Article
Engineering, Multidisciplinary
Pengfei Zhang, Ming Yang, Danielle Zeng, Soheil Soghrati
Summary: A new microstructure reconstruction algorithm is introduced, which is fully integrated with a non-iterative meshing algorithm named CISAMR. This algorithm allows for synthesizing finite element models of chopped fiber composite microstructures with desired statistical descriptors.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Materials Science, Composites
Amira Hassouna, Slah Mzali, Farhat Zemzemi, Mohamed BenTkaya, Salah Mezlini
Summary: Drilling is a common machining process used for creating holes, and optimizing it is important for improving hole quality. This study used a numerical model to analyze the sensitivity of drilling parameters on thrust force, torque, and damage. The results from the numerical model were shown to agree well with experimental data. The study also found that choosing the appropriate rake angle can improve thrust force and the quality of the drilled workpiece.
JOURNAL OF THERMOPLASTIC COMPOSITE MATERIALS
(2023)
Article
Materials Science, Multidisciplinary
Federico De Bianchi, Sathiskumar Anusuya Ponnusami, Laura Silvestroni, Antonio Mattia Grande
Summary: The thermo-elastic properties of a novel class of ceramic composites were characterized and simulated, showing good agreement between experimental and modelling results at low fiber volume fractions but discrepancies at higher fractions due to significant evolution of microstructure at high processing temperatures. The study highlights the importance of accounting for microstructural changes in modelling thermomechanical properties of sintered ceramic composites.
MATERIALS TODAY COMMUNICATIONS
(2021)
Article
Materials Science, Multidisciplinary
Weiwei Wang, Han Wang, Shaohua Fei, Haijin Wang, Huiyue Dong, Yinglin Ke
Summary: This paper introduces a novel method for generating random fiber distributions of carbon fiber reinforced plastic with high volume fraction. An adaptive fiber shaking module is developed to overcome issues like unreasonable resin-rich zones, with a maximum fiber volume fraction reached at 67.43%. Finite element analysis shows a maximum absolute error of 7.354% in elastic properties when compared with experimental and simulation results.
MATERIALS & DESIGN
(2021)
Article
Mechanics
Vu Hoang Le, Sawekchai Tangaramvong, Jaroon Rungamornrat, Suchart Limkatanyu
Summary: The paper introduces an efficient method for determining the collapse load limit of inelastic structures by utilizing the smoothed recovery stress field. The approach combines the concept of elastic compensation algorithm within the ES-FE framework and recovery stress field enhancement to systematically adjust elastic moduli for critical elements. Various numerical examples demonstrate the accuracy and efficiency of the analysis framework in overcoming numerical challenges associated with stress singularity and volumetric locking phenomena.
Article
Chemistry, Physical
Phani Prasanthi, Sivaji Babu Kondapalli, Niranjan Kumar Sita Rama Morampudi, Venkata Venu Madhav Vallabhaneni, Kuldeep Kumar Saxena, Kahtan Adnan Mohammed, Emanoil Linul, Chander Prakash, Dharam Buddhi
Summary: A two-stage micromechanics technique was used to predict the elastic modulus and Poisson's ratio of unidirectional natural fiber reinforced composites. The study emphasized the importance of considering the real microstructure of natural fibers in the design of composites, particularly at higher volume fractions. The results showed the significance of hierarchical structures of fibers in determining the elastic properties of the composite materials.
Article
Materials Science, Multidisciplinary
Qigang Han, Jiahui Wang, Zhiwu Han, Junqiu Zhang, Shichao Niu, Menglu Chen, Lin Li, Shanshan Ju, Wenke Yang
Summary: An effective model and nacre-inspired continuous fiber-reinforced laminated composites were developed, showing that the elastic modulus of basalt-carbon hybrid-layer composites increased significantly with better isotropic performance. The results were in accordance with both numerical analysis and experimental tests.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2021)
Article
Materials Science, Composites
Lang Zeng, Yibo Li, Jinsong Liu
Summary: A new algorithm called Random Sequence Expansion (RSE)_stirring algorithm is proposed to generate Representative Volume Elements (RVEs) of random fiber distributions. The algorithm generates the initial fiber random distribution and captures the real fiber distribution by stirring the generated fibers and considering the short-range spacing interactions. The proposed algorithm is verified by analyzing the RVE model using statistical functions and comparing it with experimentally obtained real fiber distributions in a Completely Spatial Random (CSR) pattern. Additionally, the equivalent modulus of the composite is predicted using RVE and compared with results from other algorithms, showing strong similarity between experimental and predicted results.
JOURNAL OF THERMOPLASTIC COMPOSITE MATERIALS
(2023)
Article
Forestry
Ismail Ezzaraa, Nadir Ayrilmis, Mohamed Abouelmajd, Manja Kitek Kuzman, Ahmed Bahlaoui, Ismail Arroub, Jamaa Bengourram, Manuel Lagache, Soufiane Belhouideg
Summary: This study presents a numerical homogenization methodology to investigate the elastic properties of wood-polymer composites produced through fused deposition modeling (FDM). Various parameters such as wood volume fraction, aspect ratio, and internal porosity were investigated. The results were validated against analytical models and experimental data, showing a satisfactory agreement and confirming the effectiveness of the proposed approach.
