Article(id=1149781956734444450, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149781952959574654, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2403842, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1716393600000, receivedDateStr=2024-05-23, revisedDate=1735142400000, revisedDateStr=2024-12-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1752058980400, onlineDateStr=2025-07-09, pubDate=1743091200000, pubDateStr=2025-03-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752058980400, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752058980400, creator=13701087609, updateTime=1752058980400, updator=13701087609, issue=Issue{id=1149781952959574654, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='9', pageStart='3529', pageEnd='3967', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752058979501, creator=13701087609, updateTime=1776333392421, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1251596220226027613, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149781952959574654, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1251596220226027614, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149781952959574654, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3613, endPage=3619, ext={EN=ArticleExt(id=1149781957032240035, articleId=1149781956734444450, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Curing Kinetics in the Manufacture of Composite Tensile Armor Layers, columnId=1156264150696317860, journalTitle=Science Technology and Engineering, columnName=Papers·General Industrial Technology, runingTitle=null, highlight=null, articleAbstract=

Considering the high-temperature thermosetting chemical issues in the manufacturing process of composite tensile armor layers, the curing kinetics of T700/epoxy prepregs were explored. Through differential scanning calorimetry (DSC) analysis and the Starink method, the autocatalytic reaction curing kinetic parameters were accurately calculated. Then a curing kinetic model was established. It has been shown by experimental results that the reaction rate of the prepreg is significantly increased at higher heating rates. After the peak is reached, the reaction rate is decreased more rapidly, resulting in a lower average final reaction heat. The apparent activation energy of the curing reaction for this prepreg is 77.04 kJ/mol, and high consistency with the experimental data is exhibited by the constructed curing kinetic model.

, correspAuthors=Jun-peng LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Rui BAO, Jun-peng LIU, Meng-lan DUAN), CN=ArticleExt(id=1149781997876371623, articleId=1149781956734444450, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=复合抗拉铠装层制备中的固化动力学, columnId=1156264150843118502, journalTitle=科学技术与工程, columnName=论文·一般工业技术, runingTitle=null, highlight=null, articleAbstract=

为研究复合抗拉铠装层制造成型过程中的高温热固化化学问题,探讨了T700碳纤维增强环氧树脂预浸料的固化动力学特性,通过对预浸料进行差示扫描量热(differential scanning calorimetry,DSC)分析,利用Starink法精确计算了自催化反应固化动力学参数,建立了固化动力学模型。试验结果表明:在更高的加热速率下,预浸料坯的反应速率显著增加,但达到峰值后反应速率下降更快,导致最终反应热的平均值更低。该预浸料的固化反应表观活化能为77.04 kJ/mol,所构建的固化动力学模型与试验数据高度匹配。

, correspAuthors=刘军鹏, authorNote=null, correspAuthorsNote=
* 刘军鹏(1986—),男,汉族,山东烟台人,博士,教授。研究方向:海洋结构力学、失效分析等。E-mail:
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鲍蕊(1994—),女,汉族,河北衡水人,博士研究生。研究方向:海洋软管复合抗拉铠装层材料力学。E-mail:

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鲍蕊(1994—),女,汉族,河北衡水人,博士研究生。研究方向:海洋软管复合抗拉铠装层材料力学。E-mail:

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鲍蕊(1994—),女,汉族,河北衡水人,博士研究生。研究方向:海洋软管复合抗拉铠装层材料力学。E-mail:

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Thermodynamic parameters of composite materials with different heating rates

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β/(℃·min-1) Ti/℃ Tp/℃ Tf/℃ ΔHo/(J·g-1)
5 114.23 147.18 180.13 132.72
10 121.94 155.86 202.41 126.14
15 123.53 163.30 221.71 126.10
20 131.25 169.27 224.65 126.19
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不同加热速度复合材料的热力学参数

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β/(℃·min-1) Ti/℃ Tp/℃ Tf/℃ ΔHo/(J·g-1)
5 114.23 147.18 180.13 132.72
10 121.94 155.86 202.41 126.14
15 123.53 163.30 221.71 126.10
20 131.25 169.27 224.65 126.19
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Autocatalytic model curing kinetics parameters

