Recent advances for quantum classifiers

Machine learning has achieved dramatic success in a broad spectrum of applications.Its interplay with quantum physics may lead to unprecedented perspectives for both fundamental research and commercial applications,giving rise to an emergent research frontier of quantum machine learning.Along this line,quantum classifiers,which are quantum devices that aim to solve classification problems in machine learning,have attracted tremendous attention recently.In this review,we give a relatively comprehensive overview for the studies of quantum classifiers,with a focus on recent advances.First,we will review a number of quantum classification algorithms,including quantum support vector machines,quantum kernel methods,quantum decision tree classifiers,quantum nearest neighbor algorithms,and quantum annealing based classifiers.Then,we move on to introduce the variational quantum classifiers,which are essentially variational quantum circuits for classifications.We will review different architectures for constructing variational quantum classifiers and introduce the barren plateau problem,where the training of quantum classifiers might be hindered by the exponentially vanishing gradient.In addition,the vulnerability aspect of quantum classifiers in the setting of adversarial learning and the recent experimental progress on different quantum classifiers will also be discussed.     

A quantum circuit design of AES requiring fewer quantum qubits and gate operations

Advanced Encryption Standard (AES) is one of the most widely used block ciphers nowadays, and has been established as an encryption standard in 2001. Here we design AES-128 and the sample-AES (S-AES) quantum circuits for deciphering. In the quantum circuit of AES-128, we perform an affine transformation for the SubBytes part to solve the problem that the initial state of the output qubits in SubBytes is not the |0>^⊗8 state. After that, we are able to encode the new round sub-key on the qubits encoding the previous round sub-key, and this improvement reduces the number of qubits used by 224 compared with Langenberg et al.’s implementation. For S-AES, a complete quantum circuit is presented with only 48 qubits, which is already within the reach of existing noisy intermediate-scale quantum computers.     

In-situ monitoring of cell-secreted lactate by electrochemiluminescence sensing under biomimetic microfluidic confinement

Cell migration proceeds in 3D matrices in vivo, which can naturally switch to distinct phenotypes for better invasion in confined microenvironments. The studies of important metabolites under confinement are extremely meaningful for comprehensive insights into cancer metastasis. The integration of cell confinement device and analytical techniques is a key point for in-situ analysis of significant metabolites in vitro.Herein, an electrochemiluminescence(ECL) sensing platform was designed for in-s...     

Cleavage/cross-coupling strategy for converting β-O-4 linkage lignin model compounds into high valued benzyl amines via dual C–O bond cleavage

Lignin is the most recalcitrant of the three components of lignocellulosic biomass. The strength and stability of the linkages have long been a great challenge for the degradation and valorization of lignin biomass to obtain bio-fuels and commercial chemicals. Up to now, the selective cleavage of C–O linkages of lignin to afford chemicals contains only C, H and O atoms. Our group has developed a cleavage/crosscoupling strategy for converting 4-O-5 linkage lignin model compounds into high value-a...     

基于MOF (Cu)@biochar气凝胶的制备及其在缓释氮肥上的应用

以羧甲基纤维素(CMC)、明胶和MOF(Cu)@biochar为原料,采用简单有效的冷冻干燥方法制备了(CMC/Gelatin/MOF(Cu)@biochar)杂化气凝胶,并用傅里叶变换红外光谱(FT-IR)、热重分析(TG)、X射线粉末衍射(XRD)、扫描电镜(SEM)和X射线光电子能谱(XPS)技术对其进行了表征;研究了MOF(Cu)@biochar含量、pH和不同的盐水溶液对杂化气凝胶溶胀行为的影响;以该气凝胶负载氯化铵,制备了一种新型缓释肥料(SRF),并研究了含2%(wt)SRF的沙性土壤的保水能力;SRF在土壤中第30天的累积释放率为79.4%;肥料在土壤中释放符合非Fickian扩散和阳离子交换的协同作用机理。     

大一学生实验室安全教育实效研究*

为考查线上线下混合安全教育模式实施后的实际效果,对天津理工大学化工、环安、机械、材料学院2020级大一学生进行实验室安全知识测试。结果表明:接受线上线下混合安全教育的大一学生安全知识的掌握情况较好;不足之处在于学生普遍对应急处置知识掌握较差。因此,在后续安全教育过程中,仍需进一步优化安全教育内容与模式,全面推进全员、全程安全教育。     

