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Materials

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Displaying 576 - 600 of 2343

Computational scanning tunneling microscope image database

December 5, 2021
Author(s)
Kamal Choudhary, Kevin Garrity, Charles Camp, Sergei Kalinin, Rama Vasudevan, Maxim Ziatdinov, Francesca Tavazza
We introduce the systematic database of scanning tunneling microscope (STM) images obtained using density functional theory (DFT) for two-dimensional (2D) materials, calculated using the Tersoff-Hamann method. It currently contains data for 716 exfoliable

How Austenitic is a Martensitic Steel Produced by Laser Powder Bed Fusion? A Cautionary Tale

December 2, 2021
Author(s)
Fan Zhang, Mark R. Stoudt, Souzan Hammadi, Carelyn E. Campbell, Eric A. Lass, Maureen E. Williams
Accurate phase fraction analysis is an essential element of microstructural characterization of alloys and often serves as a basis to quantify effects such as heat treatment or mechanical deformation. Additive manufacturing (AM) of metals, due to the

Bayesian automated weighting of aggregated DFT, MD, and experimental data for candidate thermodynamic models of aluminum with uncertainty quantification

December 1, 2021
Author(s)
Francesca Tavazza, Chandler A. Becker, Ursula R. Kattner, Joshua Gabriel, Noah Palson, Thien Duong, Marius Stan
Atomic-scale modeling methods such as density functional theory (DFT) and molecular dynamics (MD) can predict the thermodynamic properties of materials at a lower cost than experimental measurements. However, their regular usage in thermodynamic model

Thermal Shrinkage Reveals the Feasibility of Pulse-delay Photocuring Technique

December 1, 2021
Author(s)
Sri Vikram Palagummi, Taeseung Hong, Li Jiang, Martin Chiang
Objectives: To resolve applicability of the pulse-delay photocuring technique to restorative dental composites as a clinical strategy for the reduction in the detrimental polymerization stress. Methods: Model dental composites with high and low-filler

Materials Testing in Hydrogen

November 30, 2021
Author(s)
Matthew Connolly, May Ling Martin, Damian Lauria, Peter Bradley, Zack Buck, Andrew Slifka, Robert L. Amaro

Opportunities in electrically tunable 2D materials beyond graphene: Recent progress and future outlook

November 30, 2021
Author(s)
Tom Vincent, Jiayun liang, simrjit singh, eli castanon, xiaotian zhang, deep jariwala, olga kazakova, zakaria al-balushi, Amber McCreary
The interest in two-dimensional and layered materials continues to expand, driven by the compelling properties of individual atomic layers that can be stacked and/or twisted into synthetic heterostructures. The plethora of electronic properties as well as

Magnetic Structure Determination of High-Moment Rate-Earth-Based Laminates

November 29, 2021
Author(s)
D. Potashnikov, E. Caspi, A. Pesach, Q. Tao, J. Rosen, D. Sheptyakov, Hayden Evans, C. Ritter, Z. Salman, P. Bonfa, T. Ouisse, M. Barbier, O. Rivin, A. Keren
We report μSR on the 2D rare earth based parent magnets (Mo 2/3RE 1/3) 2AlC with RE = Nd, Gd, Tb, Dy, Ho and Er, and neutron diffraction on the series with RE ≠ Gd (a neutron absorber). By crossing information between the two techniques, we determine the

Sintered powder oxidation variation as a function of build height for titanium alloy produced by electron beam powder-bed fusion

November 26, 2021
Author(s)
Nicholas Derimow, Alejandro Romero, Aldo Rubio, Cesar Terrazas, Francisco Medina, Ryan Wicker, Nik Hrabe
It is well-established that titanium alloy (Ti-6Al-4V) powder oxidizes during electron beam powder-bed fusion (PBF-EB) due to the high background temperatures resulting from layer preheating and sintering of the powder bed before melting. However, it is

Imaging of Magnetic Excitations in Nanostructures with Microwave Near-Field Microscopy

November 25, 2021
Author(s)
Samuel Berweger, Robert Tyrrell-Ead, Houchen Chang, Mingzhong Wu, Hong Tang, Hans Nembach, Karl Stupic, Stephen E. Russek, Thomas Mitchell (Mitch) Wallis, Pavel Kabos
We present images of spin-wave excitations in a patterned yttrium iron garnet (YIG) thin film obtained by use of near-field microwave microscopy, which can achieve spatial resolution as high as 50 nm. Visualization of magnetic excitations is an enticing

Uncertainty Prediction for Machine Learning Models of Material Properties

November 23, 2021
Author(s)
Francesca Tavazza, Brian DeCost, Kamal Choudhary
Uncertainty quantification in artificial intelligence (AI)-based predictions of material properties is of immense importance for the success and reliability of AI applications in materials science. While confidence intervals are commonly reported for

Activation of Mechanophores in a Thermoset Matrix by Instrumented Scratch

November 17, 2021
Author(s)
Chelsea S. Davis, Jeremiah Woodcock, Ryan Beams, Mitchell Rencheck, Muzhou Wang, Stephan J. Stranick, Aaron M. Forster, Jeffrey Gilman
Scratches in polymer coatings and barrier layers negatively impact optical properties (haze, light transmission, etc.), initiate routes of degradation or corrosion (moisture permeability), and nucleate delamination of the coating. Detecting scratches in

Chiral Spin Bobbers in Exchange-Coupled Hard-Soft Magnetic Bilayers

November 17, 2021
Author(s)
X. H. Zhang, T. R. Gao, L. Fang, S. Fackler, Julie Borchers, Brian Kirby, Brian B. Maranville, S. E. Lofland, A. T. N'Diaye, E. Arenholz, A. Ullah, J. Cui, R. Skomski, Ichiro Takeuchi
The spin structure of exchange-coupled MnBi:Co-Fe bilayers is investigated by X-ray magnetic circular dichroism (XMCD), polarized neutron reflectometry (PNR), and micromagnetic simu-lations. The purpose of the present research is two-fold. First, the

Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data

November 15, 2021
Author(s)
Vishu Gupta, Kamal Choudhary, Francesca Tavazza, Carelyn E. Campbell, Wei-Keng Liao, Alok Choudhary, Ankit Agrawal
Artificial Intelligence (AI) and Machine Learning (ML) has been increasingly used in materials science to build property prediction models and accelerate materials discovery. The availability of large materials databases for some properties like formation

Evaluation of a Modified Void Descriptor Function to Uniquely Characterize Pore Networks and Predict Fracture Location in Additively Manufactured Metals

November 15, 2021
Author(s)
Dillon Watring, Jake Benzing, Orion Kafka, Li-Anne Liew, Newell Moser, John Erickson, Nik Hrabe, Ashley Spear
Variations in additive manufacturing (AM) processing parameters can lead to variations in porosity, making it challenging to predict pore- or void-sensitive mechanical response in AM metals. A recently developed pore metric, the void descriptor function
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