Article
Materials Science, Multidisciplinary
Yongmin Kim, Byeong-Joo Lee
Summary: Interatomic potentials for binary and ternary systems have been developed using the 2NN MEAM formalism, which can accurately describe various material properties and be used for atomistic simulations and exploring new tin-based alloy anode materials for sodium ion batteries.
COMPUTATIONAL MATERIALS SCIENCE
(2022)
Article
Chemistry, Physical
Joonho Ji, Byeong-Joo Lee
Summary: In this paper, a Li-Ni-O interatomic potential is developed to analyze and gain insight into cathode materials for Li-ion batteries. The potential is validated by reproducing fundamental properties and lithium diffusion characteristics in good agreement with experiments and first-principles calculations. It can be easily extended to other related systems and has significant application value in the Li-ion battery field.
JOURNAL OF POWER SOURCES
(2022)
Article
Chemistry, Physical
Yongmin Kim, Byeong-Joo Lee
Summary: To improve the cycle performance of Sn anodes, alloying metal elements such as Cu, Mn, and Ni are studied. Atomistic simulations reveal that Cu is the best alloying element in terms of reducing volume expansion and improving Na diffusion rate in Sn base alloy anode materials.
JOURNAL OF POWER SOURCES
(2023)
Article
Materials Science, Multidisciplinary
Henan Zhou, Doyl E. Dickel, Michael Baskes, Sungkwang Mun, Mohsen Asle Zaeem
Summary: A semi-empirical interatomic potential for bismuth based on the modified embedded-atom method (MEAM) has been developed, accurately reproducing physical properties and showing good agreement with experimental data and density functional theory calculations. This potential is useful for studying material and mechanical behaviors of pure bismuth under different conditions and lays the groundwork for developing potentials for bismuth alloys or compounds.
MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING
(2021)
Article
Materials Science, Multidisciplinary
Weiping Dong, Xinying Liu, Yikai Wang, Chengyu He, Mengjia Li, Mingyi Zhang
Summary: This paper presents a new phase field method to calculate the interaction potential between the first and second neighbor atoms of the D022 structure Ni3V phase in the Ni0.75AlxV0.25_x alloy. It also analyzes the change trend of interaction potential between the two neighbor atoms of the D022 structure with temperature and concentration. The feasibility of using the phase field method in understanding the microscale behavior of the Ni0.75AlxV0.25_x alloy is studied.
MATERIALS TODAY COMMUNICATIONS
(2023)
Article
Chemistry, Physical
Joonho Ji, Byeong-Joo Lee
Summary: In this paper, a new interatomic potential is developed for the Li-Ni-Mn-Co-O quinary system. The study shows that Li/Ni intermixing has a significant impact on the properties of Ni-rich cathode materials and controlling the intermixing is crucial.
JOURNAL OF POWER SOURCES
(2023)
Article
Materials Science, Multidisciplinary
Murray S. Daw, Michael Chandross
Summary: We propose a simple parametric form for interatomic potentials of the Embedded Atom Method (EAM-X) for pure FCC metals and investigate the relationship between basic properties and input parameters. Instead of fitting a set of functions to experimental data or density functional theory calculations, we adopt an inside-out approach to understand how complex properties depend on the EAM-X parameters. This method enables the identification of desired parameter regions and the matching of those parameters to real elements.
Article
Materials Science, Multidisciplinary
Murray S. Daw, Michael Chandross
Summary: We extend the parametric form of Embedded Atom Method interatomic potentials for FCC metals to treat alloys and study the dependence of alloy properties on model parameters. We introduce the concept of spread alloys, where constituent elements are defined as perturbations from an average FCC metal, and show that the model can describe the clustering and ordering tendencies of metal alloys. We prove a general theorem that alloy properties in random equimolar alloys differ from a simple rule of mixtures only based on the standard deviation among constituent parameters, independent of the number of constituents.
Article
Materials Science, Multidisciplinary
Mario Muralles, Joo Tien Oh, Zhong Chen
Summary: In this study, interatomic potentials for binary systems were developed using the second nearest-neighbor modified embedded-atom method (2NN MEAM) formalism. These potentials accurately reproduce essential physical properties and can be used to study multicomponent alloys and high entropy alloys, deepening our understanding of their unique properties at the atomic scale.
COMPUTATIONAL MATERIALS SCIENCE
(2023)
Article
Materials Science, Multidisciplinary
Jaemin Wang, Byeong-Joo Lee
Summary: Interatomic potentials for V-M binary systems were developed using the 2NN MEAM formalism, reproducing a wide range of material properties in agreement with experimental data or first-principles calculations. This allows for studying hydrogen permeability in vanadium alloys and potential development of ternary system potentials containing vanadium.
