利用可再生电力将二氧化碳转化为高附加值产品的电催化二氧化碳还原反应(CO_(2)RR)是一项具有革命性潜力的技术,因而备受关注.其中,一氧化碳被视为CO_(2)RR中最具经济效益的产物之一,可直接利用费托合成工艺将其用于合成醛、酮、烃类等...利用可再生电力将二氧化碳转化为高附加值产品的电催化二氧化碳还原反应(CO_(2)RR)是一项具有革命性潜力的技术,因而备受关注.其中,一氧化碳被视为CO_(2)RR中最具经济效益的产物之一,可直接利用费托合成工艺将其用于合成醛、酮、烃类等产品.酞菁钴(CoPc)作为单位点催化剂,因其高原子利用率和高催化选择性能,在二氧化碳转化为一氧化碳过程中具有很大优势.然而,CoPc无法为CO_(2)RR中的质子化过程提供足够质子,导致其在工业大电流密度下的效率较低.因此,探索一种能够解决CO_(2)RR中质子供给不足问题的高效电催化剂对于提升CO_(2)RR的性能至关重要.本文设计了具有增强质子供给作用的缺陷碳纳米管(d-CNT),将其作为导电载体分散CoPc,用于制备CoPc/d-CNT电催化剂.通过引入富缺陷的碳纳米管(d-CNT),加速水解离进而增加CO_(2)RR的质子供给量.X射线光电子能谱、X射线吸收近边光谱和扩展X射线吸收精细结构谱结果表明,CoPc/d-CNT成功合成,同时保留了CoPc完整的Co-N4配位结构.透射电镜、粉末X射线衍射谱和拉曼光谱共同表明,d-CNT表面缺陷相对于商用CNT明显增加.动力学实验和原位衰减全反射表面增强红外吸收光谱研究表明,含大量缺陷的d-CNT具有加速水解离的能力,显著提高了二氧化碳还原反应过程中的质子供给,从而促进了CoPc_上CO_(2)活化生成*COOH.同时,密度泛函理论计算结果表明,d-CNT表面缺陷位点上从吸附水(*H2O)到质子水(H3O+)的吉布斯自由能为0.74 eV,远低于CNT(超过2 eV),表明d-CNT促进了水解过程和质子传递,再次证实了d-CNT降低了水分子解离的势垒.通过实验和理论的共同验证,阐明了d-CNT中的缺陷能够促进水解离,改善CO_(2)RR反应过程中质子供给,增强CoPc高效催化CO_(2)RR的能力.因此,CoPc/d-CNT混合材料表现出较好的催化性能.在电流密度为500 mA cm^(-2)的流动电池中,CoPc/d-CNT�展开更多
近年来,具有独特电子效应和协同效应的异质界面工程策略在扩展催化功能和提高本征活性方面显示出较大的应用潜力.其中,具有晶型/无定形(c/a)异质结构的电催化剂,由于结构上的巨大差异,展现出显著的催化活性.然而,c/a-异质界面的可控调...近年来,具有独特电子效应和协同效应的异质界面工程策略在扩展催化功能和提高本征活性方面显示出较大的应用潜力.其中,具有晶型/无定形(c/a)异质结构的电催化剂,由于结构上的巨大差异,展现出显著的催化活性.然而,c/a-异质界面的可控调控及其与电催化性能的内在联系仍缺乏系统研究.因此,本文采用“酸刻蚀-气相磷硫化-淬火”方法,合成了具有可调控c/a异质界面的q-CoPS材料,并将其应用于碱性整体水分解.同时,通过控制淬火的初始温度,实现了对CoPS纳米棒中c/a比例的有效调控.一般来说,在晶型材料中,表面催化往往发生在固定的晶面上.而无定形材料可以同时满足体积和表面的催化.同时,无定形材料具有柔韧性,在催化反应过程中可以转化为任何需要的其他形式,因此在耐腐蚀方面也具有较好的自愈性能.此外,无定形材料还具有丰富的缺陷,运用缺陷工程可以带来一定的性能提升.因此,二者的协同作用可以提升催化剂的催化性能.本文创新性地提出了通过改变淬火初始温度对CoPS纳米棒中c/a比进行调控.采用“酸刻蚀-气相磷硫化-淬火”方法,成功制备了具有独特c/a-CoPS核壳异质结构的q-CoPS纳米棒.随着淬火初始温度的升高,无定形CoPS壳的面积也在逐渐增大.这可能是由于处于非平衡状态的磷硫化物在超低温液氮中突然淬火,处于热运动的Co,P和S原子会迅速冷却,趋向于形成无序的CoPS无定形材料.值得注意的是,制备得到的q-CoPS纳米棒具有合适的c/a含量比,提供了丰富的c/a界面活性位点,并优化了Co位点的电子构型.在析氢反应(HER)中,q-CoPS/CF仅需90 m V的过电位即可以达到1000 m Acm^(-2)的工业级电流密度,结果优于先进的Pt/C.同时,q-CoPS/CF在肼氧化反应(HzOR)中,仅0.06 V时即可实现1000 m Acm^(-2)的电流密度.密度泛函理论计算表明,在HER和HzOR中,界面处的Co原子的内在活性远�展开更多
