Article
Materials Science, Multidisciplinary
Mohammed Mendas, Stephane Benayoun, Mohamed Hadj Miloud, Ibrahim Zidane
Summary: This study extends the analysis of the indentation size effect (ISE) to lamellar cast irons, demonstrating that the tensile model and the concept of geometrically necessary dislocations (GNDs) can be used to predict the ISE of the pearlitic matrix within these materials. The summation of stresses associated with GNDs and statistically stored dislocations (SSDs) is shown to be more adequate in the prediction of ISE compared to considering only one work-hardening stress.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2021)
Article
Nanoscience & Nanotechnology
Nan Wang, Yongnan Chen, Gang Wu, Qinyang Zhao, Zhen Zhang, Lixia Zhu, Jinheng Luo
Summary: This study reveals the different contributions of geometrically necessary dislocation (GND) and statistically stored dislocation (SSD) to work hardening in dual-phase steel. By introducing high-density GND through pre-tensile loading-unloading-reloading (LUR) and high-density SSD through monotonic pre-tensile, it is found that the steel with high GND exhibits higher yield stress and stronger strain hardening ability compared to the high-SSD steel, even with almost the same total dislocation density.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2022)
Article
Engineering, Mechanical
Yilun Xu
Summary: A non-local method for establishing GND based on a non-local domain integral has been developed and validated, showing improved accuracy in predicting material fatigue life. The comprehensive study on non-local domain effect revealed the necessity of applying the non-local GND method, as it resembles experimental observations and enhances stress field predictions compared to local methods.
INTERNATIONAL JOURNAL OF PLASTICITY
(2021)
Article
Materials Science, Multidisciplinary
Wyatt A. Witzen, McLean P. Echlin, Marie-Agathe Charpagne, Tresa M. Pollock, Irene J. Beyerlein
Summary: This study investigates the intragranular distributions of geometrically necessary dislocations (GNDs) in a polycrystalline tantalum sample under shock compression loading. Using TriBeam tomography, a highly resolved 3D map of the microstructure was obtained, allowing for the examination of grain boundaries, orientations, and voids. By combining the 3D characterization, GND formulation, and a sample with approximately 6000 grains, correlations between GND density per grain and grain characteristics were analyzed. The results show that GND density increases closer to the spall plane and that grains containing voids have high GND density concentrations in the intragranular region surrounding the void.
Article
Computer Science, Interdisciplinary Applications
Cuong Le Thanh, Trong Nghia Nguyen, Truong Huu Vu, Samir Khatir, Magd Abdel Wahab
Summary: The static bending behavior of porous functionally graded micro-plates under geometrically nonlinear analysis is studied in this article. A small-scale nonlinear solution, higher-order plate theory, and isogeometric analysis are utilized to analyze the deflection of the plate, and the influence of parameters on the nonlinear behavior is investigated using numerical examples.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Civil
Minh-Chien Trinh, Hyungmin Jun
Summary: This paper analyzes the geometrically nonlinear behaviors of functionally graded composite shells under large displacements and large rotations. Instead of constructing conventional layer-wised models, equivalent single-layer composite shell elements based on general displacement fields are developed to model the inhomogeneity of composite materials. The mixed interpolation of tensorial components technique is used to eliminate membrane locking and shear locking phenomena. Geometrically nonlinear analyses are performed on different thin-walled composite structures, and the obtained results demonstrate good convergence characteristics and modeling capability of the developed quadrilateral composite shell elements.
