U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Materials

Search Publications

Search Title, Abstract, Conference, Citation, Keyword or Author
  • Published Date
Displaying 76 - 100 of 2328

Hybrid-LLM-GNN: Integrating Large Language Models and Graph Neural Networks for Enhanced Materials Property Prediction

December 18, 2024
Author(s)
Youjia Li, Vishu Gupta, Talha Killic, Kamal Choudhary, Daniel Wines, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
Graph-centric learning has attracted significant interest in material informatics. Accordingly, a family of graph-based machine learning models, primarily utilizing Graph Neural Networks (GNN), has been developed to provide accurate material properties

PVDF-based Backsheet Cracking: Mapping In Situ Phase Evolution by X-ray Scattering

December 15, 2024
Author(s)
Stephanie Moffitt, Sona Ulicna, Song-Syun Jhang, Po-Chang Pan, Michael Owen-Bellini, Peter Hacke, Michael Kempe, Jared Tracy, Kaushik Choudhury, Laura Schelhas, Xiaohong Gu
One of the most common polymers in commercial photovoltaic (PV) backsheets is polyvinylidene fluoride (PVDF). However, recent reports have shown the potential for PVDF-based backsheets to crack and fail prematurely. Previous work has suggested that polymer

An Electrically Conducting Metal-Organic Framework Having Two Orthogonal Transport Pathways

December 12, 2024
Author(s)
Shiyu Zhang, Weikang Zhang, Ashok Yadav, Md. Ansari, Jonathan Cromer, Jorge Moreno, Gavin McCarver, Wei Zhou, Sourav Saha
Owing to their diverse potential applications in electronics and energy technologies, electrically conducting metal–organic frameworks (EC-MOFs) have emerged as one of the most coveted functional materials of the twenty-first century. Among various MOF

Extracting Orientation and Distance-Dependent Interaction Potentials between Proteins in Solutions Using Small-Angle X-ray/Neutron Scattering

December 10, 2024
Author(s)
Yun Liu, Harold Hatch, Guangcui Yuan, Vincent Shen, Alexander Grishaev, Jainik Panchal, Marco Blanco
Nonspecific protein−protein interactions (PPIs) are key to understanding the behavior of proteins in solutions. However, experimentally measuring anisotropic PPIs as a function of orientation and distance has been challenging. Here, we propose to measure a

Surface photooxidation of polypropylene-based photovoltaic backsheets: A comprehensive spectroscopic investigation

December 8, 2024
Author(s)
Karissa Jensen, Ashlee Aiello, Stefan Mitterhofer, Chiara Barretta, Gernot Oreski, Christopher Stafford, Xiaohong Gu
The prospect of cost reduction, enhanced performance, and improved sustainability has been driving innovation in the development of new backsheet materials for photovoltaic (PV) modules in recent years. Among the materials of interest, polypropylene (PP)

Development and performance of a low-cost, solid-state, thermal neutron sensor with a 10B converter

December 5, 2024
Author(s)
Priscila Costa, Jamie Weaver, M Raele, Kevin Pritchard, Juscelino Leao, C Domienikan, Nicholas C. Maliszewskyj, F da Silva, W Pereira, Frederico Genezini
This study demonstrates the construction and operation of a portable, solid-state thermal neutron sensor that utilizes a photodiode coated with a thin layer of boron-10 (10B). The boron layer was created using pulsed laser deposition and analyzed through

An Adaptive Metal-Organic Framework Discriminates Xylene Isomers by Shape-Responsive Deformation

December 4, 2024
Author(s)
Jiaqi Li, Bin Sheng, Rundao Chen, Hui Wu, Wei Zhou, Fang Zheng, Baojian Liu, Qiwei Yang, Zhiguo Zhang, Yiwen Yang, Qilong Ren, Zongbi Bao
The separation of xylene isomers, especially para-xylene, is a crucial but challenging process in the chemical industry due to their similar molecular dimensions. Here, a flexible metal–organic framework, Ni(ina)2, (ina = isonicotinic acid) is employed to

Atomistic Origins of Conductance Switching in an e-Cu0.9V2O5 Neuromorphic Single Crystal Oscillator

