits subwavelength nanostructured arrays to precisely tailor light-matter interactions through local phase modulation and polarization control. These metasurface-based platforms offer transformative capabilities for electromagnetic field manpulation^221−233. For instance, ultrabroad wavelength engineering, covering UV to THz regimes; deep subwavelength hotspot control, with size down to 10 nm; minimalized sensing devices with large-scale fabrication possibilities; biocompatible labelling, facilitating specific differentiation; integrable with quantum techniques, enabling entanglement-enhanced chiral sensing with huge signal-to-noise ratios.

Metasurface chiral sensing started with the first employment of the concept of "superchiral" light in 2010. Hendry pioneered ultrasensitive detection and structural characterization of chiral biomolecules using superchiral electromagnetic fields generated by plasmonic planar chiral metamaterials⁴⁸, as shown in Fig. 13(a). This novel principle leverages the dramatically enhanced chiral asymmetry within the near-fields of metamaterial, achieving differences in the effective refractive indices of chiral samples exposed to left- and right-handed superchiral fields that are up to 10⁶ times greater than those observed in conventional optical polarimetry measurements. As the first demonstration of superchiral fields for chiral sensing, this work established a ground-breaking biospectroscopy approach. It revealed unique sensitivity to specific biomolecular structures, such as β-sheets, opening a new paradigm for ultrasensitive bioanalysis. This has profound implications for detecting amyloid diseases and viruses, while fundamentally advancing nanophotonic chiral sensing by demonstrating tailored electromagnetic field chirality far exceeding the incident illumination.

Successively, Zhao et al. developed a novel approach using twisted plasmonic metamaterials with stacked achiral nanorod layers under relative rotation to amplify chiral interactions²³⁴, as shown in Fig. 13(b). The major significance of this design is its ability to isolate and directly obtain the sign of molecular chirality using enantiomeric pairs of metamaterials (positive and negative 60-degree twist). After appropriate post-processing, this method enables unambiguous handedness detection while suppressing the large background CD signal inherent to shift-based methods. Furthermore, it achieves unprecedented sensitivity down to zeptomole levels (10⁻²¹ mole), several orders of magnitude smaller than prior works. This work introduces an ultrathin, planarized nanophotonic interface designed to detect chiral molecules exhibiting inherently weak circular dichroism in the visible and near infrared spectral range.

These works with plasmonic structures achieve high sensitivity in chiral sensing^{56,220,235−237}, while having some limitations as discussed in the section plasmonic chiral sensing. An alternative solution is to design all-dielectric metasurfaces to avoid the potential heating effect. Solomon et al. pioneered one of the first dielectric metasurfaces (silicon nanodisk arrays) for chiral sensing and enantioselective separation, overcoming the limitation in plasmonic systems⁵³, as shown in Fig. 13(c). By leveraging Mie resonances and Kerker conditions to spectrally overlap electric and magnetic modes, the uniform sign and large volume enhancements in optical chirality density and Kuhn's dissymmetry factor can be achieved. This enables enantiopure interactions across the entire metasurface, facilitating practical chiral separation. The platform has an increase in yield by a factor of >2000 for visible wavelength photoionization reactions while maintaining field intensities, offering a scalable, low-loss solution for efficient all-optical resolution of racemic mixtures.

Building upon this foundation, subsequent studies have advanced the concept from detecting single-species enantiomers to identifying complex mixtures, and from UV-Vis based measurements to VCD detection. More recently, Biswas et al. demonstrated surface-enhanced infrared absorption-induced VCD detection of thalidomide at ultralow concentration down to 50 μM using an achiral plasmonic system²³⁸. The experiments revealed a remarkable 13 orders of magnitude enhancement in sensitivity compared to conventional far-field VCD techniques. Successfully, this approach was further generalized by arraying the nanostructures into pixelated patterns across a broad infrared range, thereby enabling the simultaneous interrogation of multiple chiral species²³⁹, as shown in Fig. 13(d). By exploiting the distinct vibrational absorption "fingerprints" of different molecules, this strategy realizes a unique chiral "barcoding" scheme capable of reliably identifying and distinguishing enantiomers and biomolecules. Collectively, these advances highlight the potential for achieving high-sensitivity chiral detection in realistic molecular mixtures, making a significant step toward real-world applications.

In the past few years, more and more elegant and intriguing metasurface architectures have been proposed to expand the capabilities and increase the sensitivities in chiral sensing. For instance, nanocavities^56,240−244, special particles^{217,245−250} (e.g., core-shell, upconvention, etc), layered structures^45,251−261, achiral designs^{20,53,244,262−266}, and so forth^267−269.

