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Design monolayer iodinenes based on halogen bond and tiling theory

Physical Review B 2024年第12期109卷 125423-125423页

作者： Kejun Yu Yichen Liu Botao Fu Run-Wu Zhang Da-shuai Ma Xiao-ping Li Zhi-Ming Yu Cheng-Cheng Liu Yugui Yao Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) School of Physics Beijing Institute of Technology Beijing 100081 China Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing 100081 China College of Physics and Electronic Engineering Center for Computational Sciences Sichuan Normal University Chengdu 610068 China Institute for Structure and Function and Department of Physics and Chongqing Key Laboratory for Strongly Coupled Physics Chongqing University Chongqing 400044 People's Republic of China Center of Quantum Materials and Devices Chongqing University Chongqing 400044 People's Republic of China School of Physical Science and Technology Inner Mongolia University Hohhot 010021 China

Xenes, two-dimensional (2D) monolayers composed of a single element, with graphene as a typical representative, have attracted widespread attention. Most of the previous Xenes, X from group-IIIA to group-VIA elements, have bonding characteristics of covalent bonds. In this paper, we unveil the pivotal role of a halogen bond, which is a distinctive type of bonding with interaction strength between that of a covalent bond and a van der Waals interaction, in 2D group-VIIA monolayers. Combing the ingenious non-edge-to-edge tiling theory and state-of-the-art ab initio method with refined local density functional M06-L, we provide a precise and effective bottom-up construction of 2D iodine monolayer sheets, iodinenes, primarily governed by halogen bonds, and successfully design a category of stable iodinenes encompassing herringbone, Pythagorean, gyrated truncated hexagonal, i.e., diatomic kagome, and gyrated hexagonal tiling patterns. These iodinene structures exhibit a wealth of properties, such as nontrivial topology, flat bands and fascinating optical characteristics, offering valuable insights and guidance for future experimental investigations. Our paper not only unveils the unexplored halogen bonding mechanism in 2D materials but also opens an avenue for designing other noncovalent bonding 2D materials.

关键词： Electronic structure Structural properties Topological materials 2-dimensional systems Two-dimensional electron system Density functional theory

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Direct transformation of n-alkane into all-trans conjugated polyene via cascade dehydrogenation

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National science Review 2021年第10期8卷 42-49页

作者： Xuechao Li Kaifeng Niu Junjie Zhang Xiaojuan Yu Haiming Zhang Yuemin Wang Qing Guo Pengdong Wang Fangsen Li Zhengming Hao Chaojie Xu Yanning Tang Zhichao Xu Shuai Lu Peng Liu Guigu Xue Yen Wei Lifeng Chi Jiangsu Key Laboratory for Carbon Based Functional Materials & Devices Institute of Functional Nano & Soft Materials Soochow University Department of Physics Chemistry and Biology IFMLink?ping University Institute of Functional Interfaces Karlsruhe Institute of Technology Department of Chemistry Southern University of Science and Technology Vacuum Interconnected Nanotech Workstation (Nano-X) Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of Sciences Key Laboratory of Organic Optoelectronics and Molecular Engineering Department of Chemistry Tsinghua University

Selective C（sp3）-H activation is of fundamental importance in processing alkane feedstocks to produce high-value-added chemical products. By virtue of an on-surface synthesis strategy, we report selective cascade dehydrogenation of n-alkane molecules under surface constraints, which yields monodispersed all-trans conjugated polyenes with unprecedented length controllability. We are also able to demonstrate the generality of this concept for alkyl-substituted molecules with programmable lengths and diverse functionalities, and more importantly its promising potential in molecular wiring.

关键词： C(sp3)-H activation alkane transformation on-surface synthesis dehydrogenation molecular wiring

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Glasslike cross-plane thermal conductivity of the kagome metals RbV3Sb5 and CsV3Sb5

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Physical Review B 2023年第20期108卷 205112-205112页

作者： Yu Pang Jinjin Liu Xuanhui Fan Haobo Yang Jie Zhu Zhiwei Wang Yugui Yao Xin Qian Ronggui Yang School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory of Coal Combustion Huazhong University of Science and Technology Wuhan 430074 China Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) School of Physics Beijing Institute of Technology Beijing 100081 China Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems Beijing Institute of Technology Beijing 100081 China School of Energy and Power Engineering Dalian University of Technology Dalian 116024 China Material Science Center Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314011 China

