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arXiv 2025年

作者： da Gomes, Djardiel S. Felix, Isaac M. Radel, Willian F. Dias, Alexandre C. Ribeiro Junior, Luiz A. Pereira Junior, Marcelo L. State University of Campinas Gleb Wataghin Institute of Physics Department of Applied Physics Campinas São Paulo13083-859 Brazil University of Brasília Faculty UnB Planaltina Materials Science Postgraduate Program Federal District Brasília Brazil Center for Agri-food Science and Technology Federal University of Campina Grande Paraíba Pombal58840-000 Brazil University of Brasília Institute of Physics Physics Postgraduate Program Federal District Brasília70910900 Brazil Institute of Physics International Center of Physics University of Brasília Federal District Brasília70910-900 Brazil Institute of Physics University of Brasília Federal District Brasília70910-900 Brazil Computational Materials Laboratory University of Brasília Federal District Brasília70910900 Brazil University of Brasília College of Technology Department of Electrical Engineering Federal District Brasília70910-900 Brazil

Recently synthesized Porous 12-Atom-Wide Armchair Graphene Nanoribbons (12-AGNRs) [Nano Lett. 2024, 24, 10718-10723]exhibit tunable properties through periodic porosity, enabling precise control over their electronic, optical, thermal, and mechanical behavior. This work presents a comprehensive theoretical characterization of pristine and porous 12-AGNRs based on density functional theory (DFT) and molecular dynamics (MD) simulations. DFT calculations reveal substantial electronic modifications, including band gap widening and the emergence of localized states. Analyzed within the Bethe–Salpeter equation (BSE) framework, optical properties highlight strong excitonic effects and significant absorption shifts. Thermal transport simulations indicate a pronounced reduction in conductivity due to enhanced phonon scattering at nanopores. At the same time, MD-based mechanical analysis shows decreased stiffness and strength while maintaining structural integrity. Despite these modifications, porous 12-AGNRs remain mechanically and thermally stable. These findings establish porosity engineering as a powerful strategy for tailoring graphene nanoribbons’ functional properties, reinforcing their potential for nanoelectronic, optoelectronic, and thermal management *** Codes 00-xx © 2025, CC BY.

关键词： Nanoribbons

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Liquid-Liquid Transition in Water from First Principles

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Physical Review Letters 2022年第25期129卷 255702-255702页

作者： Thomas E. Gartner, III Pablo M. Piaggi Roberto Car Athanassios Z. Panagiotopoulos Pablo G. Debenedetti Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Physics Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA Princeton Institute for the Science and Technology of Materials Princeton University Princeton New Jersey 08544 USA Department of Chemical and Biological Engineering Princeton University Princeton New Jersey 08544 USA

A long-standing question in water research is the possibility that supercooled liquid water can undergo a liquid-liquid phase transition (LLT) into high- and low-density liquids. We used several complementary molecular simulation techniques to evaluate the possibility of an LLT in an ab initio neural network model of water trained on density functional theory calculations with the SCAN exchange correlation functional. We conclusively show the existence of a first-order LLT and an associated critical point in the SCAN description of water, representing the first definitive computational evidence for an LLT in water from first principles.

关键词： Classical statistical mechanics First order phase transitions First-principles calculations Liquid-liquid phase transition Phase transitions Thermodynamics Deep learning Density functional theory Molecular dynamics

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Deep learning inter-atomic potential for thermal and phonon behaviour of silicon carbide with quantum accuracy

arXiv

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arXiv 2021年

作者： Fu, Baoqin Sun, Yandong Zhang, Linfeng Wang, Han Xu, Ben Key Laboratory of Radiation Physics and Technology of the Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu610064 China Graduate School China Academy of Engineering Physics Beijing100193 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100088 China