碱性析氢反应(HER)可将间歇性可再生能源转化为可存储的清洁能源,因而备受关注.然而,水解离速度缓慢以及H中间体(*H)吸附和解吸困难限制了碱性HER的进一步发展.目前,针对碱性电解水解离缓慢问题,通常采用调整电催化剂结构降低水分解热...碱性析氢反应(HER)可将间歇性可再生能源转化为可存储的清洁能源,因而备受关注.然而,水解离速度缓慢以及H中间体(*H)吸附和解吸困难限制了碱性HER的进一步发展.目前,针对碱性电解水解离缓慢问题,通常采用调整电催化剂结构降低水分解热动力学能垒,以及改变三相界面微环境加速中间产物的扩散等方法来促进水分解进行.此外,可以通过调控活性位点电子结构来优化*H的吸脱附.但是采用单一的策略很难同时促进H_(2)O的解离和*H的吸脱附,难以获得令人满意的碱性HER性能.因此,探索一种能同时促进H_(2)O的解离和*H的吸脱附协同策略对提升碱性HER的性能至关重要.本文提出了一种协同策略,通过构建高曲率二硫化钴纳米针(CoS_(2)NNs)和原子级铜(Cu)的掺杂分别实现诱导纳米尺度的局域电场和原子尺度的电子局域化,从而促进碱性HER的H_(2)O解离和*H吸脱附.首先,采用有限元法模拟和密度泛函理论计算,从理论上分别证实了纳米尺度局域电场可以加速H_(2)O解离以及原子尺度电子局域化可以促进*H吸附.受理论计算结果启发,通过一步水热法和原位硫化相结合的方法制备了高曲率的Cu掺杂CoS_(2)纳米针(Cu-CoS_(2)NNs).采用扫描电镜(SEM)、透射电镜(TEM)、X射线衍射(XRD)和四探针测试等技术进行表征,研究了Cu-CoS_(2)NNs的形貌、物相结构、化学组成和导电性.结果表明,在Cu原子引入后,Cu-CoS_(2)NNs依然保持着高曲率的纳米针结构,证明了Cu在CoS_(2)NNs中的原子分散状态.相较于低曲率的Cu掺杂CoS_(2)纳米线(Cu-CoS_(2)NWs),Cu-CoS_(2)NNs只存在形貌上的区别,二者的化学组成和比例均非常接近.同时,上述材料都具有很强的导电性,且电导率基本相同,这与有限元模拟结果一致.原位衰减全反射红外光谱和电响应测试结果表明,Cu-CoS_(2)NNs具有较好的解离H_(2)O和吸附*H的能力.在1 mol L^(-1)KOH溶液和10 mA cm^(-2)展开更多
This paper focuses on end-to-end task-oriented dialogue systems,which jointly handle dialogue state tracking(DST)and response generation.Traditional methods usually adopt a supervised paradigm to learn DST from a manu...This paper focuses on end-to-end task-oriented dialogue systems,which jointly handle dialogue state tracking(DST)and response generation.Traditional methods usually adopt a supervised paradigm to learn DST from a manually labeled corpus.However,the annotation of the corpus is costly,time-consuming,and cannot cover a wide range of domains in the real world.To solve this problem,we propose a multi-span prediction network(MSPN)that performs unsupervised DST for end-to-end task-oriented dialogue.Specifically,MSPN contains a novel split-merge copy mechanism that captures long-term dependencies in dialogues to automatically extract multiple text spans as keywords.Based on these keywords,MSPN uses a semantic distance based clustering approach to obtain the values of each slot.In addition,we propose an ontology-based reinforcement learning approach,which employs the values of each slot to train MSPN to generate relevant values.Experimental results on single-domain and multi-domain task-oriented dialogue datasets show that MSPN achieves state-of-the-art performance with significant improvements.Besides,we construct a new Chinese dialogue dataset MeDial in the low-resource medical domain,which further demonstrates the adaptability of MSPN.展开更多
