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The Bauschinger effect is a classical phenomenon in which metallic materials exhibit a significant reduction in yield stress upon reverse loading after preloading. This review systematically summarizes research advances over the past two decades in microscopic physical mechanisms， responses of advanced materials， constitutive modeling， and engineering control strategies related to the Bauschinger effect. At the microscopic scale， multiscale experimental characterizations have revealed the asymmetric evolution of defect structures （e.g.， dislocation dipoles， dislocation cells， and twin boundaries） under cyclic loading， with such behavior observed in both high stacking-fault-energy metals （such as Al and its alloys， Fe） and low stacking-fault-energy metals （such as brass and austenitic stainless steels）， establishing a quantitative correlation between macroscopic back stress and microscopic defect structures. At the mesoscopic scale， cross-scale coupling of discrete dislocation dynamics and crystal plasticity finite element methods has elucidated the non-local characteristics of back stress and the nature of its heterogeneous intergranular distribution. This review discusses the Bauschinger effect in conventional metals such as aluminum alloys and steel， and focuses on the unique Bauschinger effect behaviors arising from multi-mechanism synergy in high-entropy alloys， magnesium alloys， nanostructured metals， and shape memory alloys. On this basis， the evolution of back stress models from empirical formulas to dislocation-density-based physically-based constitutive models is reviewed， along with constitutive modeling approaches that account for microstructural heterogeneity within the crystal plasticity framework. Furthermore， application strategies of the Bauschinger effect in material forming， fatigue evaluation， and performance-oriented design are summarized， reflecting a shift from passive avoidance to active utilization. Finally， future directions are discussed， including extreme environmental effects， high-throughput effect mapping， multi-physics field coupling， and cross-scale integrated computational platforms.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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