Silicon carbide (SiC) is an essential material for next generation semiconductors and components for nuclear plants. It’s applications are strongly dependent on its thermal conductivity, which is highly sensitive to microstructures. Molecular dynamics (MD) simulation is the most used methods to address thermal transportation mechanisms in devices or microstructures of nano-meters. However, the implementation of MD is limited in SiC because of lacking accurate inter-atomic potentials. In this work, using the Deep Potential (DP) methodology, we developed two inter-atomic potentials (DP-*Corresponding author. IAPs) for SiC based on two adaptively generated datasets within the density functional approximations at the local density and the generalized gradient levels. These two DP-IAPs manifest their speed with quantum accuracy in lattice dynamics simulations as well as scattering rate analysis of phonon transportation. Combining with molecular dynamics simulations, the thermal transport and mechanical properties were systematically investigated. The presented methodology and the inter-atomic potentials pave the way for a systematic approach to model heat transport in SiC related devices using multiscale modelling. Copyright © 2021, The Authors. All rights reserved.

关键词： Silicon carbide

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Local Order Metrics for Two-Phase Media Across Length Scales

arXiv

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arXiv 2022年

作者： Torquato, Salvatore Skolnick, Murray Kim, Jaeuk Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry Princeton University PrincetonNJ08544 United States McKetta Department of Chemical Engineering University of Texas at Austin AustinTX78712 United States

The capacity to devise order metrics for microstructures of multiphase heterogeneous media is a highly challenging task, given the richness of the possible geometries and topologies of the phases that can arise. This investigation initiates a program to formulate order metrics to characterize the degree of order/disorder of the microstructures of two-phase media in d-dimensional Euclidean space Rd across length scales. In particular, we propose the use of the local volume-fraction variance σV2 (R) associated with a spherical window of radius R as an order metric. We determine σV2 (R) as a function of R for 22 different models across the first three space dimensions, including both hyperuniform and nonhyperuniform systems with varying degrees of short- and long-range order. We find that the local volume-fraction variance as well as asymptotic coefficients and integral measures derived from it provide reasonably robust and sensitive order metrics to categorize disordered and ordered two-phase media across all length scales. © 2022, CC BY-SA.

关键词： Volume fraction

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High-resolution spatio-temporal model for county-level COVID-19 activity in the U.S.

arXiv

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arXiv 2020年

作者： Zhu, Shixiang Bukharin, Alexander Xie, Liyan Santillana, Mauricio Yang, Shihao Xie, Yao School of Industrial and Systems Engineering Georgia Institute of Technology Harvard Medical School Computational Health Informatics Program Harvard University School of Engineering & Applied Sciences

We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases one-week ahead of the current time, at the county-level and weekly aggregated, in the United States. A notable feature of our spatio-temporal model is that it considers the (a) temporal auto- and pairwise correlation of the two local time series (confirmed cases and death of the COVID-19), (b) dynamics between locations (propagation between counties), and (c) covariates such as local within-community mobility and social demographic factors. The within-community mobility and demographic factors, such as total population and the proportion of the elderly, are included as important predictors since they are hypothesized to be important in determining the dynamics of COVID-19. To reduce the model’s high-dimensionality, we impose sparsity structures as constraints and emphasize the impact of the top ten metropolitan areas in the nation, which we refer (and treat within our models) as hubs in spreading the disease. Our retrospective out-of-sample county-level predictions were able to forecast the subsequently observed COVID-19 activity accurately. The proposed multi-variate predictive models were designed to be highly interpretable, with clear identification and quantification of the most important factors that determine the dynamics of COVID-19. Ongoing work involves incorporating more covariates, such as education and income, to improve prediction accuracy and model interpretability. Copyright © 2020, The Authors. All rights reserved.

关键词： Dynamics

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Fair Patient Model: Mitigating Bias in the Patient Representation Learned from the Electronic Health Records

arXiv

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arXiv 2023年

作者： Sivarajkumar, Sonish Huang, Yufei Wang, Yanshan Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA United States Department of Health Information Management University of Pittsburgh PittsburghPA United States Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Clinical and Translational Science Institute University of Pittsburgh PittsburghPA United States