Although neural approaches have yielded state-of-the-art results in the sentence matching task,their perfor-mance inevitably drops dramatically when applied to unseen domains.To tackle this cross-domain challenge,we a...Although neural approaches have yielded state-of-the-art results in the sentence matching task,their perfor-mance inevitably drops dramatically when applied to unseen domains.To tackle this cross-domain challenge,we address unsupervised domain adaptation on sentence matching,in which the goal is to have good performance on a target domain with only unlabeled target domain data as well as labeled source domain data.Specifically,we propose to perform self-su-pervised tasks to achieve it.Different from previous unsupervised domain adaptation methods,self-supervision can not on-ly flexibly suit the characteristics of sentence matching with a special design,but also be much easier to optimize.When training,each self-supervised task is performed on both domains simultaneously in an easy-to-hard curriculum,which gradually brings the two domains closer together along the direction relevant to the task.As a result,the classifier trained on the source domain is able to generalize to the unlabeled target domain.In total,we present three types of self-super-vised tasks and the results demonstrate their superiority.In addition,we further study the performance of different usages of self-supervised tasks,which would inspire how to effectively utilize self-supervision for cross-domain scenarios.展开更多
Objective: The purpose of this study was to evaluate the correlation between CT perfusion parameters and the hypoxia-inducible factor-1 alpha (HIF-1α), vascular en-dothelial growth factor (VEGF), matrix metalloprotei...Objective: The purpose of this study was to evaluate the correlation between CT perfusion parameters and the hypoxia-inducible factor-1 alpha (HIF-1α), vascular en-dothelial growth factor (VEGF), matrix metalloproteinase-2 (MMP-2) and