Unlike Zhao's design with aligned plasmonic structures²³⁴, Cen et al. developed ultrathin self-aligned suspended chiral metasurfaces using single-step electron beam lithography to achieve globally enhanced optical chirality²⁵³, as shown in Fig. 13(e). Label-free enantio-discrimination at the zeptomole level was experimentally demonstrated, enabled by bidirectional molecular exposure and near-field plasmonic coupling. Leveraging giant chiroptical response, this metadevice enables ultrathin circular polarizers, chiral molecular sensing, and chiral information processing. Recently, Indukuri et al. engineered achiral negative-index metamaterial nanocavities to generate globally enhanced, enantiopure superchiral fields for fluorescence-detected circular dichroism sensing²⁴⁰, as shown in Fig. 13(f). CD measurements can be significantly enhanced through background-free detection of flavin mononucleotide chiral molecules, validated by 8-fold enhanced fluorescence decay rates and spatial uniformity in dissymmetry factors (~0.1). This breakthrough enables single-molecule chiral sensing by overcoming intrinsic background limitations of chiral plasmonic structures, with transformative implications for pharmaceutical screening and point-of-care diagnostics.

More recently, qBIC have attracted increasing attention in chiral detection^56,270−273. Compared with ideal BICs, qBIC modes introduce controlled radiation leakage, resulting in ultrahigh but finite quality factors that are more accessible in practical implementations. The strong field confinement and enhanced optical chirality associated with qBIC modes enable substantial amplification of chiroptical signals, offering promising opportunities for ultrasensitive chiral sensing. Nevertheless, the performance of qBIC-based platforms remains sensitive to fabrication imperfections and environmental perturbations, which poses challenges for scalable and robust applications. More recently, qBIC have attracted increasing attention in chiral detection^56,270−273. Compared with ideal BICs, qBIC modes introduce controlled radiation leakage, resulting in ultrahigh yet finite quality factors that are more accessible in practical implementations. The strong field confinement and enhanced optical chirality associated with qBIC modes enable substantial amplification of chiroptical signals, offering promising opportunities for ultrasensitive chiral sensing. For example, Chen et al. have demonstrated a BIC metasurface capable of integrated acquisition of CD spectrum and molar concentration over a single metasurface⁵⁶ with high sensitivities, as shown in Fig. 14(a). Li et al. proposed a new paradigm for ultrasensitive chiral detection by creating accessible chiral hotspots using a toroidal dipole Fabry-Perot bound state in the continuum (TD FP-BIC) metasurface²⁷⁰, achieving ultrahigh optical chirality enhancements of up to 10⁴-fold (Fig. 14(b)). The emergence of TD FP-BIC originates from destructive interference between TD resonance and the multilayer reflector-induced perfect mirror image. More intriguingly, the complex-valued Pasteur parameter, has been recently proved to induce strong coupling between two BICs in a metasurface (Fig. 14(c)), mediated by both the real²⁷¹ and imaginary²⁷³ components of the Pasteur parameter. Nevertheless, the performance of qBIC-based platforms remains sensitive to fabrication imperfections and environmental perturbations, which poses challenges for practically and robust applications.

For special particles, Huang et al. proposed passivated aluminum chiral shells via colloidal self-assembly to create ultraviolet plasmonic biosensors with uniform superchiral fields and surface lattice resonance modes²⁷⁴, as shown in Fig. 15(a). Record-breaking chiral sensor performance was demonstrated with the chiral sensor parameter reaching 10.9095 for the null point and 0.1739 for peaks of g-factor spectra, enabled by narrowed resonance linewidths. This platform also achieves zeptomole-level enantiomer discrimination, advancing label-free chiral sensing for biomedical diagnostics and pharmaceutical quality control. Manoccio et al. developed a core-shell 3D chiral metamaterial biosensor by combining platinum nanohelices with a conformal polymer coating, creating polarization-dependent optical responses that minimize background interference in complex biological environments²⁴⁶. Femtomolar sensitivity (10 fM) was demonstrated through redshifted CD spectra, achieving a 27 nm/pM sensitivity slope for TDP-43 biomarker detection in neurodegenerative diseases. This platform enables label-free, chip-based detection in human serum with unprecedented specificity, advancing point-of-care diagnostics. Upconversion nanoparticles can endow intriguing nonlinear effects. Lee et al. developed an upconverting chiral metamaterial platform that leverages nonlinear optical processes to amplify enantiomer discrimination signals²⁴⁵, as shown in Fig. 15(b). Small CD differences in near-infrared were converted into amplified visible photoluminescence contrasts via embedded core-shell upconversion nanoparticles, enabling detection of D-/L-glucose enantiomers at 0.05-M concentration. This nonlinear transduction strategy overcomes intrinsic sensitivity limitations of chiral sensing by exploiting power-dependent upconversion to resolve previously undetectable chirality signatures, advancing label-free molecular diagnostics for pharmaceuticals and biochemistry^247,275.