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β/(℃·min-1) lnA/min-1 m n
5 23.26 0.55 1.28
10 23.96 0.5 1.41
15 24.23 0.4 1.21
20 24.39 0.39 1.43
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自催化模型固化动力学参数

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β/(℃·min-1) lnA/min-1 m n
5 23.26 0.55 1.28
10 23.96 0.5 1.41
15 24.23 0.4 1.21
20 24.39 0.39 1.43
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复合抗拉铠装层制备中的固化动力学
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鲍蕊 1 , 刘军鹏 1, * , 段梦兰 2
科学技术与工程 | 论文·一般工业技术 2025,25(9): 3613-3619
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科学技术与工程 | 论文·一般工业技术 2025, 25(9): 3613-3619
复合抗拉铠装层制备中的固化动力学
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鲍蕊1 , 刘军鹏1, * , 段梦兰2
作者信息
  • 1 中国石油大学(北京)安全与海洋工程学院, 北京 102249
  • 2 清华大学深圳国际研究生院海洋工程研究院, 深圳 518055
  • 鲍蕊(1994—),女,汉族,河北衡水人,博士研究生。研究方向:海洋软管复合抗拉铠装层材料力学。E-mail:

通讯作者:

* 刘军鹏(1986—),男,汉族,山东烟台人,博士,教授。研究方向:海洋结构力学、失效分析等。E-mail:
Curing Kinetics in the Manufacture of Composite Tensile Armor Layers
Rui BAO1 , Jun-peng LIU1, * , Meng-lan DUAN2
Affiliations
  • 1 College of Safety and Ocean Engineering, China University of Petroleum, Beijing 102249, China
  • 2 Institute for Ocean Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
出版时间: 2025-03-28 doi: 10.12404/j.issn.1671-1815.2403842
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为研究复合抗拉铠装层制造成型过程中的高温热固化化学问题,探讨了T700碳纤维增强环氧树脂预浸料的固化动力学特性,通过对预浸料进行差示扫描量热(differential scanning calorimetry,DSC)分析,利用Starink法精确计算了自催化反应固化动力学参数,建立了固化动力学模型。试验结果表明:在更高的加热速率下,预浸料坯的反应速率显著增加,但达到峰值后反应速率下降更快,导致最终反应热的平均值更低。该预浸料的固化反应表观活化能为77.04 kJ/mol,所构建的固化动力学模型与试验数据高度匹配。

碳纤维/环氧树脂  /  预浸料  /  固化动力学  /  DSC分析

Considering the high-temperature thermosetting chemical issues in the manufacturing process of composite tensile armor layers, the curing kinetics of T700/epoxy prepregs were explored. Through differential scanning calorimetry (DSC) analysis and the Starink method, the autocatalytic reaction curing kinetic parameters were accurately calculated. Then a curing kinetic model was established. It has been shown by experimental results that the reaction rate of the prepreg is significantly increased at higher heating rates. After the peak is reached, the reaction rate is decreased more rapidly, resulting in a lower average final reaction heat. The apparent activation energy of the curing reaction for this prepreg is 77.04 kJ/mol, and high consistency with the experimental data is exhibited by the constructed curing kinetic model.