THIN-WALLED STRUCTURES
(2023)
Article
Nanoscience & Nanotechnology
Jing-Hua Zheng, Catalin Pruncu, Kai Zhang, Kailun Zheng, Jun Jiang
Summary: This study provides direct and systematic experimental data by revealing the evolution of dislocation density and grain size of AA6082 alloy under different conditions, using Electron Back Scattering Diffraction (EBSD) technique. The results show continuously increased geometrically necessary dislocation densities during hot deformation, as well as the presence of dislocation channel structures and dynamic recrystallization. The study is the first to visualize high temperature and high strain rate induced dislocation distributions over a relatively large area, offering valuable insights for improving physically based material models.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2021)
Article
Materials Science, Multidisciplinary
Eralp Demir, Edward William Horton, Anna Kareer, David M. Collins, Mahmoud Mostafavi, David Knowles
Summary: Strain gradients are used to link microscale deformation phenomena to the mechanical response of polycrystalline materials. A unique method to compute orientation gradients has been developed, which showcases its effectiveness on an electron backscatter diffraction dataset. The proposed approach successfully eliminates sharp orientation gradients at grain boundaries.
Article
Nanoscience & Nanotechnology
Daniel L. Foley, Marat Latypov, Xingyuan Zhao, Jonathan Hestroffer, Irene J. Beyerlein, Leslie E. Lamberson, Mitra L. Taheri
Summary: It was found that crystal orientation has a significant impact on GND density, with the highest density in grains with a 101 101 compression texture; additionally, grain boundaries play a crucial role as strong dislocation sources in the evolution of GND density.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2022)
Article
Engineering, Civil
Zheng Lyu, Ming Ma
Summary: This work focuses on the nonlinear dynamic response of a functionally graded magneto-electro-elastic (MEE) nanobeam. The interaction between the imperfect nanobeam and its multi-physical stimulus is numerically solved via a differential quadrature method. Simulation results demonstrate the significance of the MEE coupling effect for designing smart and advanced devices in aerospace and industrial applications.
THIN-WALLED STRUCTURES
(2023)
Article
Materials Science, Multidisciplinary
Himanshu Joshi, Junyan He, Nikhil Chandra Admal
Summary: Grain boundary processes such as shear coupling and sliding are consequences of plastic distortion during grain boundary motion. This study introduces the concept of disconnections as the primary carriers of grain boundary plasticity, and develops a diffuse-interface finite deformation theory for grain boundary plasticity based on the notion of geometrically necessary disconnections. The proposed model can accurately describe phenomena such as state-dependent shear coupling, mode switching, grain boundary sliding, and grain rotation.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2022)
Article
Mechanics
Seyed Sajad Mirjavadi, Masoud Forsat, Mohammad Reza Barati, A. M. S. Hamouda
Summary: This study investigates the nonlinear free vibrations of porous functionally graded annular spherical shell segments and highlights the factors affecting the vibration characteristics.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2022)
Article
Engineering, Mechanical
Maoyuan Jiang, Zhengxuan Fan, Serge Kruch, Benoit Devincre
Summary: This study investigates the grain size effect in FCC polycrystalline plasticity using a multiscale modeling approach combining discrete dislocation dynamics (DDD) and crystal plasticity finite element method (CPFEM). The developed model quantitatively reproduces the deformation curves of FCC polycrystals and shows significant potential for further applications.
INTERNATIONAL JOURNAL OF PLASTICITY
(2022)
Article
Materials Science, Multidisciplinary
Landon T. Hansen, Jay D. Carroll, Eric R. Homer, Robert H. Wagoner, Guowei Zhou, David T. Fullwood
Summary: This study examines the distribution of geometrically necessary dislocations (GNDs) in pure tantalum under simple tension using high-resolution electron backscatter diffraction. The correlations between GND density and grain boundary character, as well as triple junction character, are investigated. A novel application of two-point statistics is used to quantify and visualize the statistical geometric relationships between these entities. The mapping and assessment of the local net Burgers vectors across the sample are also conducted using a recently developed method. The quantification of near boundary gradient zones is compared using different approaches to characterize GND distribution.