In this paper, we report on the thermal conductivity of RbV3Sb5 and CsV3Sb5 with three-dimensional charge density wave phase transitions from 40 to 500 K measured by pump-probe thermoreflectance techniques. At room temperature, the in-plane (basal plane) thermal conductivities are found to be moderate, with 12Wm−1K−1 of RbV3Sb5 and 8.8Wm−1K−1 of CsV3Sb5, and ultralow cross-plane (stacking direction) thermal conductivities are observed, with 0.72Wm−1K−1 of RbV3Sb5 and 0.49Wm−1K−1 of CsV3Sb5. A unique glasslike temperature dependence in the cross-plane thermal conductivity is observed, which decreases monotonically even lower than the Cahill-Pohl limit as the temperature decreases below the phase transition point TCDW. This temperature dependence is found to obey the hopping transport picture. In addition, a peak in cross-plane thermal conductivity is observed at TCDW as a fingerprint of the modulated structural distortion along the stacking direction.

关键词： Charge density waves Hopping transport Phase transitions Thermal conductivity Kagome lattice Pump-probe spectroscopy

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Graphene-based optomechanically induced transparency for resonant excitation of a surface plasmon polariton

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Physical Review A 2024年第6期110卷 063508-063508页

作者： Akhtar Munir Ziauddin Shi-Hai Dong Chunfang Wang Department of Physics University of Shanghai for Science and Technology Shanghai 200093 China Quantum Optics Lab. Department of Physics COMSATS University Islamabad Islamabad Pakistan Research Center for Quantum Physics Huzhou University Huzhou 313000 China Centro de Investigación en Computación Instituto Politécnico Nacional UPALM CDMX 07738 Mexico

Cavity optomechanics, which focuses on the radiation-pressure interaction between electromagnetic fields and mechanical resonators, provides a suitable platform for exploring macroscopic quantum effects. Here, we propose an approach for coupler-free resonance excitation of surface plasmon polaritons (SPPs), which comprises a top vacuum or air layer, a metal film, and graphene placed on a dielectric slab. Unlike typical systems that employ an atomic or other solid medium, our setup takes advantage of the unique features of the graphene optomechanical (GOM) medium to investigate the direct resonance excitation of SPPs via optomechanical interactions. By employing two laser beams (a control beam and a probe beam) directed through air or vacuum to the top surface, we reveal that optomechanically induced transparency (OMIT) results from destructive interference between probe field and pump field-driven mechanical oscillations. We observe that this OMIT phenomenon possess the low-loss (high transmission) criterion in the region of slightly negative probe detuning, i.e., Re [ɛc]≪1 and Im [ɛc]<1, which is the basis for observing the coupler-free resonance excitation of SPPs. We utilize the transfer matrix approach to compute the reflectance and transmittance spectra, and we observe small dips in the reflectance and high sharp peaks in the transmittance spectra, revealing coupler-free resonance excitation of SPPs. The amplitudes of these sharp peaks in transmittance spectra showing resonance excitation of SPPs that can be enhanced by properly adjusting the control parameters, including, the control laser beam power, angle of incidence, and the thickness of the metal film. This approach has the potential to provide advantages such as tunable coupling and dynamic control of SPPs, paving the way for plasmonic devices with enhanced functionality and performance.

关键词： Optomechanics Plasmonics Quantum optics

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Auxiliary dynamical mean-field approach for Anderson-Hubbard model with off-diagonal disorder

arXiv

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arXiv 2025年

作者： Zhang, Zelei Yan, Jiawei Huang, Li Ke, Youqi School of physical science and technology ShanghaiTech University Shanghai201210 China 2020 X-LAB Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China Institute of Materials China Academy of Engineering Physics Sichuan Jiangyou621900 China

This work reports a theoretical framework that combines the auxiliary coherent potential approximation (ACPA-DMFT) with dynamical mean-field theory to study strongly correlated and disordered electronic systems with both diagonal and off-diagonal disorders. In this method, by introducing an auxiliary coupling space with extended local degree of freedom,the diagonal and off-diagonal disorders are treated in a unified and self-consistent framework of coherent potential approximation, within which the dynamical mean-field theory is naturally combined to handle the strongly correlated Anderson-Hubbard model. By using this approach, we compute matsubara Green’s functions for a simple cubic lattice at finite temperatures and derive impurity spectral functions through the maximum entropy method. Our results reveal the critical influence of off-diagonal disorder on Mott-type metal-insulator transitions. Specifically, a reentrant phenomenon is identified, where the system transitions between insulating and metallic states under varying interaction strengths. The ACPA-DMFT method provides an efficient and robust computational method for exploring the intricate interplay of disorder and strong correlations. © 2025, CC BY-NC-ND.