SERS-based chiral sensing. SERS leverages enhanced electromagnetic fields near plasmonic nanostructures to achieve extraordinary signal amplification (10⁶ to 10¹⁴ fold) and single-molecule sensitivity. This technique captures molecular fingerprints via Raman peaks, making it ideal for chiral sensing applications that demand precise discrimination of enantiomers. In the past few years, SERS have been widely utilized for chiral sensing, achieving unprecedented performance. The first demonstration to use SERS for chiral sensing was proposed by Zhang et al., who utilized the self-assembled core-satellite gold nanoparticle network. Based on the changes in the tunnelling current, this approach was able to identify the chirality of carnitine molecule with nanomolar concentration⁵². Wang et al. developed a chiral-label-free SERS strategy using vertically aligned Au nanorod arrays to synchronously discriminate and identify small aromatic enantiomers without chiral auxiliaries or circularly polarized light²⁷⁶, as shown in Fig. 16(a). This approach enables ultrasensitive chiral sensing with molecular specificity, successfully identifying >10 chiral compounds (e.g., amino acids, alcohols) and offering transformative potential for real-time analysis in pharmaceutical synthesis and asymmetric catalysis.

Fundamentally, an ideal chiral discrimination strategy is difficult to achieve due to the inevitable nonspecific binding of wrong enantiomers and the insufficient intrinsic optical activity of chiral molecules. To address this issue, Arabi et al. engineered an "Inspector Recognition Mechanism" for absolute chiral discrimination using SERS with chiral-imprinted polydopamine substrates²⁷⁷, as shown in Fig. 16(b). Specific enantiomer binding is verified by linear aminothiol inspectors, which degrade SERS tags only when imprinted cavities are vacant or non-specifically occupied, while fully occupied cavities block inspector permeation. This strategy achieves ultrahigh sensitivity (limit of detection: 10^–5–10^–4 μg·L⁻¹) along with broad enantioselectivity across diverse chiral analytes, enabling direct analysis in complex biological/environmental matrices. Leong et al. developed a generic method for chiral distinguishment using SERS²⁷⁸, as shown in Fig. 16(c). This method utilizes a label-free chiral SERS sensing strategy by synergizing nanoporous gold bowls with electrochemical modulation to generate enantiospecific molecular fingerprints. Intrinsic surface defects on gold bowls act as asymmetric recognition sites, enabling stereospecific enantiomer adsorption without chiral probes. Consequently, the direct enantiomeric differentiation is achieved, validated by unique spectral signatures and chemometrics.

SERS chiral sensing uses molecule-specific vibrational fingerprints for label-free enantiomer differentiation^279−285, offering versatile chiral sensing for pharmaceuticals and biomedicine^57,286−289. It achieves ultrahigh sensitivity through plasmonic enhancement and avoids extrinsic chiral selectors by employing engineered, intrinsically chiral nanostructures. These nanostructures create localized asymmetric environments that drive stereospecific adsorption. However, the field may intrinsically face some limitations: susceptibility to matrix interference in biological samples, challenges in scalable nanofabrication of reproducible chiral substrates, and restricted analytical throughput for multiplexed detection due to spectral complexity. Future efforts could likely be devoted to, for instance, machine learning-enabled spectral deconvolution for real-time enantiomer identification in complex matrices; miniaturized lab-on-chip systems enabling point-of-care deployment for clinical diagnostics. These efforts aim to bridge fundamental nanomaterial innovations with practical applications requiring precise chiral discrimination.

AI-assisted chiral detection. When analyzing complex multicomponent samples, subtle enantiomeric differences in optical spectra (e.g., peak shifts, intensity ratios) are often obscured by noise or matrix interference. ML provides a powerful means to extract these latent patterns, which are undetectable by conventional analysis, and has already been widely employed across various scientific disciplines^{148,290−305}. Owing to its strong target-recognition capabilities, ML can analyze spectrum signals of specific chiral molecule and even directly identify the geometric handedness of chiral particles.

