Article(id=1169295842235134036, tenantId=1146029695717560320, journalId=1146120122248306696, issueId=1169295841580819245, articleNumber=1009-2617(2025)03-0309-07, orderNo=null, doi=10.13355/j.cnki.sfyj.2025.03.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736265600000, receivedDateStr=2025-01-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1756711453254, onlineDateStr=2025-09-01, pubDate=1750348800000, pubDateStr=2025-06-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1756711453254, onlineIssueDateStr=2025-09-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1756711453254, creator=13701087609, updateTime=1756711453254, updator=13701087609, issue=Issue{id=1169295841580819245, tenantId=1146029695717560320, journalId=1146120122248306696, year='2025', volume='44', issue='3', pageStart='283', pageEnd='431', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1756711453097, creator=13701087609, updateTime=1756711962360, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1169297977647571041, tenantId=1146029695717560320, journalId=1146120122248306696, issueId=1169295841580819245, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1169297977647571042, tenantId=1146029695717560320, journalId=1146120122248306696, issueId=1169295841580819245, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=309, endPage=315, ext={EN=ArticleExt(id=1169295842885251161, articleId=1169295842235134036, tenantId=1146029695717560320, journalId=1146120122248306696, language=EN, title=Leaching Mechanism of Cobalt and Lithium from Waste Lithium Cobaltate Batteries by L-Malic Acid/Ascorbic Acid, columnId=1152626641181700664, journalTitle=Hydrometallurgy of China, columnName=Experiment Research, runingTitle=null, highlight=null, articleAbstract=

The recycling of lithium cobaltate from waste lithium-ion batteries is of great significance for alleviating resource shortage and reducing environmental pollution. L-malic acid/ascorbic acid system was used as leaching agent to recover cobalt and lithium from waste lithium cobaltate batteries. The effects of L-malic acid concentration, ascorbic acid concentration, liquid volume to solid mass ratio, reaction temperature and time on the leaching rates of cobalt and lithium in lithium cobaltate were investigated. The leaching mechanism was discussed through kinetic analysis and SEM characterization. The results show that the optimal leaching conditions are L-malic acid concentration of 0.2 mol/L, ascorbic acid concentration of 0.1 mol/L, liquid volume to solid mass ratio of 0.3 mL/1 mg, reaction temperature of 70 ℃, leaching time of 1 h. Under the conditions, the leaching rates of cobalt and lithium are above 98%. The kinetic analysis shows that the leaching process is mainly controlled by external diffusion. The method is efficient and environmentally friendly, and can provide an important technical reference for the green recovery of lithium cobaltate in waste lithium-ion batteries.

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废旧锂离子电池中钴酸锂的资源化回收对于缓解资源短缺和减少环境污染具有重要意义。研究了以L-苹果酸/抗坏血酸体系为浸出剂,从废旧钴酸锂电池中回收钴与锂,考察了L-苹果酸和抗坏血酸浓度、液固体积质量比、浸出温度和时间对钴、锂浸出率的影响,并通过动力学分析和SEM表征探讨了浸出机制。结果表明:最佳浸出条件为L-苹果酸浓度0.2 mol/L,抗坏血酸浓度0.1 mol/L,液固体积质量比0.3 mL/1 mg,浸出温度70 ℃,浸出时间1 h,在该条件下,钴和锂浸出率均达98%以上;浸出过程主要受外部扩散控制。该法高效、环保,可为废旧锂离子电池中钴酸锂的绿色回收提供技术参考。

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陈燕萌(1986—),女,硕士,副教授,主要研究方向为湿法冶金。E-mail:
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杨鹏飞(1993—),男,硕士,讲师,主要研究方向为湿法冶金。

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杨鹏飞(1993—),男,硕士,讲师,主要研究方向为湿法冶金。

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杨鹏飞(1993—),男,硕士,讲师,主要研究方向为湿法冶金。

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L-苹果酸/抗坏血酸对废旧钴酸锂电池中钴与锂元素浸出机制研究
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杨鹏飞 , 蓝樊盛 , 蓝峻峰 , 叶有明 , 谢雪珍 , 陈燕萌
湿法冶金 | 试验研究 2025,44(3): 309-315
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湿法冶金 | 试验研究 2025, 44(3): 309-315
L-苹果酸/抗坏血酸对废旧钴酸锂电池中钴与锂元素浸出机制研究
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杨鹏飞, 蓝樊盛, 蓝峻峰, 叶有明, 谢雪珍, 陈燕萌
作者信息
  • 广西科技师范学院 化学与材料工程学院,广西 来宾 546100
  • 杨鹏飞(1993—),男,硕士,讲师,主要研究方向为湿法冶金。