关键词： Hubbard model

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Protein Structure Prediction:Challenges,Advances,and the Shift of Research Paradigms

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Genomics, Proteomics & Bioinformatics 2023年第5期21卷 913-925页

作者： Bin Huang Lupeng Kong Chao Wang Fusong Ju Qi Zhang Jianwei Zhu Tiansu Gong Haicang Zhang Chungong Yu Wei-Mou Zheng Dongbo Bu Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Changping Laboratory Beijing 102206China Microsoft Research AI4Science Beijing 100080China Huawei Noah’s Ark Lab Wuhan 430206China Zhongke Big Data Academy Zhengzhou 450046China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China

Protein structure prediction is an interdisciplinary research topic that has attracted researchers from multiple fields,including biochemistry,medicine,physics,mathematics,and computer *** researchers adopt various research paradigms to attack the same structure prediction problem:biochemists and physicists attempt to reveal the principles governing protein folding;mathematicians,especially statisticians,usually start from assuming a probability distribution of protein structures given a target sequence and then find the most likely structure,while computer scientists formulate protein structure prediction as an optimization problem-finding the structural conformation with the lowest energy or minimizing the difference between predicted structure and native *** research paradigms fall into the two statistical modeling cultures proposed by Leo Breiman,namely,data modeling and algorithmic ***,we have also witnessed the great success of deep learning in protein structure *** this review,we present a survey of the efforts for protein structure *** compare the research paradigms adopted by researchers from different fields,with an emphasis on the shift of research paradigms in the era of deep *** short,the algorithmic modeling techniques,especially deep neural networks,have considerably improved the accuracy of protein structure prediction;however,theories interpreting the neural networks and knowledge on protein folding are still highly desired.

关键词： Protein folding Protein structure prediction Deep learning Transformer Language model

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Nano-plasmonic graphene-quantum dots integrated photoelectronic biosensor

Nano-plasmonic graphene-quantum dots integrated photoelectro...

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OptoElectronics and Communications Conference, OECC

作者： Jiaxing Sun Lin Zhou Hongju Mao Jianlong Zhao Xianfeng Chen Department of Physics School of Science and Technology Nottingham Trent University Nottingham United Kingdom State Key Lab of Transducer Tech Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences China

We report a nano-plasmonic biosensor with integrated optoelectronic architecture developed on a miniaturized chip. With simple means, the nano-plasmonic sensor demonstrated the capability to record the selective and specific binding of proteins to the bioreceptors immobilized on gold nanoparticles arrays placed directly on a photoconductive graphene-Perovskite quantum dots hybrid channel. The distinct combination of the nano-plasmonic structure, proteins and hybrid two-dimensional materials endowed the photoelectronic detection of biotin with advantages of label-free, ultrahigh sensitivity and rapid speed.

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Zero sample image anomaly detection guided by multi-modal prompts

Zero sample image anomaly detection guided by multi-modal pr...

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International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign)

作者： Jinhong Wang Xinying Xu Gang Xie Kai Wang Xiaohu Yuan College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan China School of Physics and Electronic Information YanTai University Yantai China Qiyuan Lab Beijing China

ISBN: (数字)9798350363043

ISBN: (纸本)9798350363050

Large visual language models such as CLIP show strong zero sample recognition capability in anomaly detection tasks. It learns object-independent prompts through the guidance of prompt engineering, fine-tunes CLIP to anomaly detection tasks, and shows good generalization ability. However, prompt engineering usually needs to design hundreds of prompts, which increases the difficulty of designing prompts, and can not be used well for multi-class anomaly detection. To solve these problems, this paper proposes a zero sample anomaly detection method guided by multi-modal prompt learning. By introducing multimodal prompts for text branches and visual branches, the consistency of text and visual branch representations is improved, ensuring that the two modes learn cooperatively from each other. In addition, a uniform domain-aware contrast state template is designed for fine-grained visual language matching. For imagelevel and pixel-level anomaly detection, this method achieves better performance than non-prompt learning in zero-sample anomaly detection.