Objective: To pre-train fair and unbiased patient representations from Electronic Health Records (EHRs) using a novel weighted loss function that reduces bias and improves fairness in deep representation learning models. Methods: We defined a new loss function, called weighted loss function, in the deep representation learning model to balance the importance of different groups of patients and features. We applied the proposed model, called Fair Patient Model (FPM), to a sample of 34,739 patients from the MIMIC-III dataset and learned patient representations for four clinical outcome prediction tasks. Results: FPM outperformed the baseline models in terms of three fairness metrics: demographic parity, equality of opportunity difference, and equalized odds ratio. FPM also achieved comparable predictive performance with the baselines, with an average accuracy of 0.7912. Feature analysis revealed that FPM captured more information from clinical features than the baselines. Conclusion: FPM is a novel method to pre-train fair and unbiased patient representations from EHR data using a weighted loss function. The learned representations can be used for various downstream tasks in healthcare and can be extended to other domains where bias and fairness are important. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

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A Design of Nested Photonic Crystal Fiber for OAM Mode Propagation 3rd

A Design of Nested Photonic Crystal Fiber for OAM Mode Pro...

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3rd International Conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Punia, Sushma Saharia, Ankur Ismail, Yaseera Petruccione, Francesco Bourdine, Anton V. Demidov, Vladimir V. Morozov, Oleg G. Yin, Juan Singh, Ghanshyam Tiwari, Manish Optoelectronics and Photonics Research Lab Department of Electronics and Communication Engineering Manipal University Jaipur Jaipur303007 India Department of Physics Stellenbosch University Stellenbosch7600 South Africa School of Data Science and Computational Thinking Stellenbosch University Stellenbosch7602 South Africa Stellenbosch South Africa Department of Communication Lines Povolzhskiy State University of Telecommunications and Informatics 23 Lev Tolstoy Street Samara Oblast443010 Russia JSC Scientific Production Association State Optical Institute Named after Vavilov S.I. 36/1 Babushkin Street St. Petersburg192171 Russia Department of Photonics and Communication Links Saint Petersburg State University of Telecommunications Named after M.A. Bonch-Bruevich 22 Bolshevikov Avenue St. Petersburg193232 Russia Department of Radiophotonics and Microwave Technologies Kazan National Research State University named after A.N. Tupolev-KAI 10 Karl Marx Street Kazan420111 Russia Division of Quantum Physics and Quantum Information University of Science and Technology of China 99 Xiupu Road Pudong District Shanghai200093 China Department of ECE Malaviya National Institute of Technology Jaipur Jaipur302017 India

ISBN: (纸本)9789819784639

This work is intended to present a nested Photonic Crystal Fiber (PCF) for OAM mode propagation. The proposed PCF comprises of a dense flint SF6 and a very light flint LLF1. The finite-element method (FEM) is used for the modal analysis to obtain propagating HE/EH modes. The proposed fiber has shown flat dispersion during the propagation of multiple orbital angular momentum (OAM) modes. Furthermore, the designed PCF’s nonlinearity (gamma) and confinement loss (CL) are calculated to prove the practical feasibility of the design. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Photonic crystal fibers

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Numerical Simulation of Spear Motion as Game Items

Numerical Simulation of Spear Motion as Game Items

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International Symposium on Nanoscience and Nanotechnology in Life sciences 2017, ISNNLS 2017

作者： Muhima, R.R. Mardi, S. Hariadi, M. Puspitasari, I. Informatics Engineering Department ITATS Arief Rachman Hakim 100 Surabaya Indonesia Electrical Engineering Department Sepuluh Nopember Institute of Technology Indonesia Information System Study Program Faculty of Science and Technology Universitas Airlangga Jl. Mulyorejo Surabaya60115 Indonesia

Game development in 3D is mostly done by characters, items and the environment. Game items such as character weapons modeled in 3D will be the attraction of a game. In this paper, spear motion as a game items is modeled in 3D. Nonlinear Equations Six Degrees of Freedom (6 DOF) are used for mathematical models of spear motion. The parameters studied in the motion model are: geometry, mass and aerodynamics. Spear aerodynamic parameters were analyzed using the Datcom method. Numerical simulation of mathematical models of spear motion with variations in the initial velocity of the throw and the direction of the throw. From the results of numerical simulation, the maximum range R = 131.7 m at the initial velocity V0 = 40 m/s, the direction of throw (angle θ0 = 35 deg, angle φ0 = 10 deg, ψ0 = 0 deg). And the maximum height Hmax = 12.18 m is achieved at the initial velocity V0 = 20 m/s, direction of throw (angle θ0 = 35 deg, angle φ0 = 40 deg, angle ψ0 = 0 deg). © 2020 Published under licence by IOP Publishing Ltd.

