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Sina Ghadi, Xiaobo Chen, Nicholas Tomasello, Nicholas Derimow, Srikanth Rangarajan, Guangwen Zhou, Scott Schiffres
Assessment of metal powders in powder bed additive manufacturing is crucial, as the quality of the powders significantly impacts the final printed parts. This study introduces a novel technique to characterize metal powders by analyzing changes in their
Rajesh Das, He Li, Hayden Evans, Zeyu Deng, Dan Zhao, Anthony K. Cheetham
Carbon capture, utilization, and sequestration (CCUS) have emerged as pivotal mitigation strategies in addressing climate change induced by greenhouse gas emissions. In this pursuit, our objective is to enhance the efficacy of adsorptive CO2 capture by
Crystal structure determination from powder diffraction patterns is a complex challenge in materials science, often requiring extensive expertise and computational resources. This study introduces DiffractGPT, a generative pre-trained transformer model
John Pettibone, Eric S. Windsor, Tae Joon Cho, Thomas Forbes, Ying Tung Kuo, Justin Gorham, Li Piin Sung, Song-Syun Jhang
Determining unknown secondary micro and nanoplastic (MNP) composition remains a persistent analytical challenge for field collected samples. The availability of material standards should accelerate method development for improved identification. Here
Andrew Naclerio, Peifu Cheng, Saban Hus, John Diulus, Marti Checa, Ivan Vlassiouk, William Fissel, Liam Collins, Matthew Coupin, Jamie Warner, Andrei Kolmakov, An-Ping Li, Piran Ravichandran Kidambi
Nanopores embedded within monolayer hexagonal boron nitride (h-BN) offer possibilities of creating atomically thin ceramic membranes with unique combinations of high permeance (atomic thinness), high selectivity (via molecular sieving), increased thermal
A new wide-ranging correlation for the thermal conductivity of nitrogen, based on the most recent ab initio dilute gas theoretical calculations, a simplified crossover critical enhancement contribution, and critically evaluated experimental data, is
Logan Lang, Eduardo Hernandez, Kamal Choudhary, Aldo Romero
Traditional data storage formats and databases often introduce complexities and inefficiencies that hinder rapid iteration and adaptability. To address these challenges, we introduce ParquetDB, a Python-based database framework that leverages the Parquet
Amine impregnated sorbents have been extensively studied for use in direct air capture (DAC) of CO2. In a dry environment, CO2 capture follows a carbamate formation mechanism, where capture capacity and amine efficiency are controlled by thickness of the
Qingyu Pan, Fan Zhang, Deepak Vikraman Pillai, Zilong Zhang, Yufeng Zheng, Lang Yuan, Monica Kapoor, John Carsley, Xiaoyuan Lou
In the present work, we studied the grain refinement by adding in situ reactants, pure titanium (Ti) or a combination of Ti and boron (B), and investigated the governing mechanism in Al-Mn-Fe-Si 3104 alloy made by laser direct energy deposition (DED)
Sarbajit Banerjee, Y. S. Meng, Andrew M. Minor, Minghao Zhang, Nestor J. Zaluzec, Maria K. Chan, Gerald Seidler, David W. McComb, Joshua Agar, Partha P. Mukherjee, Brent Melot, Karena Chapman, Beth S. Guiton, Robert F. Klie, Ian D. McCue, Paul M. Voyles, Ian Robertson, Ling Li, Miaofang Chi, Joel F. Destino, Arun Devaraj, Emmanuelle Marquis, Carlo U. Segre, Huinan H. Liu, Judith C. Yang, Kasra Momeni, Amit Misra, Niaz Abdolrahim, Julia E. Medvedeva, Wenjun Cai, Alp Sehirlioglu, Melike Dizbay-Onat, Apurva Mehta, Lori Graham-Brady, Benji Maryuama, Krishna Rajan, Jamie H. Warner, Mitra L. Taheri, Sergei V. Kalinin, B. Reeja-Jayan, Udo D. Schwarz, Sindee L. Simon, Craig Brown
In alignment with the Materials Genome Initiative and as the product of a workshop sponsored by the US National Science Foundation, we define a vision for materials laboratories of the future in alloys, amorphous materials, and composite materials; chart a
Raymond Simmonds, Sudhir Sahu, Trevyn Larson, Florent Lecocq, Tongyu Zhao, Anthony McFadden
The application of parallel plate capacitors composed of aluminum-contacted, crystalline silicon fins for use in superconducting circuits is explored by evaluating the performance of superconducting lumped element resonators and transmon qubits. High
Daniel Wheeler, Edwin Schwalbach, S H. Davis, P W. Voorhees, James Warren
The Vapor-Liquid-Solid (VLS) method is one of the most popular techniques for growing semiconducting nanowires, and the stability of the liquid droplet is an important factor controlling wire morphology, and, ultimately, functionality. Earlier theoretical
Anthony Kotula, Benjamin Dolata, Yoontae Kim, Sara Orski, Jonathan Seppala
Material extrusion is a common additive manufacturing process that subjects polymers to non-steady deformation and thermal processing to build a customized part. The mechanical properties of these parts are often worse than those of injection-molded
The "Additive Construction – The Path to Standardization II" workshop, hosted by the National Institute of Standards and Technology (NIST) and U.S. Army Engineer Research and Development Center (ERDC), brought together key players from the additive
A new fundamental equation of state expressed as a function of the Helmholtz energy is presented for 3,3,3-trifluoroprop-1-ene (R-1243zf). The equation is valid from the triple point temperature (122.35 K) to 430 K at pressures up to 35 MPa. The expected
We investigated the suitability of using readily available ("off-the-shelf"), as opposite to made-to-order, AISI 4340 steel for the production of NIST reference Charpy specimens of low- and high-energy level. This study was preceded by technical
Aqueous two-phase extraction (ATPE) is an effective and scalable liquid-phase processing method for purifying single species of single-wall carbon nanotubes (SWCNTs) from multiple species mixtures. Recent metrological developments have led to advances in
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
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
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