December 4, 2024
Author(s)
Cherno Jaye, Conan Weiland, Daniel Fischer, John Ponis, Nicholas Jerla, George Agbeworvi, Saul Perez-Beltran, Nitin Kumar, Kenna Ashen, Jialu Li, Edrick Wang, Michelle A. Smeaton, Fatme Jardali, Sarbajeet Chakraborty, Patrick J. Shamberger, Katherine L. Jungjohann, Lu Ma, Jinghua Guo, G Sambandamurthy, Xiaofeng Qian, Sarbajit Banerjee
: Building artificial neurons and synapses is key to achieving the promise of energy efficiency and acceleration envisioned for brain-inspired information processing. Emulating the spiking behavior of biological neurons in physical materials requires

Small-Angle Scattering and Dark-Field Imaging for Validation of a New Neutron Far-Field Interferometer

December 1, 2024
Author(s)
Caitlyn M. Wolf, Peter Bajcsy, Wei-Ren Chen, Robert Dalgliesh, Michael Daugherty, Liliana de Campo, Fumiaki Funama, Lilin He, Michael Huber, David Jacobson, Paul A. Kienzle, Youngju Kim, Hubert King, Nikolai Klimov, Jacob LaManna, Fankang Li, Alexander Long, Ryan Murphy, Gergely Nagy, Sarah M. Robinson, Pushkar Sathe, Gregory N. Smith, Anna Sokolova, Sven Vogel, Erik Watkins, Yuxuan Zhang, Daniel Hussey, Kathleen Weigandt
The continued advancement of complex materials often requires a deeper understanding of the structure–function relationship across many length scales, which quickly becomes an arduous task when multiple measurements are required to characterize

Precipitation hardening of laser powder bed fusion Ti-6Al-4V

November 20, 2024
Author(s)
Nicholas Derimow, Jake Benzing, Jacob Garcia, Zachary Levin, Ping Lu, Newell Moser, Chad Beamer, Frank DelRio, Nikolas Hrabe
The laser powder bed fusion (PBF-L) additive manufacturing (AM) community has dedicated significant efforts into process optimization and control for defect-free Ti-6Al-4V. As defects become less of an issue for PBF-L Ti-6Al-4V, the processing-structure

Clarifying the Formation of Equiaxed Grains and Microstructural Refinement in the Additive Manufacturing of Binary Ti-Cu

November 14, 2024
Author(s)
Alec Saville, Adriana Eres-Castellanos, Andrew Kustas, Levi Van Bastian, Donald Susan, Dale Cillessen, Sven Vogel, Natalie Compton, Kester Clarke, Amy Clarke
Controlling microstructural evolution in metallic additive manufacturing (AM) is difficult, especially in producing refined as-built grains instead of coarse, directional grains. Traditional solutions involve adding inoculants to AM feedstocks, but

Neutron Vibrational Spectroscopic Study of the Acetonitrile:Acetylene (1:2) Cocrystal Relevant to Titan, Saturn's Moon

November 13, 2024
Author(s)
Morgan Kramer, Luke Daemen, Yongqiang Cheng, Rafael Balderas-Xicohtencatl, Anibal Ramirez-Cuesta, Craig Brown, Tomce Runcevski
Saturn's moon Titan features a surface composed of various organic solids with pronounced compositional and structural diversity. On top of the icy core, the surface experiences a temperature of ≈93 K and pressure of ≈1.45 atm. Under these conditions, most

Workshop Report on Autonomous Methodologies for Accelerating X-ray Measurements

November 5, 2024
Author(s)
Zachary Trautt, Austin McDannald, Brian DeCost, Howard Joress, A. Gilad Kusne, Francesca Tavazza, Tom Blanton
The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs

Broadband Characterization of Flexible Conductor-Dielectric Composites

November 4, 2024
Author(s)
Luckshitha Suriyasena Liyanage, Nathan Orloff, Nicholas Jungwirth, Sarah Evans, Christian Long, Angela Stelson, Jacob Pawlik, James Booth
Broadband measurements are important for characterizing a wide range of materials for communications applications at microwave and mm-wave frequencies. Here we report on broadband measurements of the effective permittivity of conductor-dielectric flexible

Prediction of Magnetic Properties in van der Waals Magnets using Graph Neural Networks

November 4, 2024
Author(s)
Kamal Choudhary, Peter Minch, Trevor David Rhone, Romakanta Bhattarai
We study two-dimensional (2D) magnetic materials using state-of-the-art machine learning models that use a graph-theory framework. We find that representing materials as graphs allows us to better learn structure-property relationships by leveraging both
Was this page helpful?