1,3-丁二烯选择性加氢催化剂的设计策略以及构效关系

催化裂化是石油化工的核心单元之一.从催化裂化尾气中分离出来的碳四馏分富含许多的不饱和烯烃,如1-丁烯、顺、反式-2-丁烯以及少量的1,3-丁二烯,这些不饱和烯烃可以通过后续聚合反应,生成合成橡胶和工程塑料的重要原料,具有重要的应用价值.上述工艺过程对原料中1,3-丁二烯的含量(<100~200 ppm)有严苛的要求.采用选择性加氢技术对碳四馏分中的1,3-丁二烯进行选择性加氢,将其转化为更高附加值的单烯烃是一个理想的解决方案.然而,1,3-丁二烯加氢反应得到的单烯烃可能发生深度加氢得到副产物丁烷.因此,开发高效选择性加氢催化剂对碳四资源的利用具有重要的现实意义.另一方面,1,3-丁二烯加氢反应可以作为模型反应,用来考察选择性加氢催化剂的性能.基于此,该反应无论在工业界还是学术界均受到广泛关注.尽管如此,有关1,3-丁二烯加氢催化剂研究进展方面的综述极少.仅有关于1,3-丁二烯加氢作为模型反应的综述报道.本文对过去半个世纪以来1,3-丁二烯加氢反应中不同催化剂的发展历程进行系统综述,特别是包括Pd,Pt和Au等的单一贵金属催化剂.重点介绍以下内容:(1)固体催化剂构效关系,包括活性金属尺寸效应、晶面和形貌效应以及载体效应(晶相、孔道和酸碱性);(2)高性能催化剂的设计新策略,如单原子催化剂、核壳结构催化剂、金属-离子液复合催化体系以及载体的形貌调控;(3)催化剂的反应机理和失活机理.提出了1,3-丁二烯选择性加氢高性能催化剂开发面临的挑战,并对潜在的发展方向进行了展望.本文认为随着纳米技术和金属纳米材料合成方法的快速发展,对贵金属活性组分进行原子层面上的调控(包括形貌、尺寸以及单原子配位环境等)已成为可能.这将有助于研制出一类新型高性能选择性加氢催化材料,从而实现高转化率条件下高附加值单烯烃的定向转化.此外,载体的酸碱性和孔道结构的调控有助于进一步调节催化剂的抗积炭性能,也是未来发展的一个重要方向.     

部分还原氧化石墨烯的制备、 表征及对人宫颈癌HeLa细胞的体外杀伤作用

以氧化石墨烯(GO)为原料, 利用温和方法制备了3种不同还原程度的部分还原氧化石墨烯pRGO₁, pRGO₂和pRGO₃(pRGO_1—3)； 利用傅里叶变换红外光谱(FTIR)、 拉曼光谱(Raman)、 X 射线光电子能谱(XPS)、 紫外-可见光谱(UV-Vis)、 透射电子显微镜(TEM)和 EDS能谱对其结构和形貌进行了表征. 细胞实验结果表明, 无激光照射下pRGO_1—3本身的细胞毒性较低; 近红外(NIR)激光照射下pRGO_1—3通过光热和光毒性双重作用杀伤肿瘤细胞. 实验结果显示了pRGO 在肿瘤光热疗法和光动力疗法领域的应用潜力.     

多孔有机笼的制备及其用作毛细管电色谱手性固定相

多孔有机笼(POCs)是具有一类内在的、客体可及的空腔的离散分子，是一类独特的微孔材料。本文根据席夫碱反应原理，用(1R,2R)-二氨基环己烷和3,3′,5,5′-四醛基-4,4′-联苯二酚缩合成一种孔径均匀、高比表面积、热化学稳定性良好的棱柱形手性多孔有机笼(POCs)。采用核磁共振氢谱仪、红外光谱、热重分析和扫描电子显微镜对该材料进行表征。将该材料溶解在二氯甲烷中，用动态涂覆法将溶液均匀地涂覆在石英毛细管内壁上，制成毛细管电色谱柱。结果表明，该手性电色谱柱不仅能拆分氧氟沙星、特罗格尔碱、2-氨基-1-丁醇和1-苯基-1-戊醇4种手性药物，还能拆分o,m,p-甲苯胺和o,m,p-氯苯胺2种位置异构体，说明该手性柱具有良好的手性分离能力。通过研究氧氟沙星、特罗格尔碱、2-氨基-1-丁醇和1-苯基-1-戊醇的最佳拆分条件，得出电压、缓冲溶液浓度和pH值对组分分离度有显著影响，其中，氧氟沙星、特罗格尔碱、2-氨基-1-丁醇的最优分离电压均为15 kV, 1-苯基-1-戊醇的最佳分离电压为17 kV;氧氟沙星、特罗格尔碱、2-氨基-1-丁醇、1-苯基-1-戊醇的最佳缓冲液浓度均为0.100 ...