carbon fiber/epoxy resin  /  prepreg  /  curing kinetics  /  DSC analysis
鲍蕊, 刘军鹏, 段梦兰. 复合抗拉铠装层制备中的固化动力学. 科学技术与工程, 2025 , 25 (9) : 3613 -3619 . DOI: 10.12404/j.issn.1671-1815.2403842
Rui BAO, Jun-peng LIU, Meng-lan DUAN. Curing Kinetics in the Manufacture of Composite Tensile Armor Layers[J]. Science Technology and Engineering, 2025 , 25 (9) : 3613 -3619 . DOI: 10.12404/j.issn.1671-1815.2403842
非黏结柔性立管是海洋油气开采中的重要管道系统,将海上平台和水下系统进行连接运输,由多种材料制成,具有很高的柔韧性和耐腐蚀性,是海洋油气开采的关键结构。随着油气资源开发向更深海域的拓展,对于更长、更大直径的非黏结柔性立管的需求日益增加,但立管重量的增加以及内外介质的腐蚀作用对其应用带来了限制。目前科研学者及生产公司将复合材料制成抗拉铠装层,取代碳钢材料,不仅开辟了新的研究方向,也展现了巨大的发展潜力[1-3]。复合材料由于其重量、抗腐蚀性的优势,既能保障结构强度的可靠性,又能大幅度降低柔性立管的整体重量,从而在确保结构强度的同时,推进深水油气开采技术的发展。
纤维增强材料具有较高的强度重量比,在具有等效结构承载力时,结构更轻。Nammi等[4]分析了复合材料柔性立管,指出通过适当的设计,可在保持力学性能不变的情况下显著减轻重量,进而减少海上平台的承载负担。Zhang等[5]研究了纤维增强复合材料中的微固化残余应力演化,并分析了残余应力的力学行为影响因素,提出了一种优化设计策略。随着碳纤维增强聚合物(carbon fiber reinforced polymer,CFRP)或复合装甲在替代非黏结软管的金属压缩和拉伸铠装层方面的应用日益广泛,Technip公司开发的具有四层碳纤维铠装层的非黏结柔性管道,为轻型柔性立管提供了新方案,这种设计可以在超深水作业中减少甚至消除对浮力筒的需求。在复合材料抗拉铠装层的制备过程中,热压罐成型技术是目前制作复合材料制件的关键技术之一。在热压罐内,树脂经历从液态到橡胶态,最终转变为玻璃态的复杂化学反应和能量交换过程,直至固化成型[6]。在复合材料的固化过程,由此带来的热量会对材料的温度及固化度梯度产生影响,其中的固化不均匀性会使结构出现固化变形,且其中的流变耦合也将对复合材料的尺寸精度和强度性能带来干扰[7-9]
目前对环氧树脂体系的研究已经成为研究的热点,很多学者通过差示扫描量热(differential scanning calorimetry,DSC)和动态热机械分析(dynamic mechanical analysis,DMA)的缩写,即等试验技术对其展开了深入研究,开发了多种方法用于探究其固化动力学[12-13]。区别于其他技术,DSC能够执行等温与非等温扫描,这为后续通过固化动力学模型分析反应速率与固化程度提供了便利。Hassanpour等[10]研究了固化碳纤维/环氧树脂复合材料的湿气吸收和玻璃化转变温度动力学。通过实验测量了复合材料在不同湿度条件下的湿气吸收率,并分析了湿气对材料玻璃化转变温度的影响。李元昊等[11]通过DSC等手段,对新型环氧树脂体系的固化反应进行了详细的动力学分析,并评估了其在碳纤维复合材料中的力学性能和热性能。张成林等[12]和高腾龙等[13]分析了预浸料在不同加热速率下的固化过程,计算了固化反应的动力学参数,并基于实验数据,建立了固化动力学模型,并通过模型验证了其准确性和可靠性。张雨晴等[14]利用非等温DSC分析方法,确定了合成TSPZ-EP环氧树脂的高温固化行为,并通过外推法确定固化工艺,测试其力学性能。郑波等[15]根据动态DSC试验及流变仪数据,利用N级分段模型,并优化了工艺条件以提高材料强度。宦佳琪等[16]在此基础上结合傅里叶红外光谱确定了固化反应机理,采用Kissinger方程、Ozawa方程及Crane分别获取固化动力学参数,得出固化机理为羚酸离子在咪哗离子的存在下先与环氧发生加成反应,反应释放出咪哗分子再与环氧进行催化开环。