通讯作者:

陈燕萌(1986—),女,硕士,副教授,主要研究方向为湿法冶金。E-mail:
Leaching Mechanism of Cobalt and Lithium from Waste Lithium Cobaltate Batteries by L-Malic Acid/Ascorbic Acid
Pengfei YANG, Fansheng LAN, Junfeng LAN, Youming YE, Xuezhen XIE, Yanmeng CHEN
Affiliations
  • College of Chemistry and Materials Engineering, Guangxi Science and Technology Normal University, Laibin 546100, China
出版时间: 2025-06-20 doi: 10.13355/j.cnki.sfyj.2025.03.004
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废旧锂离子电池中钴酸锂的资源化回收对于缓解资源短缺和减少环境污染具有重要意义。研究了以L-苹果酸/抗坏血酸体系为浸出剂,从废旧钴酸锂电池中回收钴与锂,考察了L-苹果酸和抗坏血酸浓度、液固体积质量比、浸出温度和时间对钴、锂浸出率的影响,并通过动力学分析和SEM表征探讨了浸出机制。结果表明:最佳浸出条件为L-苹果酸浓度0.2 mol/L,抗坏血酸浓度0.1 mol/L,液固体积质量比0.3 mL/1 mg,浸出温度70 ℃,浸出时间1 h,在该条件下,钴和锂浸出率均达98%以上;浸出过程主要受外部扩散控制。该法高效、环保,可为废旧锂离子电池中钴酸锂的绿色回收提供技术参考。

L-苹果酸  /  抗坏血酸  /  废旧钴酸锂电池  /  浸出  /  锂  /  钴  /  机制

The recycling of lithium cobaltate from waste lithium-ion batteries is of great significance for alleviating resource shortage and reducing environmental pollution. L-malic acid/ascorbic acid system was used as leaching agent to recover cobalt and lithium from waste lithium cobaltate batteries. The effects of L-malic acid concentration, ascorbic acid concentration, liquid volume to solid mass ratio, reaction temperature and time on the leaching rates of cobalt and lithium in lithium cobaltate were investigated. The leaching mechanism was discussed through kinetic analysis and SEM characterization. The results show that the optimal leaching conditions are L-malic acid concentration of 0.2 mol/L, ascorbic acid concentration of 0.1 mol/L, liquid volume to solid mass ratio of 0.3 mL/1 mg, reaction temperature of 70 ℃, leaching time of 1 h. Under the conditions, the leaching rates of cobalt and lithium are above 98%. The kinetic analysis shows that the leaching process is mainly controlled by external diffusion. The method is efficient and environmentally friendly, and can provide an important technical reference for the green recovery of lithium cobaltate in waste lithium-ion batteries.