MICROSCOPY AND MICROANALYSIS
(2023)
Article
Nanoscience & Nanotechnology
Qingge Xie, Zhi Li, Hongchua Ma, Shuang Liu, Xingwei Liu, Jinxu Liu, Jurij J. Sidor
Summary: Studying the hardening variation inside and outside of Geometrically Necessary Bands (GNBs) helps understand their formation to accommodate deformation heterogeneity. The slip activities induced by prismatic and basal slips were verified using a crystal plasticity model and electron backscatter diffraction microstructures. Abundance of GNBs was observed, and the hardening/softening effect in GNBs is compensated by softening/hardening behavior near GNBs. The high and low GNDD regions share the same shape and peak positions in frequency-strength profiles, confirming the correlation between high GNDDs and low GNDDs.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2023)
Article
Materials Science, Ceramics
Ali Bagheri, Ali Nazari, Jay G. Sanjayan
CERAMICS INTERNATIONAL
(2018)
Article
Materials Science, Ceramics
Ahmed Graytee, Jay G. Sanjayan, Ali Nazari
CERAMICS INTERNATIONAL
(2018)
Article
Construction & Building Technology
Sarah Al-Qutaifi, Ali Nazari, Ali Bagheri
CONSTRUCTION AND BUILDING MATERIALS
(2018)
Article
Construction & Building Technology
A. Mohammed, J. G. Sanjayan, A. Nazari, N. T. K. Al-Saadi
CONSTRUCTION AND BUILDING MATERIALS
(2018)
Article
Green & Sustainable Science & Technology
Ali Bagheri, Ali Nazari, Ailar Hajimohammadi, Jay G. Sanjayan, Pathmanathan Rajeev, Mostafa Nikzad, Tuan Ngo, Priyan Mendis
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Construction & Building Technology
Hsiao Yun Leong, Dominic Ek Leong Ong, Jay G. Sanjayan, Ali Nazari, Sze Miang Kueh
JOURNAL OF MATERIALS IN CIVIL ENGINEERING
(2018)
Article
Construction & Building Technology
Hsiao Yun Leong, Dominic Ek Leong Ong, Jay G. Sanjayan, Ali Nazari
JOURNAL OF MATERIALS IN CIVIL ENGINEERING
(2018)
Article
Materials Science, Ceramics
Ali Bagheri, Ali Nazari, Jay G. Sanjayan, Wenhui Duan
CERAMICS INTERNATIONAL
(2018)
Article
Construction & Building Technology
Ali Nazari, Ali Bagheri, Jay G. Sanjayan, Melissa Dao, Chathumini Mallawa, Peita Zannis, Samuel Zumbo
CONSTRUCTION AND BUILDING MATERIALS
(2019)
Article
Chemistry, Physical
Behzad Nematollahi, Praful Vijay, Jay Sanjayan, Ali Nazari, Ming Xia, Venkatesh Naidu Nerella, Viktor Mechtcherine
Article
Materials Science, Multidisciplinary
Shin Hau Bong, Behzad Nematollahi, Ming Xia, Ali Nazari, Jay Sanjayan
Proceedings Paper
Construction & Building Technology
Shin Hau Bong, Behzad Nematollahi, Ali Nazari, Ming Xia, Jay G. Sanjayan
FIRST RILEM INTERNATIONAL CONFERENCE ON CONCRETE AND DIGITAL FABRICATION - DIGITAL CONCRETE 2018
(2019)
Article
Construction & Building Technology
Ali Bagheri, Ali Nazari, Jay G. Sanjayan, Pathmanathan Rajeev
CONSTRUCTION AND BUILDING MATERIALS
(2017)
Article
Construction & Building Technology
Pshtiwan Shakor, Jay Sanjayan, Ali Nazari, Shami Nejadi
CONSTRUCTION AND BUILDING MATERIALS
(2017)
Article
Construction & Building Technology
Graciela Lopez Alvarez, Ali Nazari, Ali Bagheri, Jay G. Sanjayan, Christo De lange
CONSTRUCTION AND BUILDING MATERIALS
(2017)
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)