杨旭锋[17]通过结合T700/PPS体系的固化机理,开展了单向板热压成型试验,检测到残余变形。基于热-结晶-力学多物理场耦合分析模型,预测了T700/PPS复合材料管道成型残余应力。Liang等[18]研究了固化温度对碳纤维复合材料力学性能的影响,并探讨了其在纤维缠绕压力容器中的应用。通过一系列实验,分析了在不同固化温度条件下,碳纤维复合材料的拉伸强度、弯曲强度和冲击韧性等力学性能的变化。这些研究成果表明,通过掌握固化速率、温度和时间等输入参数,可以准确预测并控制复合材料成型过程中的固化变形。
为后续深入了解固化中的残余应力问题,需要探讨热固化工艺及复合材料制备过程中的动力学特性,现首先对T700/环氧树脂单向预浸料进行动态DSC试验,旨在研究其固化行为。为了模拟固化动力学过程,比较N级反应动力学模型和自催化模型对材料进行建模。通过对比分析,得出自催化模型能够更加准确地反映出碳纤维/环氧树脂材料的固化反应过程。通过DSC数据的进一步分析,解释加热速率与固化反应过程之间的相互关系。将自催化模型的预测结果与实验数据进行比对,验证该模型的高度准确性。这不仅有助于深化固化过程的理解,而且在确定动力学参数方面发挥关键作用。基于这些研究成果,能够为环氧树脂预浸料在海洋结构应用中的固化工艺提供优化建议,进而提升材料的应用性能。
柔性立管的具体结构如图1所示,其中抗拉铠装层为复合材料。为分析复合抗拉铠装层制造过程中的残余应力问题,选用T700/环氧树脂单向预浸料体系材料对固化动力学进行研究。其中预浸料的厚度约为0.15 mm,树脂含量为35%,面积密度为150 g/m2。采用TA仪器的DSCQ200设备测量固化过程中环氧预浸料坯的放热热流,图2为具体试验设备,样品重量为18 mg,将其放入坩埚中进行试验。
将样品从冰箱中取出后,先置于室温25 ℃下使其回温。随后取少量样品置入封闭的铝制坩埚中进行热量测量。实验中,采用流速为20~30 mL/min的氮气作保护气体,同时利用液氮制冷技术以尽可能减少在测量过程中样品的氧化现象。随后,采用不同的加热速率对材料进行动态试验。预浸料体系在接近玻璃化温度时会发生相态变化,这会导致材料微观结构中分子运动能力增强,从而比热发生显著变化。
在不同升温速率β下进行的试验中,准确地测定了起始温度Ti(℃)、放热峰值温度Tp(℃)以及终止温度Tf(℃),其对应的相关数据如表1所示。在图3的非等温DSC曲线中,这3个关键温度点分别位于材料放热峰的开始、峰值和结束位置。在各种升温速率条件下,复合材料都展现了明显的单一放热峰。在较低升温速率下,放热过程较为平缓,说明复合材料体系需要一定时间来完成固化反应。在加热速度不断提高的情况下,相同时间内环氧树脂体系的热效应呈现递增趋势,使得放流热惯性以及温度梯度差增大。同时该反应的热流峰所对应的温度点逐渐增大,峰值出现明显的升高情况。
采用Starink法求解表观活化能,进而预测反应速率,理解热固化反应机制。通过式(1)左右两侧,观察到线性函数,其中表观活化能直接影响反应速率,拟合得到表观活化能Eα,进而获得截距常数Cs
ln$\left(\frac{{\beta }_{i}}{{T}_{\alpha,i}^{1.92}}\right)$=Cs-1.000 8$\left(\frac{{E}_{\alpha }}{R{T}_{\alpha }}\right)$
式(1)中:Tα,i为不同升温速率β下,转换率为α时的对应温度;理想气体常数R为8.314 J/(mol·K)。
图4为ln(β/${T}_{\alpha }^{1.92}$)和1/Tα的关系图,两者呈现很好的线性关系。根据不同固化程度下的直线斜率及截距,取平均值计算得到活化能Eα为77.04 kJ/mol,其误差分布如图5所示。随着固化度的提升,Eα总体呈现下降趋势。这表明,在固化初期,材料固化需要更高的活化能来推动化学反应。随着固化程度的深入,所需的活化能逐渐降低,从初始的约85 kJ/mol降低到约65 kJ/mol。这种变化反映出,在固化初期,由于反应物相对自由度高,需要更多能量来启动反应。而随着网络结构的逐步建立,分子之间的距离缩短,使得化学反应更加容易进行,进而活化能的要求降低。这一趋势的理解对于调控复合材料的固化工艺至关重要,有助于优化生产流程,提高材料性能。