Traditional approaches typically rely on imaging or spectral data of chiral molecules^306−310, employing methods such as support vector machines, fully-connected neural networks, or random forests for classification and identification. However, these methods often struggle with the high dimensionality and information-rich nature of raw data, leading to poor recognition performance when the data is insufficient. Dimensionality reduction techniques, such as principal component analysis, are commonly applied to address this issue³¹¹, yet they still require manual feature extraction and careful selection of principal components.

In contrast, deep learning leverages deep neural networks to automatically perform feature extraction³¹². Convolutional neural networks^313,314 (CNNs), as a core deep learning architecture, can process both one-dimensional spectral and two-dimensional imaging data. By applying convolutional kernels to extract image features, CNNs effectively reduce data dimensionality and are typically connected to fully-connected neural networks to perform classification. Variants such as VGG and ResNet exhibit powerful image recognition capabilities and are readily adaptable for chiral molecule recognition. For data affected by significant background noise, specialized architectures like YOLO or U-Net can be applied for object localization and image segmentation, extracting small regions containing only the target, which are then fed into classification networks for chiral molecule identification.

The use of R-CNN for chiral particle recognition represents an important milestone in automated molecular analysis. R-CNN identifies and classifies chiral structures from scanning tunnelling microscope (STM) images, however, their multi-stage pipeline limits efficiency. Faster R-CNN³¹⁵ improve upon this by unifying region proposal, feature extraction, and classification into a single network. This evolution significantly improves both inference speed and training efficiency while maintaining high recognition accuracy.

The approach used in the ref.³¹⁵ consists of the following four components: data selection, data augmentation, model training, and domain-specific expertise. The data selection module employs t-SNE to evaluate data quality and visualize molecular image distributions, facilitating the curation of high-quality training samples. The data augmentation module expands the dataset using synthetic variations of raw STM images. The model training module adopts Faster R-CNN, which performs feature extraction, molecule detection, and chiral classification in an end-to-end manner. The fourth module incorporates domain knowledge through conditional random fields to refine predictions on low-quality STM images, reducing false positives and improving overall recognition performance. Once fully trained, the pipeline automatically processes hundreds of STM images across varying resolutions, with each chiral molecule annotated by a bounding box and its corresponding chiral class.

Recently, Han et al. developed a deep-learning-enabled methodology combining neural networks with genetic algorithms to predict and inversely design the chiroptical properties of plasmonic Born-Kuhn nanodimers for target-specific chiral sensing³¹⁶, as shown in Fig. 17(a). The optimal sensor structure was algorithmically optimized by the genetic algorithm based on neural-network-predicted circular dichroism spectra, enabling ultrasensitive enantiomer discrimination without chiral probes. This approach establishes a versatile platform for designing chiral plasmonic sensors tailored to specific analytes, advancing precision in pharmaceutical and biomedical diagnostics. Using linear programming and a parameter sweep algorithm⁵⁵, Santos et al. quantified the concentration and relative proportions of all four stereoisomers in 20 samples with diverse isomeric distributions, achieving an average absolute percent error of 1.7%.

Reinforcement learning enables resource-efficient optimization by autonomously exploring parameter spaces through trial-and-error interactions with an environment, strategically prioritizing high-potential nanostructures over exhaustive simulation. Chen et al. developed a reinforcement-learning-driven workflow integrating neural networks and Bayesian optimization to inversely design chiral plasmonic metasurfaces with sharp CD peaks³⁰⁴. With this approach, fabricated microfluidic chips are capable of differentiating glucose enantiomers via 7-nm resonance shifts, as validated by cathodoluminescence spectroscopy. This method establishes a demonstrably effective framework for algorithmically evolving nanophotonic sensors, significantly advancing label-free chiral detection in biomedicine while minimizing computational costs. Notably, Zhang et al. developed a deep-learning framework with a cyclic data iteration strategy that significantly outperforms prior methods by expanding the chiral metasurface design space to 30×30-pixel freeform structures while achieving a 21-fold increase in high-CD-response (>0.6) yield³¹⁷. The methodology's efficacy was experimentally validated through terahertz biosensing, where record-high simulated/experimental CD values (≈0.7/0.6) were attained, enabling label-free differentiation of D/L-glutamic acid enantiomers with 0.08 CD resolution. This approach establishes a universal pipeline for calibration-free chiral detection, overcoming computational bottlenecks in nanophotonic design and accelerating clinical translation for disease diagnostics and drug development.

