100 kHz腔倒空薄片激光器理论与实验研究

对100 kHz运转的腔倒空薄片激光器的输出特性进行了理论和实验研究。首先建立起腔倒空薄片激光器的速率方程理论模型，模型中考虑了单位时间谐振腔中新增的自发辐射光子数，对其占总自发辐射光子数的比例进行了分析，并结合一些参数进行了仿真。进一步搭建了重复频率为100 kHz的腔倒空薄片激光器实验装置，获得了平均功率为253 W的纳秒激光脉冲输出，光光效率约为35.2%,脉冲宽度为10.4 ns,单脉冲能量为2.53 mJ,脉冲的峰值功率超过了200 kW,x和y方向的光束质量M²分别为9.77和9.27。针对腔倒空调Q的动力学稳定性问题，研究了普克尔盒开关时间对输出平均功率和输出脉冲稳定性的影响，实验中观察到了倍周期分岔和确定性混沌现象，从理论上对这个现象进行了仿真分析，仿真结果可与实验结果相符。     

Numerical study of dynamic zigzag patterns in migrating epithelial tissue

Collective cell migration plays a crucial role in embryonic development, metastasis, and wound healing. Nevertheless, to the best of our knowledge, how the coordination between the cell motility and deformations affects the collective motion of epithelial cells is not fully understood. In this work, we propose a modified self-propelled Voronoi model for epithelial cell migration incorporating the coupling between the self-propulsion of cells and the polarization of the cell elongation. At a high coupling strength,we observe the emergence of backward traveling band structures formed by highly aligned cells, which can be regulated by cell elongations or shape anisotropy. Increasing the cell shape anisotropy, we find that large bands split into multiple small microbands. The latter essentially forms a dynamic zigzag pattern, in which the angle between the polarization direction of the bands and the migration direction switches alternatively between π/4 and-π/4 because the cells are forced to move preferentially in the anterior direction. We also analyzed the disclinations in the cell monolayer, force distribution near the domain boundaries and the shape alignment of the epithelial monolayer during the formation of this dynamic pattern. The present findings may further our understanding of stripe pattern formations in living systems and inspire potential designs for cell sorting.     

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。