L-malic acid  /  ascorbic acid  /  waste lithium cobaltate batteries  /  leaching  /  lithium  /  cobalt  /  mechanism
杨鹏飞, 蓝樊盛, 蓝峻峰, 叶有明, 谢雪珍, 陈燕萌. L-苹果酸/抗坏血酸对废旧钴酸锂电池中钴与锂元素浸出机制研究. 湿法冶金, 2025 , 44 (3) : 309 -315 . DOI: 10.13355/j.cnki.sfyj.2025.03.004
Pengfei YANG, Fansheng LAN, Junfeng LAN, Youming YE, Xuezhen XIE, Yanmeng CHEN. Leaching Mechanism of Cobalt and Lithium from Waste Lithium Cobaltate Batteries by L-Malic Acid/Ascorbic Acid[J]. Hydrometallurgy of China, 2025 , 44 (3) : 309 -315 . DOI: 10.13355/j.cnki.sfyj.2025.03.004
钴酸锂(LiCoO2)作为锂离子电池中常用的一种正极材料,广泛应用于电子产品、电动汽车及储能领域[1-2]。但随着锂离子电池的广泛使用,废旧锂离子电池数量也随之增加。废旧锂离子电池中不仅含有大量有价金属(如Co和Li),还含有电解液、导电剂等对环境和人类健康有害的物质[3]。因此,高效回收其中的有价金属不仅能够有效节约资源,还能显著减少环境污染,符合绿色循环经济的理念,有利于推动行业的可持续发展[4-5]
湿法冶金因具有操作简便、成本较低、金属回收率较高等优点,已广泛应用于废旧锂离子电池的金属回收[6-7]。但传统的浸出工艺普遍依赖于强酸、强氧化剂(如硫酸-双氧水体系[8]),浸出率虽高,但存在操作风险高、环境污染大等问题[9]。因此,探索环境友好型的浸出体系逐渐成为了研究热点。
近年来,有机酸作为一种绿色、可降解的浸出剂,因毒性低、环境兼容性好而受到广泛关注[10-11]。其中,L-苹果酸(C4H6O5,MA)是一种典型的二元羧酸,具有较强的配合能力,能够与金属离子形成稳定的螯合物,从而显著提高金属溶解度[12];抗坏血酸(L-抗坏血酸,VC)作为一种还原型有机酸,其化学性质活泼,在氧化还原反应中具有良好的电子供体特性,能将高价态的Co3+还原为低价态的Co2+,从而促进钴的浸出。L-苹果酸和抗坏血酸作为食品级添加剂对环境的危害性较低,且二者作为浸出剂,在温和条件下即可获得较好的浸出效果,不仅能降低能耗,还能避免使用强氧化剂。但现有相关研究主要集中在单一有机酸的浸出性能评估方面,而对于L-苹果酸和抗坏血酸的协同作用研究仍不足,特别是二者对钴酸锂中钴和锂浸出行为的影响机制,尚未得到系统阐释。因此,试验考察了L-苹果酸和抗坏血酸对废旧钴酸锂电池中钴与锂的协同浸出作用,优化了浸出工艺参数,并深入分析了浸出过程中的反应机制,以期为未来开发绿色、高效的废旧电池回收工艺提供参考。
试验原料:废旧钴酸锂电池,来自卓能新能源股份有限公司(深圳,中国)。废旧钴酸锂电池经饱和氯化钠溶液放电、手动拆卸等预处理后得到正极材料,其XRD图谱如图1所示,可见衍射峰和钴酸锂的标准卡片吻合。
试验试剂:抗坏血酸,购自成都市科隆化学品有限公司(中国);L-苹果酸(纯度为98%)购自上海麦克林生化有限公司(中国)。所有试剂均直接使用,无须提纯。
主要仪器:原子吸收分光光度计,AAS-6300CF型,日本岛津公司;X射线衍射仪(XRD),UltimaⅣ型,日本理学公司;场发射扫描电镜(SEM),MIRALMS型,捷克泰思肯有限公司。
L-苹果酸和抗坏血酸在废旧钴酸锂电池正极材料浸出过程中的协同作用机制主要依赖于二者的还原和配合能力。钴酸锂本身在酸性条件下可以分解,其中的钴和锂会以离子形式溶解,抗坏血酸作为还原剂,能将钴酸锂中的Co3+还原为更易溶解的Co2+,从而加快钴浸出速率;同时,L-苹果酸会与Co2+形成稳定的配合物,进一步增大钴溶解度。反应方程式如下:
LiCoO2+4H+=Li++Co3++2H2O;
C6H8O6+2Co3+=2Co2++C6H6O6+2H+;
Co2++2C4H6O5= C o ( C 4 H 6 O 5 ) 2 2 +
称取500 mg废旧钴酸锂电池样品置于100 mL圆底烧瓶中,分别加入0.05~1.25 mol/L的L-苹果酸溶液与0~0.3 mol/L的抗坏血酸;将烧瓶置于带有磁力搅拌的恒温水浴中,并将温度设置在40~80 ℃范围内;液固体积质量比设置为0.05~0.4 mL/1 mg。Li和Co浸出率计算公式如下:
x B = ρ B ρ B 0 × 100 %