采用T-β外推法来选择固化工艺的温度属性,该方法将预浸料在不同加热速率β下的DSC数据,采用线性拟合方法Arrhenius方程对温度进行外推至β=0 ℃/min,获得TiTpTf,得到3种理论外推温度:凝胶温度、固化温度及后处理温度。图6为T700/epoxy体系固化温度外推曲线,分别拟合得到TiTpTf的对应系数为0.92、0.99和0.88,证明所选用的线性拟合模型能够准确描述预浸料的热反应过程。理论外推固化温度TiTpTf分别为109.58、140.48和169.01 ℃。基于此,预浸料可从110 ℃开始加热,将温度加热到140 ℃,随后再增温至170 ℃,采用特定的加热速度及保温时间,使材料完成后处理,确保树脂充分反应并彻底固化。
在固化过程中,树脂经历一系列相变,包括聚合反应产生的放热。经过热流曲线测量总反应热,固化度计算公式为
α=$\frac{S}{{S}_{\mathrm{T}}}$=$\frac{{\int }_{0}^{t}(\mathrm{d}Q/\mathrm{d}t)\mathrm{d}t}{{\int }_{0}^{{t}_{\mathrm{f}}}(\mathrm{d}Q/\mathrm{d}t)\mathrm{d}t}$
通过使用不同的动力学模型,可以从DSC数据中获得表示固化速率的经验模型。N阶动力学模型假设在整个固化过程中只发生一级反应,速率方程可以表示为
$\frac{\mathrm{d}\alpha }{\mathrm{d}t}$=A${\mathrm{e}}^{\frac{-{E}_{\alpha }}{RT}}$(1-α)n
式(3)中:A为指数前因子;n为固化动力学的反应级数。取ln$\left(\frac{\mathrm{d}\alpha }{\mathrm{d}t}\right)$+$\frac{{E}_{\alpha }}{RT}$和ln(1-α)作图,对数据进行线性拟合,得到反应级数。在0.05~0.9的固化度范围内研究固化动力学,以此获得合适的固化参数。采用N阶动力学模型获得的曲线关系如图7所示,观察到当固化度小于0.7时呈现线性关系,当固化度大于0.7时,呈明显的非线性。这种现象说明,当固化度高于0.7时,N阶动力学模型与式(3)不相符,从而证明N阶模型不能准确描述该材料的固化反应过程。因此,需要探索其他模型以更准确地描述材料的固化动力学行为。
自催化模型通过考虑两个反应顺序来精确地交联聚合物链,固化反应在初始阶段反应速率较低,存在诱导期,反应充分特定时间,才会呈现大幅上升趋势最终达到最高点。环氧树脂体系的自催化模型的表达式为
$\frac{\mathrm{d}\alpha }{\mathrm{d}t}$=A${\mathrm{e}}^{\frac{-{E}_{\alpha }}{RT}}$αm(1-α)n
式(4)中:mn均为固化动力学的反应级数,通过在式(4)的两侧取自然对数,得
ln$\left(\frac{\mathrm{d}\alpha }{\mathrm{d}t}\right)$=lnA+mlnα+nln(1-α)-$\frac{{E}_{\alpha }}{RT}$
从DSC测量数据中获得固化度曲线如图8所示。可以看出,随着升温速率的提高,达到同一固化程度所需的温度也随之升高。当固化程度为0.5时,5 ℃/min的升温速率对应的温度明显低于20 ℃/min的升温速率。在低固化程度区域,升温速率对固化温度的影响更为显著,反映了升温速率对固化起始阶段的影响。固化度与温度存在“S”形,随着温度升高,固化度逐渐增加,且随着加热速率的增加,所需要的反应温度提高,该反应与自催化反应特征非常相符[18]。对模型中的其他参数进行非线性拟合,固化动力学参数如表2所示。随着升温速率的增加,指前因子A不断增加,相比之下,反应级数m呈现轻微递减,n变化较小,变化趋势不明显。
采用不同加热速率,对自催化模型下的预浸料体系固化曲线进行试验比较,结果如图9所示。可以看出,在固化反应的前期和相关加热速率下能实现较好地匹配。自催化模型在计算反应速率时考虑了树脂和反应产物浓度,并能准确预测该预浸料体系的固化反应过程。同时结合图8,可以看到一致性:固化度曲线上升的温度区间与反应速率曲线的峰值温度相符。且随着温度的继续升高,固化程度趋于饱和(接近1),对应的反应速率曲线开始下降,反映了反应逐渐完成。在低温区固化进度缓慢,相对应的反应速率曲线的峰出现在更高的温度范围内。