COMPUTATIONAL MATERIALS SCIENCE
(2021)
Article
Materials Science, Multidisciplinary
Miao He, Eaman T. Karim, Maxim Shugaev, Leonid Zhigilei
Summary: Molecular dynamics simulations were used to investigate the generation of vacancies at a crystal-liquid interface under conditions of undercooling for bcc Cr and fcc Ni metals. The results show that the vacancy concentrations produced can exceed equilibrium values by orders of magnitude. Different trends in vacancy concentration with temperature for Ni and Cr are related to the temperature dependences of the crystallization front velocity predicted for the two metals.
Article
Engineering, Environmental
Chen Li, Min Yuan, Yang Liu, Haikuo Lan, Yuting Chen, Zhenjiang Li, Kang Liu, Lei Wang
Summary: In this study, a unique method for manufacturing a defect-rich Fe single-atom catalyst loaded on a carbon nanosheets carrier was proposed. The catalyst showed exceptional activity and electron/proton transfer ability in the oxygen reduction reaction. It also exhibited excellent performance in liquid zinc-air batteries and flexible solid-state batteries.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Chemistry, Physical
Ming Liang, Lishi Ma, Bochao Chen, Enzuo Liu, Chunsheng Shi, Chunnian He, Naiqin Zhao
Summary: In this work, 2D-MoTe2@3DPCN structure was successfully constructed for SIB anode via a NaCl-assisted strategy. The unique architecture facilitates both ions and electrons transportation, prevents material aggregation and volume change. As a result, it exhibits high discharge specific capacity, excellent rate capability and outstanding long cycle life as SIB anode.
ENERGY STORAGE MATERIALS
(2022)
Article
Materials Science, Multidisciplinary
Jiaqi Li, Chen Peng, Jingkun Wang, Jie Li, Hongliang Zhang
Summary: Hard carbons were investigated for their structure and transformation during annealing using annealing-MD simulations and Arrhenius framework. Sodium behavior in hard carbon anodes with different nanostructures was also studied using ReaxFF-MD. The study revealed that hard carbon exhibited the highest ion diffusion rates and minimum volume swelling at low heat treatment temperature.
DIAMOND AND RELATED MATERIALS
(2022)
Article
Engineering, Electrical & Electronic
Guokai Chen, Xiye Guo, Kai Liu, Xiaoyu Li, Jun Yang
Summary: This paper introduces a restricted weighted k-nearest neighbor algorithm (RWKNN) specifically designed for indoor environments. By considering indoor moving constraints and introducing a confidence number, it mitigates the limitations of the traditional WKNN positioning method. Through simulation, field experiments, and verification, RWKNN demonstrates superior robustness and accuracy.
IEEE SENSORS JOURNAL
(2022)
Correction
Materials Science, Multidisciplinary
A. D. Boccardo, M. Tong, S. B. Leen, D. Tourret, J. Segurado
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Tao Li, Qing Hou, Jie-chao Cui, Jia-hui Yang, Ben Xu, Min Li, Jun Wang, Bao-qin Fu
Summary: This study investigates the thermal and defect properties of AlN using molecular dynamics simulation, and proposes a new method for selecting interatomic potentials, developing a new model. The developed model demonstrates high computational accuracy, providing an important tool for modeling thermal transport and defect evolution in AlN-based devices.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Shin-Pon Ju, Chao-Chuan Huang, Hsing-Yin Chen
Summary: Amorphous boron nitride (a-BN) is a promising ultralow-dielectric-constant material for interconnect isolation in integrated circuits. This study establishes a deep learning potential (DLP) for different forms of boron nitride and uses molecular dynamics simulations to investigate the mechanical behaviors of a-BN. The results reveal the structure-property relationships of a-BN, providing useful insights for integrating it in device applications.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
M. Salman, S. Schmauder
Summary: Shape memory polymer foams (SMPFs) are lightweight cellular materials that can recover their undeformed shape through external stimulation. Reinforcing the material with nano-clay filler improves its physical properties. Multiscale modeling techniques can be used to study the thermomechanical response of SMPFs and show good agreement with experimental results.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Laura Gueci, Francesco Ferrante, Marco Bertini, Chiara Nania, Dario Duca
Summary: This study investigates the acidity of 30 Bronsted sites in the beta-zeolite framework and compares three computational methods. The results show a wide range of deprotonation energy values, and the proposed best method provides accurate calculations.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
K. A. Lopes Lima, L. A. Ribeiro Junior
Summary: Advancements in nanomaterial synthesis and characterization have led to the discovery of new carbon allotropes, including biphenylene network (BPN). The study finds that BPN lattices with a single-atom vacancy exhibit higher CO2 adsorption energies than pristine BPN. Unlike other 2D carbon allotropes, BPN does not exhibit precise CO2 sensing and selectivity by altering its band structure configuration.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Jay Kumar Sharma, Arpita Dhamija, Anand Pal, Jagdish Kumar