Chiral particles exhibit geometric handedness almost indistinguishable to the human eye. Machine learning can analyze microscopy images to classify this handedness. Visheratina et al. developed a deep learning framework combining Siamese learning and synthetic data generation to identify chirality in scanning electron microscope (SEM) images with minimal training data³¹⁸, as shown in Fig. 17(b). Using only 30 original images, it achieved near-perfect (99%) accuracy for detecting chiral bowtie particles and distinguishing their handedness. The model generalized effectively, reaching 93% accuracy on unseen chiral geometries without retraining. This approach enables high-throughput, automated chirality analysis of nanostructured materials, overcoming traditional EM limitations and accelerating discovery for photonic and biomedical applications. Later, Huang et al. developed an automated deep learning framework using Grounding DINO, Segment Anything, and ResNet to achieve 99% accuracy in chiral nanoparticle segmentation and handedness classification from SEM images, requiring zero manual annotations³¹⁹, as shown in Fig. 17(c). By leveraging Grounding DINO and Segment Anything for automated detection and segmentation, this approach eliminated manual annotation entirely and reduced data requirements by 33% compared to prior methods, achieving high accuracy with only 20 raw SEM images versus over 30 labelled images. Crucially, synthetic data augmentation enabled robust handling of overlapping particles, resolving a key limitation in earlier segmentation models while maintaining greater than 95% accuracy across resolutions for high-throughput screening.

Overall, optical chiral detection has evolved from conventional far-field spectroscopic techniques toward nanophotonic-enhanced and data-driven sensing paradigms. Traditional chiroptical methods provide a solid physical foundation for enantiomer identification, while nanophotonic platforms, such as plasmonic structures, dielectric metasurfaces, and BIC resonators, enable strong field confinement and enhanced optical chirality, significantly amplifying weak chiroptical signals. These advances have greatly improved detection sensitivity, yet they also introduce new challenges, including fabrication sensitivity, environmental perturbations, stringent experimental conditions, and the increasing complexity and dimensionality of experimental data.

In this context, deep-learning-based approaches have begun to play a substantive role in chiral molecule detection by enabling the identification of weak and complex chiroptical signatures that are difficult to resolve using conventional analytical models. In particular, neural networks have shown promise in enhancing detection sensitivity, improving classification robustness, and accelerating the interpretation of high-dimensional spectral data in chiral sensing platforms. However, the application of deep learning in chiral molecule detection faces several major challenges, with the most significant being the scarcity of high-quality and accurately labelled datasets. Chiral identification requires expert annotation and experimental validation, which are both time-consuming and costly. As a result, available datasets are often limited in size. When trained on such small-scale data, deep neural networks are prone to overfitting, leading to strong performance on training data but poor generalization to new samples. Additionally, structural variability and noise in real-world data further complicate model training and reliability.

Future developments in AI-assisted chiral detection will likely focus on four key directions. (1) Generative models, including generative adversarial networks and diffusion models, offer a promising route to augment chiral spectral and light-matter interaction datasets, thereby alleviating data scarcity and improving model robustness in low-sample regimes. (2) Self-supervised, semi-supervised, and few-shot learning strategies are particularly well suited for chiral detection tasks, where labelled enantiomeric data are scarce and costly to obtain. (3) The incorporation of domain knowledge and physics-inspired constraints, such as symmetry considerations and chiroptical response models, into network architectures can improve training efficiency while enhancing physical interpretability and generalization across different chiral systems. (4) Multimodal learning frameworks that integrate spectral, structural, and chemical descriptors are expected to further improve the robustness and interpretability of chiral recognition systems, especially for complex or weakly chiral molecular targets.

4　Conclusions

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Over the past decade, optical sorting and detection of chiral molecules have undergone rapid progress, driven by advances in structured light fields, nanophotonic devices, and integrated systems. Detailed comparisons of representative methods, including their key performance metrics and application scenarios, are summarized in Tables 1−3. Nevertheless, this field remains at a formative stage, with substantial room for improvement and several significant challenges to be addressed, as schematically illustrated in Fig. 18.