Article
Engineering, Mechanical
Gopi Krishna Pamidi, Pavan Kumar Penumakala, A. V. S. Siva Prasad
Summary: The study demonstrates that external patch repair can effectively restore the load carrying capacity and longitudinal stiffness of a composite structure. The research is beneficial for maintenance engineers.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2021)
Article
Materials Science, Multidisciplinary
Tolga Topkaya, Yuan Gao, Philippe H. Geubelle
Summary: This study investigates the manufacturing of short-fiber-reinforced polymeric matrix composites based on frontal polymerization (FP) using numerical analysis and analytical predictions. The results show the dependence of the steady-state front velocity and inclination angle on the fiber orientation angle and volume fraction.
ACS APPLIED POLYMER MATERIALS
(2022)
Article
Materials Science, Composites
Ping Liu, Yucheng Zhong, Qing-Xiang Pei, Viacheslav Sorkin, Yong-Wei Zhang
Summary: Short fiber reinforced thermoplastic composites have gained significant interest for their low density, high strength, environmental resistance, and low cost. Optimizing internal structures to maximize mechanical properties is crucial. Increasing the weight fraction of linkage material can enhance the mechanical properties of SFRTPCs.
COMPOSITES SCIENCE AND TECHNOLOGY
(2022)
Article
Materials Science, Composites
Yuan Fu, Ping Zheng, Yi Jian Qiu, Jin Liu, You Liang Zhang, Lei Lu, Hui Guo
Summary: In this work, a dual-scale homogenization procedure was used to predict the response of effective elastic properties in chopped fiber reinforced epoxy matrix structures. Two methods, representative volume element (RVE) and unit cell (UC), were introduced and implemented at different scales. The average strain and stress in the UC three-dimensional structure were extracted using a post-processing scheme based on Gauss theorem in the space direction-sensitive Hotelling expansion (SDSHE) model. X-ray computed tomography was used to determine the orientation angle and probability distribution information of chopped fiber length. The proposed models showed excellent correlations with experiments, proving their effectiveness.
POLYMER COMPOSITES
(2022)
Article
Mechanics
Wei Xiang, Xin Li, Hua Ni, Bo Liu
Summary: This study performed stress predictions of fiber-reinforced ceramic matrix composites using a hierarchical quadrature element method. The sensitivity of the model to interface properties was investigated, and the process of determining optimal interface parameters for micromechanical analysis was elaborated. The accuracy of the model was validated by comparing with analytical results, and the microstructural behavior and mechanisms related to global failure were analyzed. This work establishes the foundations for a promising approach for fracture analysis of composites.
COMPOSITE STRUCTURES
(2022)
Article
Materials Science, Multidisciplinary
Adrian Hernandez-Perez, Hugo Fuentes-Gutierrez, Francisco Lopez-Santos, Elias R. Ledesma-Orozco, Francis Aviles
Summary: The accuracy of existing closed-form micromechanical models in predicting the elastic constants of unidirectional fiber reinforced composites is assessed using a finite element model as a reference for comparison. Detailed numerical analysis with formal statistical metrics allows for quantitative assessment and recommendations for the most suitable models for each material constant.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2021)
Article
Biophysics
Sagar Singh, Assimina A. Pelegri, David I. Shreiber
BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
(2015)
Article
Engineering, Biomedical
Xiaodong Zhao, Assimina A. Pelegri
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
(2016)
Article
Chemistry, Multidisciplinary
Hsiao-Fang Lee, Keivan Esfarjani, Zhizhong Dong, Gang Xiong, Assimina A. Pelegri, Stephen D. Tse
Article
Mechanics
Stephen S. Recchia, Max Tenorio, Suzanne Horner, James Q. Zheng, Assimina A. Pelegri
Article
Biophysics
Sagar Singh, Assimina A. Pelegri, David I. Shreiber
JOURNAL OF BIOMECHANICS
(2017)
Article
Polymer Science
Korhan Sahin, Jan Kenneth Clawson, James Singletary, Suzanne Horner, James Zheng, Assimina Pelegri, Ioannis Chasiotis
Article
Mechanics
Stephen Recchia, James Zheng, Assimina A. Pelegri
Article
Computer Science, Interdisciplinary Applications
Xiaodong Zhao, Assimina A. Pelegri
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
(2014)
Article
Biophysics
Xiaodong Zhao, Assimina A. Pelegri
JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME
(2014)
Article
Materials Science, Composites
Wensong Yang, Yi Pan, Assimina A. Pelegri
JOURNAL OF COMPOSITE MATERIALS
(2013)
Article
Materials Science, Multidisciplinary
W. S. Bao, S. A. Meguid, Z. H. Zhu, Y. Pan, G. J. Weng
MECHANICS OF MATERIALS
(2012)
Article
Mechanics
Prashanth Turla, Hinal Patel, Assimina A. Pelegri
Article
Nanoscience & Nanotechnology
Tongfen Liang, Xiyue Zou, Ramendra Kishor Pal, Jingjin Xie, Maame Konadu Assasie-Gyimah, Jiaqi Liu, Weijian Guo, Chuyang Chen, Max Tenorio, Daniel Sullivan, Anna Root, Paul Stansel, Anne Q. McKeown, George J. Weng, William W. Sampson, Assimina A. Pelegri, Aaron D. Mazzeo
ACS APPLIED MATERIALS & INTERFACES
(2020)
Article
Mechanics
Stephen Recchia, James Q. Zheng, Suzanne Horner, Assimina A. Pelegri
Proceedings Paper
Engineering, Mechanical
Max Tenorio, Assimina A. Pelegri
INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION - 2012, VOL 8
(2012)
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)