关键词： Learning systems Visualization Costs Accuracy Biological system modeling Prompt engineering Informatics Anomaly detection Optimization

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Tree Models Machine Learning to Identify Liquid Metal based Alloy Superconductor

arXiv

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arXiv 2025年

作者： Hua, Chen Liu, Jing Key Lab of Cryogenic Science and Technology Technical Institute of Physics and Chemistry Chinese Academy of Sciences Beijing100190 China School of Future Technology University of Chinese Academy of Sciences Beijing100049 China School of Biomedical Engineering Tsinghua University Beijing100084 China

Superconductors, which are crucial for modern advanced technologies due to their zero-resistance properties, are limited by low Tc and the difficulty of accurate prediction. This article made the initial endeavor to apply machine learning to predict the critical temperature (Tc) of liquid metal (LM) alloy superconductors. Leveraging the SuperCon dataset, which includes extensive superconductor property data, we developed a machine learning model to predict Tc. After addressing data issues through preprocessing, we compared multiple models and found that the Extra Trees model outperformed others with an R2 of 0.9519 and an RMSE of 6.2624 K. This model is subsequently used to predict Tc for LM alloys, revealing In0.5Sn0.5 as having the highest Tc at 7.01 K. Furthermore, we extended the prediction to 2,145 alloys binary and 45,670 ternary alloys across 66 metal elements and promising results were achieved. This work demonstrates the advantages of tree-based models in predicting Tc and would help accelerate the discovery of high-performance LM alloy superconductors in the coming time. © 2025, CC BY.

关键词： Superconducting transition temperature

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Real topological phonons in 3D carbon allotropes

arXiv

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arXiv 2024年

作者： Wang, Xiaotian Bai, Jingbo Wang, Jianhua Cheng, Zhenxiang Qian, Shifeng Wang, Wenhong Zhang, Gang Yu, Zhi-Ming Yao, Yugui School of Physical Science and Technology Southwest University Chongqing400715 China School of Material Science and Engineering Tiangong University Tianjin300387 China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314000 China Anhui Province Key Laboratory of Optoelectric Materials Science and Technology Department of Physics Anhui Normal University Anhui Wuhu241000 China University of Wollongong Wollongong2500 Australia Key Lab of Advanced Optoelectronic Quantum Architecture and Measurement MOE Beijing Key Lab of Nanophotonics & Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing100081 China

There has been a significant focus on real topological systems that enjoy space-time inversion symmetry (PT ) and lack spin-orbit coupling. While the theoretical classification of the real topology has been established, more progress has yet to be made in the materials realization of such real topological systems in three dimensions (3D). To address this crucial issue, by selecting the carbon-based material candidates as targets, we perform high-throughput computing to inspect the real topology in the phonon spectrums of the 3D carbon allotropes in the Samara Carbon Allotrope Database (SACADA). Among 1192 kinds of 3D carbon allotropes, we find 65 real topological systems with a phononic real Chern insulating (PRCI) state, 2 real topological systems with a phononic real nodal line (PRNL) state, 10 real topological systems with a phononic real Dirac point (PRDP) state, and 8 real topological systems with a phononic real triple-point pair (PRTPP) state. This extremely expands the material candidates with real topology, especially for the gapless topological phonons. We exhibit the PRCI, PRNL, PRTPP, and PRDP states of 27-SG. 166-pcu-h, 1081-SG. 194-42T13-CA, 52-SG. 141-gis, and 132-SG. 191-3,4T157 as illustrative examples, and explore the second-order boundary mode, i.e., phononic hinge mode. Among the four examples, the materials 1081-SG. 194-42T13-CA and 52-SG. 141-gis are so ideal that the PRNL and PRTPP in them are well separated from other bands, and the phononic hinge mode can be clearly observed. This study aims to broaden the understanding of 3D topological phonons, and emphasizes the potential of 3D carbon allotropes as a valuable framework for exploring the fascinating physics related to phononic hinge modes and phononic real topology. © 2024, CC BY.

关键词： Phonons

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