Summary: In this study, the quaternary Heusler alloys LiAEFeSb were investigated for their crystal structure, electronic properties, and magnetic behavior. Density functional theory calculations revealed that LiSrFeSb and LiBaFeSb exhibit half-metallic band structure and 100% spin polarization, making them excellent choices for spintronic applications.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Roman A. Eremin, Innokentiy S. Humonen, Alexey A. Kazakov, Vladimir D. Lazarev, Anatoly P. Pushkarev, Semen A. Budennyy
Summary: Computational modeling of disordered crystal structures is essential for studying composition-structure-property relations. In this work, the effects of Cd and Zn substitutions on the structural stability of CsPbI3 were investigated using DFT calculations and GNN models. The study achieved accurate energy predictions for structures with high substitution contents, and the impact of data subsampling on prediction quality was comprehensively studied. Transfer learning routines were also tested, providing new perspectives for data-driven research of disordered materials.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Zhixin Sun, Hang Dong, Yaohui Yin, Ai Wang, Zhen Fan, Guangyong Jin, Chao Xin
Summary: In this study, the crystal structure, electronic structure, and optical properties of KH2PO4: KDP crystals under different pressures were investigated using the generalized gradient approximate. It was found that high pressure caused a phase transition in KDP and greatly increased the band gap. The results suggest that high pressure enhances the compactness of KDP and improves the laser damage threshold.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Tingting Yu
Summary: This study presents atomistic simulations revealing that an increase in driving force may result in slower grain boundary movement and switches in the mode of grain boundary shear coupling migration. Shear coupling behavior is found to effectively alleviate stress and holds potential for stress relaxation and microstructure manipulation in materials.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Y. Zhang, X. Q. Deng, Q. Jing, Z. S. Zhang
Summary: The electronic properties of C2N/antimonene van der Waals heterostructure are investigated using density functional theory. The results show that by applying horizontal strain, vertical strain, electric field, and interlayer twist, the electronic structure can be adjusted. Additionally, the band alignment and energy states of the heterostructure can be significantly changed by applying vertical strain on the twisted structure. These findings are important for controlling the electronic properties of heterostructures.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Chad E. Junkermeier, Evan Larmand, Jean-Charles Morais, Jedediah Kobebel, Kat Lavarez, R. Martin Adra, Jirui Yang, Valeria Aparicio Diaz, Ricardo Paupitz, George Psofogiannakis
Summary: This study investigates the adsorption properties of carbon dioxide (CO2), methane (CH4), and dihydrogen (H2) in carbophenes functionalized with different groups. The results show that carbophenes can be promising adsorbents for these gases, with high adsorption energies and low desorption temperatures. The design and combination of functional groups can further enhance their adsorption performance.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Y. Borges, L. Huber, H. Zapolsky, R. Patte, G. Demange
Summary: Grain boundary structure is closely related to solute atom segregation, and machine learning can predict the segregation energy density. The study provides a fresh perspective on the relationship between grain boundary structure and segregation properties.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
M. R. Jones, L. T. W. Fey, I. J. Beyerlein
Summary: In this work, a three-dimensional ab-initio informed phase-field-dislocation dynamics model combined with Langevin dynamics is used to investigate glide mechanisms of edge and screw dislocations in Nb at finite temperatures. It is found that the screw dislocation changes its mode of glide at two distinct temperatures, which coincides with the thermal insensitivity and athermal behavior of Nb yield strengths.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Joshua A. Vita, Dallas R. Trinkle
Summary: This study introduces a new machine learning model framework that combines the simplicity of spline-based potentials with the flexibility of neural network architectures. The simplified version of the neural network potential can efficiently describe complex datasets and explore the boundary between classical and machine learning models. Using spline filters for encoding atomic environments results in interpretable embedding layers that can incorporate expected physical behaviors and improve interpretability through neural network modifications.
COMPUTATIONAL MATERIALS SCIENCE
(2024)