Article
Engineering, Multidisciplinary
Yongqiang Ling, Xiaoli Zhu, Lei Song, Xiaohui Yang
Summary: The incorporation of multi-walled carbon nanotubes (MWCNT) into phosphogypsum has been found to have multifaceted effects on its properties. The addition of MWCNT significantly shortens the setting time, enhances the strength and water resistance of phosphogypsum, and promotes its hydration process.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Chemistry, Physical
Bin-Hao Chen
Summary: The adsorption properties of hydrogen molecules in twisted double-walled carbon nanotubes were investigated, and it was found that the amount of stored hydrogen and the kinetic diameter of hydrogen molecules are influenced by the degree of twisting. Additionally, the adsorption heat was found to depend on the extent of twisting.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Materials Science, Ceramics
Mehena Oualit, Amar Irekti
Summary: This experimental study aims to develop metakaolin-based geopolymer mortars reinforced with multiwalled carbon nanotubes (MWCNTs). The results indicate that the incorporation of multi-walled carbon nanotubes improves the compressive strength of the geopolymer matrices.
CERAMICS INTERNATIONAL
(2022)
Article
Materials Science, Multidisciplinary
Nelli G. Muradyan, Harutyun Gyulasaryan, Avetik A. Arzumanyan, Maria M. Badalyan, Marine A. Kalantaryan, Yeghiazar V. Vardanyan, David Laroze, Aram Manukyan, Manuk G. Barseghyan
Summary: In this study, multi-walled carbon nanotubes (MWCNTs) were synthesized using a modified solid-phase pyrolysis method, and effectively dispersed using ultrasonic energy. The optimal concentration for enhancing the compressive strength of cement mortars was found to be 0.01% with a sonication time of 40 minutes.
Article
Chemistry, Multidisciplinary
Min-Ken Li, Adnan Riaz, Martina Wederhake, Karin Fink, Avishek Saha, Simone Dehm, Xiaowei He, Friedrich Schoeppler, Manfred M. Kappes, Han Htoon, Valentin N. Popov, Stephen K. Doom, Tobias Hertel, Frank Hennrich, Ralph Krupke
Summary: This work demonstrates that electroluminescence excitation is selective towards neutral defect-state configurations with the lowest transition energy, which, combined with gate control, leads to high spectral purity.
Article
Construction & Building Technology
Hamzeh Marwan Allujami, Muyideen Abdulkareem, Taha M. Jassam, Ramez A. Al-Mansob, Azmi Ibrahim, Jing Lin Ng, Hok Chai Yam
Summary: The objective of this research is to improve the performance of recycled aggregate concrete (RAC) by adding multiwalled carbon nanotubes (MWCNT), particularly in terms of compressive strength and impact resistance. The experimental results show that incorporating MWCNT can significantly enhance the properties of RAC.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Timofei Eremin, Valentina Eremina, Yuri Svirko, Petr Obraztsov
Summary: Covalent functionalization of single-walled carbon nanotubes (SWCNTs) can greatly enhance their photoluminescent (PL) brightness, making them suitable for infrared light emitters.
Article
Chemistry, Physical
Elena Cerro-Prada, Rosalia Pacheco-Torres, Fernando Varela
Summary: The study shows that adding 0.02 wt.% MWCNTs to cement mortar can increase compressive and flexural strength at 90 days curing time. Mortars with 0.01 and 0.015 wt.% MWCNT loading have a decrease in resistivity at both 28 and 90 days curing time.
Article
Materials Science, Multidisciplinary
Daniela A. Damasceno, Caetano R. Miranda
Summary: Carbon nanotubes are widely used in developing new technologies, with their mechanical properties influenced by chirality and defects. Tensile strength of SWCNTs is significantly dependent on defect configurations, and certain combinations of defects can control fracture patterns, contributing to the design of innovative nanostructures with tailored properties.
PHILOSOPHICAL MAGAZINE
(2022)
Article
Chemistry, Multidisciplinary
Alejandro Lopez-Moreno, Susana Ibanez, Sara Moreno-Da Silva, Luisa Ruiz-Gonzalez, Natalia Martin Sabanes, Eduardo Peris, Emilio M. Perez
Summary: Mechanically interlocked derivatives of carbon nanotubes (MINTs) are interesting and stable nanotube products. This study explores the encapsulation of single-walled carbon nanotubes within a palladium-based metallosquare, revealing the sensitivity of MINT formation to structural variations of the metallo-assemblies. The study also demonstrates the potential application expansion of MINTs through supramolecular coordination complexes.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
Article
Chemistry, Multidisciplinary
Zhiwu Bie, Yajie Deng, Xuefeng Liu, Jiaqi Zhu, Jixiao Tao, Xian Shi, Xiaoqiao He
Summary: This study investigates the effects of defects on the tensile mechanical properties of coiled carbon nanotubes (CCNTs) using molecular dynamics (MD) simulations. The results show that defects in CCNTs decrease the spring constant and elastic limit, but improve the ductility and energy absorbing ability. The stiffness, elastic limit, ductility, and deformation pattern of defected CCNTs can be adjusted by changing the position or type of defects. This study provides important insights into the mechanical properties of CCNTs with defects and is useful for designing CCNTs with specific properties.