关键词： Aerodynamics

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Towards improved property prediction of two-dimensional (2D) materials using many-body Quantum Monte Carlo methods

arXiv

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arXiv 2024年

作者： Wines, Daniel Ahn, Jeonghwan Benali, Anouar Kent, Paul R.C. Krogel, Jaron T. Kwon, Yongkyung Mitas, Lubos Reboredo, Fernando A. Rubenstein, Brenda Saritas, Kayahan Shin, Hyeondeok Štich, Ivan Ataca, Can GaithersburgMD20899 United States Material Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Computational Science Division Argonne National Laboratory ArgonneIL60439 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics Konkuk University Seoul05029 Korea Republic of Department of Physics North Carolina State University RaleighNC27695-8202 United States Department of Chemistry Brown University ProvidenceRI02912 United States Department of Physics Brown University ProvidenceRI02912 United States Institute of Informatics Slovak Academy of Sciences Bratislava845 07 Slovakia Department of Physics University of Maryland Baltimore County BaltimoreMD21250 United States

The field of two-dimensional (2D) materials has grown dramatically in the last two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computation applications. These 2D structures, which are often exfoliated from layered van der Waals (vdW) materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. In order to overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as Diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. This approach has been applied to 2D systems of wide interest including graphene, phosphorene, MoS2, CrI3, VSe2, GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT. © 2024, CC BY.

关键词： Density functional theory

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Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar

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Smart Health 2024年 34卷

作者： Chokphukhiao, Chaturapron Pattaranit, Pattrawan Tun, Wonn Shweyi Thet Masa, Sakaowrat Leemananil, Rattikorn Natteerapong, Nuttaphorn Phetcharaburanin, Jutarop Boonlue, Sophon Sunat, Khamron Patramanon, Rina Information Technology International Program College of Computing Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Digital Innovation Faculty of Education Khon Kaen University Khon Kaen 40002 Thailand Integrative Biomedical Informatics and Computational Imaging Center I-BIC Faculty of Associated Medical Science Khon Kaen University Khon Kaen 40002 Thailand Department of System Biosciences and Computational Medicine Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Khon Kaen University National Phenome Institute Khon Kaen University Khon Kaen 40002 Thailand Department of Biochemistry Faculty of Science. Khon Kaen University Khon Kaen 40002 Thailand Department of Microbiology Faculty of Science Khon Kaen University Khon Kaen 40002 Thailand Department of Computer Science College of Computing Khon Kaen University 40002 Thailand

Introduction: The use of modern technologies has become crucial for enhancing people's awareness of health problems. By early health risk detection, there will be better treatment outcomes, the severity of illness will decrease, and costs for treatment will also reduce. Performing routine checkups could help patients feel less anxious about their health in the future. In this study, the innovation of “Digital Health Avatar” enables users to monitor physical changes, raise awareness of medical conditions, and encourage healthy behaviors by visualizing health status as a 3D figure. Methods: Health data were collected using medical devices like blood test strips, body composition meters, and automatic blood pressure monitors. API technology and cloud computing systems were used to process these collected data and produced a three-dimensional avatar that indicated the user's health status. User satisfaction survey on using the health avatar system was assessed through a survey of 61 participants. Results: Health avatar system successfully generate the data and display the measurement results on the health report page of the system. Users can easily check and record their physiological conditions through the avatar. Moreover, users showed satisfaction on the use of the health avatar system and its effectiveness in health check-ups in the survey. Conclusions: The ‘Digital Health Avatar’ has the potential to significantly promote individual well-being and health awareness. Its development will be improved by user feedback and continued study, ensuring it becomes an efficient tool for promoting healthier lifestyles. © 2024 The Authors

关键词： Digital health avatar Health sensors Healthcare Three-dimensional model

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