microvessel density (MVD) marked by CD34 molecular of rabbit VX2 liver tumors and to investigate the value of CT perfusion imaging in evaluating tumor angiogenesis. Material and methods: Twenty-four cases of rabbit VX2 liver tumor were performed by CT perfusion scanning. Hepatic artery perfusion (HAP), portal vein perfusion (PVP), total hepatic blood flow (THBF) and hepatic perfusion index (HPI) were measured by perfusion software. HIF-1α, VEGF and MMP-2 expression and MVD were detected in the 24 rabbit VX2 liver tumor tissue samples using immunohistochemical method. The correlation between the HIF-1α, VEGF, MMP-2 expression and MVD and CT perfusion parameters were analyzed. Results: Correlation analysis revealed that the expression of HIF-1α, MMP-2, MVD were positively related to the HAP, THBF, HPI (p < 0.01), but no relations with PVP (p > 0.05);and correlation analysis revealed that the expression of VEGF was positively related to the HAP, HPI (p 0.05). There was a positive relationship between the expression of HIF-1α, VEGF, MMP-2 and MVD (p < 0.01). Conclusions: CT perfusion imaging can reflect the blood perfusion of the rabbit VX2 liver tumors and evaluate the information of angiogenesis about tumors.展开更多
文摘利用可再生电力将二氧化碳转化为高附加值产品的电催化二氧化碳还原反应(CO_(2)RR)是一项具有革命性潜力的技术,因而备受关注.其中,一氧化碳被视为CO_(2)RR中最具经济效益的产物之一,可直接利用费托合成工艺将其用于合成醛、酮、烃类等产品.酞菁钴(CoPc)作为单位点催化剂,因其高原子利用率和高催化选择性能,在二氧化碳转化为一氧化碳过程中具有很大优势.然而,CoPc无法为CO_(2)RR中的质子化过程提供足够质子,导致其在工业大电流密度下的效率较低.因此,探索一种能够解决CO_(2)RR中质子供给不足问题的高效电催化剂对于提升CO_(2)RR的性能至关重要.本文设计了具有增强质子供给作用的缺陷碳纳米管(d-CNT),将其作为导电载体分散CoPc,用于制备CoPc/d-CNT电催化剂.通过引入富缺陷的碳纳米管(d-CNT),加速水解离进而增加CO_(2)RR的质子供给量.X射线光电子能谱、X射线吸收近边光谱和扩展X射线吸收精细结构谱结果表明,CoPc/d-CNT成功合成,同时保留了CoPc完整的Co-N4配位结构.透射电镜、粉末X射线衍射谱和拉曼光谱共同表明,d-CNT表面缺陷相对于商用CNT明显增加.动力学实验和原位衰减全反射表面增强红外吸收光谱研究表明,含大量缺陷的d-CNT具有加速水解离的能力,显著提高了二氧化碳还原反应过程中的质子供给,从而促进了CoPc_上CO_(2)活化生成*COOH.同时,密度泛函理论计算结果表明,d-CNT表面缺陷位点上从吸附水(*H2O)到质子水(H3O+)的吉布斯自由能为0.74 eV,远低于CNT(超过2 eV),表明d-CNT促进了水解过程和质子传递,再次证实了d-CNT降低了水分子解离的势垒.通过实验和理论的共同验证,阐明了d-CNT中的缺陷能够促进水解离,改善CO_(2)RR反应过程中质子供给,增强CoPc高效催化CO_(2)RR的能力.因此,CoPc/d-CNT混合材料表现出较好的催化性能.在电流密度为500 mA cm^(-2)的流动电池中,CoPc/d-CNT�
文摘近年来,具有独特电子效应和协同效应的异质界面工程策略在扩展催化功能和提高本征活性方面显示出较大的应用潜力.其中,具有晶型/无定形(c/a)异质结构的电催化剂,由于结构上的巨大差异,展现出显著的催化活性.然而,c/a-异质界面的可控调控及其与电催化性能的内在联系仍缺乏系统研究.因此,本文采用“酸刻蚀-气相磷硫化-淬火”方法,合成了具有可调控c/a异质界面的q-CoPS材料,并将其应用于碱性整体水分解.同时,通过控制淬火的初始温度,实现了对CoPS纳米棒中c/a比例的有效调控.一般来说,在晶型材料中,表面催化往往发生在固定的晶面上.而无定形材料可以同时满足体积和表面的催化.同时,无定形材料具有柔韧性,在催化反应过程中可以转化为任何需要的其他形式,因此在耐腐蚀方面也具有较好的自愈性能.此外,无定形材料还具有丰富的缺陷,运用缺陷工程可以带来一定的性能提升.因此,二者的协同作用可以提升催化剂的催化性能.本文创新性地提出了通过改变淬火初始温度对CoPS纳米棒中c/a比进行调控.采用“酸刻蚀-气相磷硫化-淬火”方法,成功制备了具有独特c/a-CoPS核壳异质结构的q-CoPS纳米棒.随着淬火初始温度的升高,无定形CoPS壳的面积也在逐渐增大.这可能是由于处于非平衡状态的磷硫化物在超低温液氮中突然淬火,处于热运动的Co,P和S原子会迅速冷却,趋向于形成无序的CoPS无定形材料.值得注意的是,制备得到的q-CoPS纳米棒具有合适的c/a含量比,提供了丰富的c/a界面活性位点,并优化了Co位点的电子构型.在析氢反应(HER)中,q-CoPS/CF仅需90 m V的过电位即可以达到1000 m Acm^(-2)的工业级电流密度,结果优于先进的Pt/C.同时,q-CoPS/CF在肼氧化反应(HzOR)中,仅0.06 V时即可实现1000 m Acm^(-2)的电流密度.密度泛函理论计算表明,在HER和HzOR中,界面处的Co原子的内在活性远�
文摘碱性析氢反应(HER)可将间歇性可再生能源转化为可存储的清洁能源,因而备受关注.然而,水解离速度缓慢以及H中间体(*H)吸附和解吸困难限制了碱性HER的进一步发展.目前,针对碱性电解水解离缓慢问题,通常采用调整电催化剂结构降低水分解热动力学能垒,以及改变三相界面微环境加速中间产物的扩散等方法来促进水分解进行.此外,可以通过调控活性位点电子结构来优化*H的吸脱附.但是采用单一的策略很难同时促进H_(2)O的解离和*H的吸脱附,难以获得令人满意的碱性HER性能.因此,探索一种能同时促进H_(2)O的解离和*H的吸脱附协同策略对提升碱性HER的性能至关重要.本文提出了一种协同策略,通过构建高曲率二硫化钴纳米针(CoS_(2)NNs)和原子级铜(Cu)的掺杂分别实现诱导纳米尺度的局域电场和原子尺度的电子局域化,从而促进碱性HER的H_(2)O解离和*H吸脱附.首先,采用有限元法模拟和密度泛函理论计算,从理论上分别证实了纳米尺度局域电场可以加速H_(2)O解离以及原子尺度电子局域化可以促进*H吸附.受理论计算结果启发,通过一步水热法和原位硫化相结合的方法制备了高曲率的Cu掺杂CoS_(2)纳米针(Cu-CoS_(2)NNs).采用扫描电镜(SEM)、透射电镜(TEM)、X射线衍射(XRD)和四探针测试等技术进行表征,研究了Cu-CoS_(2)NNs的形貌、物相结构、化学组成和导电性.结果表明,在Cu原子引入后,Cu-CoS_(2)NNs依然保持着高曲率的纳米针结构,证明了Cu在CoS_(2)NNs中的原子分散状态.相较于低曲率的Cu掺杂CoS_(2)纳米线(Cu-CoS_(2)NWs),Cu-CoS_(2)NNs只存在形貌上的区别,二者的化学组成和比例均非常接近.同时,上述材料都具有很强的导电性,且电导率基本相同,这与有限元模拟结果一致.原位衰减全反射红外光谱和电响应测试结果表明,Cu-CoS_(2)NNs具有较好的解离H_(2)O和吸附*H的能力.在1 mol L^(-1)KOH溶液和10 mA cm^(-2)
基金supported by the National Key Research and Development Program of China under Grant No.2020AAA0106400the National Natural Science Foundation of China under Grant Nos.61922085 and 61976211+2 种基金the Independent Research Project of National Laboratory of Pattern Recognition under Grant No.Z-2018013the Key Research Program of Chinese Academy of Sciences(CAS)under Grant No.ZDBS-SSW-JSC006the Youth Innovation Promotion Association CAS under Grant No.201912.