Article
Materials Science, Multidisciplinary
P. Kaur, J. Singh
Summary: This study proposes the use of alternative materials with high levels of supplementary cementitious materials and geopolymer composites to develop the construction industry. The properties of metakaolin-based geopolymer mortar, along with corn cob ash (CCA) and multi-walled carbon nanotubes (MWCNTs), were characterized and tested. The experimental investigation showed that there was a significant increase in compressive strength of the geopolymer mortar when CCA and MWCNTs were combined at certain concentrations, but beyond that, there was a reduction in strength.
Article
Materials Science, Multidisciplinary
Ritu Verma, Neena Jaggi
Summary: This study investigates the effects of osmium and boron co-doping on hydrogen storage in carbon nanotubes using ab-initio calculations. The results show that osmium/boron co-doping enhances the hydrogen storage capacity, but an increase in boron atom concentration reduces the storage ability.
DIAMOND AND RELATED MATERIALS
(2022)
Article
Multidisciplinary Sciences
Julia Villalva, Aysegul Develioglu, Nicolas Montenegro-Pohlhammer, Rocio Sanchez-de-Armas, Arturo Gamonal, Eduardo Rial, Mar Garcia-Hernandez, Luisa Ruiz-Gonzalez, Jose Sanchez Costa, Carmen J. Calzado, Emilio M. Perez, Enrique Burzuri
Summary: Encapsulating robust Fe-based SCO molecules within the 1D cavities of single-walled carbon nanotubes (SWCNT) can endure encapsulation and positioning of individual heterostructures in nanoscale transistors, triggering a large conductance bistability and providing a backbone for readout and positioning of SCO molecules into nanodevices, as well as helping to tune their magnetic properties at the nanoscale. Spin-crossover molecules are ideal sensors due to their ability to change spin-state under various stimuli, but typically face limitations such as insulating and unstable properties, which can be overcome through encapsulation inside carbon nanotubes.
NATURE COMMUNICATIONS
(2021)
Article
Environmental Sciences
Miaomiao Tan, Longfei Liu, Deyun Li, Chengliang Li
Summary: The transport behavior of multi-walled carbon nanotubes with different surface modifications in water-saturated sand columns was influenced by pH and ionic strength, with COOH-MWCNTs exhibiting the strongest mobility.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Chemistry, Physical
V. Vijayaraghavan, Jacob F. N. Dethan, A. Garg
MOLECULAR SIMULATION
(2018)
Article
Chemistry, Physical
Jacob F. N. Dethan, Varghese Swamy
MOLECULAR SIMULATION
(2020)
Review
Chemistry, Physical
Jacob F. N. Dethan, Varghese Swamy
Summary: The molecular dynamics simulation method is widely used to study the mechanical and thermal properties of nanomaterials. However, there is a lack of comprehensive review comparing the thermal and mechanical properties of carbon nanotubes (CNTs), boron nitride nanotubes (BNNTs), and their hybrid structures obtained using this method. This paper reviews the contradicting results on the mechanical and thermal properties of CNTs and BNNTs published in the literature. The study identifies a lack of discussion on the thermal and mechanical properties of BNNTs and the impact of encapsulated hydrogen. The authors hope that future research will address these contradictions and provide important insights for hydrogen storage and fuel cell applications.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Materials Science, Multidisciplinary
Jacob F. N. Dethan, Jingjie Yeo, M. Akbar Rhamdhani, Varghese Swamy
Summary: In this study, the thermal conductivities of boron nitride nanotubes (BNNTs) and carbon nanotubes (CNTs) as potential hydrogen storage materials were investigated using molecular dynamics simulations. The results show that different potentials have different predictions on the thermal transport, both qualitatively and quantitatively, but exhibit consistency in the interface thermal transport of CNT-BNNT compositions.
MATERIALS TODAY COMMUNICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Jacob F. N. Dethan
Summary: The thermal conductivity of hydrogenated h-BN nanosheets was investigated using molecular dynamics simulations. A newly parameterized reactive force field (ReaxFF) was used to accurately model the interactions between hydrogen and h-BN. It was found that hydrogenation reduces the thermal conductivity due to a change in the bonding structure. Additionally, both increased temperature and the presence of vacancy defects were found to further decrease the thermal conductivity. These findings provide insights for the design of hydrogen storage systems using h-BN nanosheets.
Article
Chemistry, Physical
Jacob F. N. Dethan
Summary: Hydrogenation significantly improves the mechanical properties of borophene, but has minimal effect on thermal conductivity. An increase in temperature reduces the Young's modulus and thermal conductivity of borophene. The presence of hydrogen stabilizes the mechanical properties of borophene, making it a potential alternative to hydrogen boride sheets for hydrogen storage applications.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Article
Physics, Multidisciplinary
V. Vijayaraghavan, J. F. N. Dethan, Liang Gao
SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY
(2019)
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)