For optical sorting, research has evolved from early demonstrations based on ORP, OGF, OLF and OPF to more sophisticated platforms such as metasurfaces, waveguides, BICs and EPs. While these approaches are steadily advancing enantioselective manipulation toward higher precision, speed, versatility, and biocompatibility, practical deployment remains constrained by several fundamental and technical challenges, most notably low throughput and insufficient system stability. More specifically, low throughput in optical chiral sorting fundamentally arises from the intrinsic trade-off between optical force magnitude and interaction range. High-Q near-field platforms, such as BICs and EPs based nanophotonic structures can generate strongly enhanced optical forces, but their effective working distance is typically confined to subwavelength scales. In contrast, far-field optical forces offer larger interaction ranges but are generally too weak for efficient enantioselective manipulation. Strategies that enhance near-field force efficiency while extending the effective interaction region seems feasible, but they require further development and deeper exploitation of resonant mechanisms such as BICs and EPs. In addition, optical force-based sorting places stringent demands on system stability. Optical heating, thermal diffusion, and background noise can readily degrading performance. Integrating optical manipulation with advanced microfluidic platforms^320−323 offers a promising route to improved stability and environmental control, although challenges related to flow regulation, interface engineering³²⁴, co-design of microfluidic and nanophotonics, and long-term stability under realistic operating conditions remain to be addressed. From a commercialization perspective, additional constraints must be considered. At the microscale, optical sorting offers limited advantages compared with mature techniques such as flow cytometry and acoustic sorting. At the nanoscale, practical deployment is hindered by low sorting throughput, the high fabrication cost of large-area near-field structures, limited chip reusability, and insufficient long-term operational stability. Addressing these challenges will be essential for translating optical chiral sorting from proof-of-concept demonstrations toward practical applications.

For chiral detection, techniques including superchiral fields, plasmonic and dielectric metasurfaces, VCD, and SERS have substantially boosted sensitivity, in some cases enabling detection down to the single-molecule and zeptomole levels. However, similar to optical sorting, these approaches are fundamentally constrained by intrinsic physical trade-offs between near-field enhancement, effective interaction range, and measurement robustness. While strong near-field confinement enables extreme sensitivity, it often comes at the cost of limited probing volume, stringent fabrication tolerances, and increased susceptibility to environmental perturbations. In addition, chiral optical detection generally lacks intrinsic molecular specificity, which poses further challenges for identifying target chiral species in complex real-world environments, such as serum or urine, where multiple chiral and achiral components coexist. Addressing this issue typically requires complementary strategies, including surface functionalization or AI-assisted multispectral analysis. Beyond physical limitations, practical translation is further impeded by engineering and standardization challenges. In particular, device-to-device reproducibility, large scale nanofabrication, long-term measurement stability, and the absence of unified calibration and benchmarking protocols remain major barriers to industrial adoption. From a commercialization perspective, future progress will rely not only on further sensitivity enhancement, but also on the development of scalable, cost-effective, and reproducible nanophotonic platforms with standardized performance metrics. In this context, point-of-care testing³²⁵ and lab-on-chip³²⁶ integration offer promising pathways toward compact and automated detection, while hybrid multimodal strategies that couple optical, electrochemical³²⁷, and mass-sensitive detection may improve robustness and accelerate the transition from laboratory demonstrations to application-ready chiral sensing systems.

Besides, artificial intelligence is emerging as a valuable complement to these advances, providing tools for extracting hidden spectral features, classifying molecular handedness, and enabling inverse design of photonic structures. Emerging frontiers now focus on enhancing autonomy, accessibility, and interpretability. Self-supervised learning alleviates the dependence on labelled datasets for identification of novel particles; edge computing integrates lightweight models like MobileNet into portable devices for real-time monitoring of environmental pollutants; and explainable AI methods like SHAP values provide interpretability, revealing how features contribute to classification outcomes and thereby building user trust. These advancements collectively position machine learning not merely as analytical tools but as discovery catalysts—bridging raw data complexity with scientific insight across materials science, environmental monitoring, and biomedical diagnostics. The combination of AI-driven analysis with engineered optical fields offers a promising pathway to achieve robust, high-throughput, and autonomous chiral sorting and sensing.

In summary, the convergence of photonic nanostructures, microfluidic integration, and intelligent data processing is expected to accelerate the transition from proof-of-concept demonstrations toward real-world applications. Such advances will be particularly impactful in pharmaceutical manufacturing, clinical diagnostics, and enantioselective catalysis, where precise control and reliable identification of chirality remain indispensable.

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Year 2026 volume 9 Issue 6

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doi: 10.29026/oea.2026.250255

Receive Date：2025-09-23
Online Date：2026-10-19
Published：2026-06-08

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Received：2025-09-23
Accepted：2026-01-20

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