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Displaying 26 - 50 of 2405

Overcoming Roadblocks for Implementing AI/ML Methods for Materials Advancement

April 6, 2026
Author(s)
James Warren, Francesca Tavazza, Austin McDannald, Aaron Kusne, Howard Joress, David Hoogerheide, Brian DeCost, Kamal Choudhary, Debra Audus
The development of novel materials with tailored properties is a complex, multi-objective optimization problem that has long been a challenge in materials research. The integration of artificial intelligence (AI) and machine learning (ML) techniques has

Dynamic Embedding Representation for Graph Neural Networks to Enhance Materials Property Prediction with Limited Datasets

March 24, 2026
Author(s)
Vishu Gupta, Kamal Choudhary, Youjia Li, Muhammed Nur Talha Kili, Daniel Wines, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
Graph neural networks (GNNs) have proven effective in understanding and predicting diverse material properties, even when working with limited datasets. An important step in training GNN is to use an appropriate and informative graph embedding that can

Studies Of Water Films and Carbonation Via Neutron Scattering and Infrared Adsorption: In Situ Studies of Mg(OH)2 and Ca(OH)2

March 24, 2026
Author(s)
Hubert King, Ryan Murphy, Avery Baumann, Robert Dalgliesh, Dirk Honecker, Gregory Smith
Small-angle neutron scattering was used to investigate structural evolution during the carbonation of Ca(OH)₂ and Mg(OH)₂ under humidified CO₂, using both H₂O and D₂O vapor. For Ca(OH)₂, carbonation led to a progressive increase in both nano- and meso

System-Conditioned Reparameterization of the SCAN Functional for Accurate Bandgaps: From Analytical Constraints to Machine Learning

March 7, 2026
Author(s)
Viviana Faride Dovale Farelo, Pedram Tavadze, Miguel Marques, Srinjoy Das, Kamal Choudhary, Alejandro Bautista-Hernandez, Aldo Romero
This work investigates how reparametrizing the Strongly Constrained and Appropriately Normed (SCAN) exchange–correlation (XC) functional within density functional theory affects predictions of the electronic bandgap (Eg) for solids. A system dependent

Spin excitation continuum from degenerate states in the mixed ferro-antiferromagnetic exchange system CeMgAl11O19

March 6, 2026
Author(s)
Bin Gao, Tong Chen, Chunxaio Liu, Mason Klemm, Shu Zhang, Zhen Ma, Xianghan Xu, CHOONGJAE WON, Gregory McCandless, Karthik Rao, Naoki Murai, Seiko Ohira-Kawamura, Stephen Moxim, Jason Ryan, Xiaozhou Huang, Xiaoping Wang, Manh Duc Le, Emilia Morosan, Julia Chan, Sang-Wook Cheong, Oleg Tchernyshyov, Leon Balents, Pengcheng Dai
In magnetically ordered insulators, elementary quasiparticles manifest as spin waves - collective motions of localized magnetic moments that propagate through the lattice - observed via inelastic neutron scattering. In effective spin- 1/2 systems where

Comparison of Electroluminescence and Photoluminescence Imaging of Mixed-Cation Mixed-Halide Perovskite Solar Cells at Low Temperatures

February 16, 2026
Author(s)
Hurriyet Yuce Cakir, Haoran Chen, Isaac Ogunniranye, Susanna Thon, Yanfa Yan, Zhaoning Song, Behrang Hamadani
Mixed-cation mixed-halide perovskites have emerged as promising candidates for high-performance solar cells. This study investigates the temperature-dependent optoelectronic properties of Rb0.05Cs0.05MA0.05FA0.85Pb(I0.95Br0.05)3 perovskite solar cells

Surface-State-Driven Anomalous Hall Effect in Altermagnetic MnTe Films

February 9, 2026
Author(s)
Ling-Jie Zhou, Zhi J. Yan, Hongtao Rong, Yufei Zhao, Pu Xiao, Lok K. Lai, Zhiyuan Xi, Ke Wang, Tibendra Adhikari, Ganesh P. Tiwari, Zhong Lin, Pascal Manuel, Fabio Orlandi, Dmitry Khalyavin, Alexander Grutter, Chao-Xing Liu, Binghai Yan, Cui-Zu Chang
Altermagnets have recently emerged as a new class of magnetic materials that combine compensated magnetic order with spin-split electronic band structures. In this work, we employ molecular beam epitaxy (MBE) to grow MnTe thin films with controlled

Halogen Bonding Can Stabilize Permanent Porosity

February 3, 2026
Author(s)
Michael Moghadasnia, Hayden Evans, J. Sanchez Hernandez, Adria Hippely, Madilyn Holm, Gemma Ponce, Hannah Martin, Ronin Mannina, Brian Eckstein, Ryan Klein, Praveen Kumar, Charlotte Stern, Craig Brown, C. McGuirk
Halogen bonding has emerged as an intuitive and programmable handle for constructing ordered molecular solids. However, its ability to support permanent porosity has remained unresolved. Here, we report a self-complementary strategy that surpasses this

Predicting Properties from Near-Infrared Spectra with Machine Learning for Improved Polyolefin Differentiation

January 29, 2026
Author(s)
Shuaijun Li, Robert Ivancic, Bradley Sutliff, Derek Huang, Enrique Blazquez-Blazquez, Tyler Martin, Kalman Migler, Debra Audus, Sara Orski
The rapid increase in plastic waste necessitates innovative strategies to advance plastic recycling. As currently used, the industrial state-of-the-art sorting technology, near-infrared (NIR) spectroscopy, cannot effectively differentiate polyolefins, the

Scanned Squid Microscope with High-speed Electrical Connectivity

January 26, 2026
Author(s)
Ian Haygood, Bochao Xu, John Biesecker, Michael Schneider
We report on a cryogen-free scanned SQUID microscope operating at 4 K, with the capability of up to 40 RF (40 GHz) connections to a device under test. The system utilizes planar gradiometric SQUID loops which are fully shield except for a pair of pickup

Evaluating Large Language Models for Inverse Semiconductor Design

January 16, 2026
Author(s)
MUHAMMED NUR TALHA KILIC, Daniel Wines, Kamal Choudhary, Vishu Gupta, Youjia Li, Sayak Chakrabarty, WEI-KENG LIAO, Alok Choudhary, Ankit Agrawal
Large Language Models (LLMs) with generative capabilities have garnered significant attention in various domains, including materials science. However, systematically evaluating their performance for structure generation tasks remains a major challenge. In

Topological Nodal Line and Weyl Magnons in the Non-Coplanar Antiferromagnet MnTe2

December 20, 2025
Author(s)
Angela Hight Walker, Thuc Mai, Kevin Garrity
Using a combination of band representation analysis, inelastic neutron scattering (INS), magneto-Raman spectroscopy measurements, and linear spin wave theory, we determine that the non-coplanar antiferromagnet MnTe2 hosts symmetry-protected topological

Predicting Lattice Parameters from Atomic-Scale Images of Two Dimensional Materials Using Deep Learning

December 15, 2025
Author(s)
Sayak Chakrabarty, Kamal Choudhary, Youjia Li, Daniel Wines, Vishu Gupta, Muhammed Nur Talha Kilic, Alok Choudhary, Ankit Agrawal
Determining lattice parameters in two-dimensional (2D) materials is essential for materials characterization and discovery. In this work, we propose a deep-learning-driven pipeline that addresses the regression task of estimating the lattice constants (a)
Displaying 26 - 50 of 2405
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