玻璃化转变温度是表征环氧树脂相变信息的重要参数。通过DSC数据进行拟合,测量热固化度相关下的玻璃化转变温度。通过式(6)计算固化样品的固化度,并通过试验测得的热流曲线变化计算玻璃化转变温度。利用Pascault-Williams方程可获得玻璃化转变温度的最佳拟合经验模型。
Tg=Tg0+$\frac{({T}_{\mathrm{g}\infty }-{T}_{\mathrm{g}0}){\lambda }_{\mathrm{g}}\alpha }{1-(1-{\lambda }_{\mathrm{g}})\alpha }$
式(6)中:Tg0Tg∞分别为未固化和完全固化样品的玻璃化转变温度;λg为通过迭代过程获得的拟合参数。对于当前T700/环氧树脂,Tg0Tg∞分别为134.51 ℃和175.79 ℃,λg=0.364。图10展示了测得的玻璃化转变温度与相关模型的比较结果。
用DMA对特定固化周期完全固化的样品进行测量。为了测量不同频率下样品的弹性模量随温度的变化,通过升温和5 min恒温来进行拉伸试验,以确保热平衡。图11(a)显示了固化后的储能模量和损耗模量。图11(b)显示了损耗因子tanδ随温度的变化。随着温度的升高,树脂从液体凝胶化转变为固体凝胶化,固化树脂的储能模量在125 ℃左右下降,在170 ℃左右趋于稳定。在180 ℃的温度下,树脂完全固化,模量达到稳定。损耗因子在低温较弱且处于恒定状态(材料处于玻璃态),高温下迅速升高(材料变得黏弹性)。损失因子的整个峰值将在接近固化树脂的玻璃化转变时获得,在玻璃化之前,随着频率的增加,测得的储能模量差异更大。从实验结果中观察到,储能模量的差异为8 GPa,损耗模量为0.6 GPa。树脂玻璃化后,不同频率下的储能模量和耗能模量之差分别为5 GPa和0.3 GPa。
针对T700/环氧树脂预浸料体系,通过DSC测试,采用Starink方程搭建了预浸料体系固化动力学模型,通过线性拟合及自催化模型求得表观活化能和反应级数。得到以下结论。
(1)非等温固化的最大反应热可以在220 ℃ 以下实现。随着升温速率增加,固化度-温度曲线向高温移动,表明预浸料达到相同固化程度所需的温度不断升高。
(2)采用T-β外推法,拟合了T700/环氧树脂体系的凝胶温度为109.58 ℃,固化温度140.48 ℃以及后处理温度169.01 ℃。随着温度的升高,树脂从液体凝胶化转变为固体凝胶化。储能模量在125 ℃左右下降,在170 ℃左右趋于稳定,在180 ℃的温度下,树脂完全固化,模量达到稳定。
(3)在玻璃化之前,储能模量在不同频率下的差异为8 GPa,损耗模量的差异为0.6 GPa。树脂玻璃化后,不同频率下的储能模量和耗能模量之差分别为5 GPa和0.3 GPa。损耗因子在玻璃态时变化较小,在接近固化树脂的玻璃化转变时获得峰值。
  • 国家自然科学基金(52171286)
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2025年第25卷第9期
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doi: 10.12404/j.issn.1671-1815.2403842
  • 接收时间:2024-05-23
  • 首发时间:2025-07-09
  • 出版时间:2025-03-28
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  • 收稿日期:2024-05-23
  • 修回日期:2024-12-26
基金
国家自然科学基金(52171286)
作者信息
    1 中国石油大学(北京)安全与海洋工程学院, 北京 102249
    2 清华大学深圳国际研究生院海洋工程研究院, 深圳 518055

通讯作者:

* 刘军鹏(1986—),男,汉族,山东烟台人,博士,教授。研究方向:海洋结构力学、失效分析等。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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