文摘This paper focuses on end-to-end task-oriented dialogue systems,which jointly handle dialogue state tracking(DST)and response generation.Traditional methods usually adopt a supervised paradigm to learn DST from a manually labeled corpus.However,the annotation of the corpus is costly,time-consuming,and cannot cover a wide range of domains in the real world.To solve this problem,we propose a multi-span prediction network(MSPN)that performs unsupervised DST for end-to-end task-oriented dialogue.Specifically,MSPN contains a novel split-merge copy mechanism that captures long-term dependencies in dialogues to automatically extract multiple text spans as keywords.Based on these keywords,MSPN uses a semantic distance based clustering approach to obtain the values of each slot.In addition,we propose an ontology-based reinforcement learning approach,which employs the values of each slot to train MSPN to generate relevant values.Experimental results on single-domain and multi-domain task-oriented dialogue datasets show that MSPN achieves state-of-the-art performance with significant improvements.Besides,we construct a new Chinese dialogue dataset MeDial in the low-resource medical domain,which further demonstrates the adaptability of MSPN.
基金supported by the National Natural Science Foundation of China under Grant Nos.61922085 and 61976211the National Key Research and Development Program of China under Grant No.2020AAA0106400+2 种基金the Key Research Program of the Chinese Academy of Sciences under Grant No.ZDBS-SSW-JSC006the Independent Research Project of the National Laboratory of Pattern Recognition under Grant No.Z-2018013the Youth Innovation Promotion Association of Chinese Academy of Sciences under Grant No.2020138.
文摘Although neural approaches have yielded state-of-the-art results in the sentence matching task,their perfor-mance inevitably drops dramatically when applied to unseen domains.To tackle this cross-domain challenge,we address unsupervised domain adaptation on sentence matching,in which the goal is to have good performance on a target domain with only unlabeled target domain data as well as labeled source domain data.Specifically,we propose to perform self-su-pervised tasks to achieve it.Different from previous unsupervised domain adaptation methods,self-supervision can not on-ly flexibly suit the characteristics of sentence matching with a special design,but also be much easier to optimize.When training,each self-supervised task is performed on both domains simultaneously in an easy-to-hard curriculum,which gradually brings the two domains closer together along the direction relevant to the task.As a result,the classifier trained on the source domain is able to generalize to the unlabeled target domain.In total,we present three types of self-super-vised tasks and the results demonstrate their superiority.In addition,we further study the performance of different usages of self-supervised tasks,which would inspire how to effectively utilize self-supervision for cross-domain scenarios.
文摘Objective: The purpose of this study was to evaluate the correlation between CT perfusion parameters and the hypoxia-inducible factor-1 alpha (HIF-1α), vascular en-dothelial growth factor (VEGF), matrix metalloproteinase-2 (MMP-2) and microvessel density (MVD) marked by CD34 molecular of rabbit VX2 liver tumors and to investigate the value of CT perfusion imaging in evaluating tumor angiogenesis. Material and methods: Twenty-four cases of rabbit VX2 liver tumor were performed by CT perfusion scanning. Hepatic artery perfusion (HAP), portal vein perfusion (PVP), total hepatic blood flow (THBF) and hepatic perfusion index (HPI) were measured by perfusion software. HIF-1α, VEGF and MMP-2 expression and MVD were detected in the 24 rabbit VX2 liver tumor tissue samples using immunohistochemical method. The correlation between the HIF-1α, VEGF, MMP-2 expression and MVD and CT perfusion parameters were analyzed. Results: Correlation analysis revealed that the expression of HIF-1α, MMP-2, MVD were positively related to the HAP, THBF, HPI (p < 0.01), but no relations with PVP (p > 0.05);and correlation analysis revealed that the expression of VEGF was positively related to the HAP, HPI (p 0.05). There was a positive relationship between the expression of HIF-1α, VEGF, MMP-2 and MVD (p < 0.01). Conclusions: CT perfusion imaging can reflect the blood perfusion of the rabbit VX2 liver tumors and evaluate the information of angiogenesis about tumors.