式中:xB—Li或Co浸出率,%;ρB—浸出液中Li或Co质量浓度,μg/mL;ρB0—正极材料被消解后Li或Co质量浓度,μg/mL。
采用原子吸收分光光度计测定滤液中Li和Co含量;采用X射线衍射仪分析固体粉末样品的晶体结构,数据采集的范围(2θ)为5°~80°,扫描速度为2°/min,通过场发射扫描电镜分析表面形貌。
在抗坏血酸浓度为0.2 mol/L、浸出时间为1 h、浸出温度为80 ℃、液固体积质量比为0.3 mL/1 mg条件下,探究L-苹果酸浓度对Li和Co浸出率的影响,结果如图2所示。
图2看出,L-苹果酸浓度对Li和Co浸出率的影响显著:L-苹果酸浓度从0.05 mol/L增至0.2 mol/L时,Li和Co浸出率迅速升高,并达98%以上;随后继续增大L-苹果酸浓度,Li和Co浸出率趋于平稳,说明浸出反应已达到平衡状态。因此,确定选择L-苹果酸浓度为0.2 mol/L,以兼顾浸出效果和经济性。
在L-苹果酸浓度为0.2 mol/L、浸出时间为1 h、浸出温度为80 ℃、液固体积质量比为0.3 ml/1 mg条件下,探究抗坏血酸浓度对Li和Co浸出率的影响,结果如图3所示。
图3看出,随抗坏血酸浓度增大,Li和Co浸出率均先升高后趋于平稳:抗坏血酸浓度从0增至0.1 mol/L,Li和Co浸出率均逐渐升高;抗坏血酸浓度大于0.1 mol/L时,Li和Co浸出率均无明显变化,且在98%以上。这是因为抗坏血酸作为一种还原剂,在浸出过程中能通过还原反应将Co3+还原为Co2+,而Co2+更易与L-苹果酸反应,进而提高浸出率;抗坏血酸浓度增至0.1 mol/L后,溶液中的还原剂浓度可满足金属还原需求,金属离子的还原反应基本完成,之后进一步增大抗坏血酸浓度,Li和Co浸出率也不会有明显变化。因此,确定选择抗坏血酸浓度为0.1 mol/L。
在L-苹果酸浓度为0.2 mol/L、抗坏血酸浓度为0.1 mol/L、浸出时间为1 h、浸出温度为80 ℃条件下,探究液固体积质量比对Li和Co浸出率的影响,结果如图4所示。
图4看出;液固体积质量比从0.05 mL/1 mg增至0.3 mL/1 mg时,Li和Co浸出率均显著升高,并在0.3 mL/1 mg下达最大值;液固体积质量比继续增大,Li浸出率几乎不变,而Co浸出率略有下降。这可能是由于液固体积质量比过大时,溶液中的L-苹果酸/抗坏血酸浓度被稀释,对金属浸出率产生了影响。因此,确定选择液固体积质量比为0.3 mL/1 mg。
在L-苹果酸浓度为0.2 mol/L、抗坏血酸浓度为0.1 mol/L、浸出时间为1 h、液固体积质量比为0.3 ml/1 mg条件下,探究浸出温度对Li和Co浸出率的影响,结果如图5所示。
图5看出:浸出温度从40 ℃升至60 ℃,Li和Co浸出率均显著提高;浸出温度升至70 ℃时,Li和Co浸出率均可99%,表明升高温度可以加快L-苹果酸/抗坏血酸与目标金属的反应速率,从而提高浸出率。这主要是因为温度升高促进了反应动力学过程,增强了溶剂分子的扩散能力和金属的配合反应效率。因此,确定选择浸出温度为70 ℃,以兼顾浸出效率提升和能耗节约。
在L-苹果酸浓度为0.2 mol/L、抗坏血酸浓度为0.1 mol/L、浸出温度为70 ℃、液固体积质量比为0.3 ml/1 mg条件下,探究浸出时间对Li和Co浸出率的影响,结果如图6所示。可以看出:浸出时间从10 min延长至60 min,Li和Co浸出率均迅速上升,表明在浸出初期,金属离子浸出速率较快,这可能是因为在溶液中反应物浓度较高,传质和化学反应的驱动力更强;随浸出时间继续延长,Li和Co浸出率趋于稳定,表明体系内的传质与化学反应逐渐达到平衡状态。因此,确定选择浸出时间为60 min。
L-苹果酸、抗坏血酸、L-苹果酸/抗坏血酸对Li和Co浸出率的对比结果如图7所示。可以看出:单独使用L-苹果酸作为浸出剂,Li和Co浸出效果较差;相比之下,单独使用抗坏血酸为浸出剂的Li和Co浸出效果较好,说明抗坏血酸能有效促进Co和Li溶解;L-苹果酸与抗坏血酸同时使用时,二者的协同作用能进一步提高Li和Co浸出率,浸出率均超过98%。综上可知,L-苹果酸/抗坏血酸的效果优于单一浸出剂,二者的协同作用对提高金属浸出率有明显影响。
浸出前、后正极材料的SEM分析结果如图8所示。可知:浸出前钴酸锂正极材料为规则的颗粒状,表面较为光滑,分布均匀,呈完整的晶体结构;而经过L-苹果酸/抗坏血酸浸出后的浸出渣形貌发生了显著变化,颗粒形态趋于破碎,表面变得粗糙且多孔化,同时存在大量片状或絮状结构,表明材料在浸出过程中发生了严重溶解现象。这种形貌的显著变化,不仅反映了浸出体系对钴酸锂结构的强烈破坏作用,也进一步验证了浸出体系对钴酸锂正极材料浸出效果较好。
确定反应速率控制步骤对于更好地理解浸出机制至关重要。通过探讨浸出动力学,可以深入掌握浸出反应的特性。目前,用于描述浸出过程的典型动力学模型通常有4种,即外扩散、内扩散、化学反应和混合控制模型[13-14]。4种控制模型如下:
外扩散控制模型:
x = k 1 t ;
内扩散控制模型:
1 - 2 3 x - ( 1 - x ) 2 3 = k 2 t ;
化学反应控制模型:
1 - ( 1 - x ) 1 3 = k 3 t;
混合控制模型:
( 1 - x ) 1 3 - 1 + 1 3 l n ( 1 - x ) = k 4 t
式中:x—金属浸出率,%;k1—外扩散模型的速率常数,min-1;k2—内扩散模型的速率常数,min-1;k3—化学反应控制模型的速率常数,min-1;k4—混合控制模型的速率常数,min-1;t—浸出时间,min。
为了探究浸出过程的速率控制步骤进行了动力学分析。在最佳条件下,研究了不同浸出温度(40、50、60、70 ℃)和不同浸出时间(10~60 min)下的浸出动力学,并根据相应的动力学方程进行动力学拟合,结果如图9~11所示。
图9看出:金属浸出率随浸出时间延长和浸出温度升高逐渐升高,这是由于温度升高,溶质的扩散速率和反应速率加快,促进了浸出过程的进行。通过对比3种模型的拟合度发现,Li、Co外扩散控制模型的相关系数分别为R2=0.94、R2=0.97(图10),明显优于化学反应控制、内部扩散控制模型和混合控制模型,表明浸出过程主要受外部扩散的限制。此外,不同温度下Li、Co外扩散模型的拟合结果(图11)显示,其R2均在0.94以上,进一步验证了外扩散模型在描述浸出过程中的适用性。
以L-苹果酸/抗坏血酸体系为浸出剂,从废旧钴酸锂电池中绿色回收钴和锂是可行的。通过优化浸出条件,确定最佳浸出参数为:L-苹果酸浓度0.2 mol/L,抗坏血酸浓度0.1 mol/L,液固体积质量比0.3 mL/1 mg,浸出温度70 ℃和浸出时间1 h。在此条件下,钴和锂浸出率均超过98%,该法在高效回收钴酸锂中的钴和锂方面具有显著优势。动力学分析结果表明,浸出过程主要受到外部扩散的控制,进一步揭示了浸出过程的机制。扫描电子显微镜(SEM)表征结果表明,浸出过程中钴酸锂的结构发生了明显变化,进一步证实了L-苹果酸和抗坏血酸协同作用在浸出过程中的重要性。该法可为废旧锂离子电池中钴酸锂的资源化回收提供一种有效且环保的解决方案,具有潜在应用价值,对缓解钴和锂资源短缺和减少环境污染具有重要意义。
  • 广西科技计划项目(桂科AB22035053)
  • 广西科技计划项目(桂科AD20297139)
  • 广西科技师范学院科研基金项目(GXKS2023ZDB009)
  • 广西科技师范学院科研基金项目(GXKS2024QNTD13)
  • 广西重点研发计划项目(桂科AB24010240)
  • 广西科技师范学院创新训练计划项目(X2024175)
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2025年第44卷第3期
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doi: 10.13355/j.cnki.sfyj.2025.03.004
  • 接收时间:2025-01-08
  • 首发时间:2025-09-01
  • 出版时间:2025-06-20
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  • 收稿日期:2025-01-08
基金
广西科技计划项目(桂科AB22035053)
广西科技计划项目(桂科AD20297139)
广西科技师范学院科研基金项目(GXKS2023ZDB009)
广西科技师范学院科研基金项目(GXKS2024QNTD13)
广西重点研发计划项目(桂科AB24010240)
广西科技师范学院创新训练计划项目(X2024175)
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    广西科技师范学院 化学与材料工程学院,广西 来宾 546100

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陈燕萌(1986—),女,硕士,副教授,主要研究方向为湿法冶金。E-mail:
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2种不同金属材料的力学参数

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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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