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Indentation test is used with growing popularity for the characterization of various materials on different scales. Developed methods are combining the test with computer simulation and inverse analyses to assess material parameters…

Computational Physics · Physics 2015-07-14 Vladimir Buljak , Shwetank Pandey

In this study, we develop a conditional diffusion model that proposes the optimal process parameters and predicts the microstructure for the desired mechanical properties. In materials development, it is costly to try many samples with…

Computational Engineering, Finance, and Science · Computer Science 2025-10-27 Arisa Ikeda , Ryo Higuchi , Tomohiro Yokozeki , Katsuhiro Endo , Yuta Kojima , Misato Suzuki , Mayu Muramatsu

We introduce a computational database with calculated structural, thermodynamic, electronic, magnetic, and optical properties of 820 one-dimensional materials. The materials are systematically selected and exfoliated from experimental…

The extreme and repeated temperature variation during additive manufacturing of metal parts has a large effect on the resulting material microstructure and properties. The ability to accurately predict this temperature field in detail, and…

Applied Physics · Physics 2021-10-15 Lichao Fang , Lin Cheng , Jennifer A. Glerum , Jennifer Bennett , Jian Cao , Gregory J. Wagner

The present article proposes a data analysis method for experimentally-derived measurements, which consists of an auto-optimization procedure and a sensitivity analysis. The method was applied to the results of a total-reflection…

Since the implementation of the Materials Genome Project by the Obama administration in the United States, the development of various computational materials databases has fundamentally expanded the choices of industries such as materials…

Materials Science · Physics 2024-05-09 Ying Fang , Hezhu Shao

The thermal characteristics of silicon between 15 and 300 deg K are investigated by applying a computer program on the solution of the differential heat diffusion equation. The computer model is linked to high-purity silicon through a set…

Materials Science · Physics 2007-08-31 H. Diedrich , R. Liberati

The paper presents an approach for the identification of elasto-static parameters of a robotic manipulator using the virtual experiments in a CAD environment. It is based on the numerical processing of the data extracted from the finite…

Robotics · Computer Science 2013-11-27 Alexandr Klimchik , Anatol Pashkevich , Damien Chablat

The thermo-electrical properties of a complex silicon cantilever structure used in thermal scanning probe lithography are modeled based on well established empirical laws for the thermal conductivity in silicon, the electrical conductivity…

Materials Science · Physics 2017-11-28 M. Spieser , C. Rawlings , E. Lörtscher , U. Duerig , A. W. Knoll

The experimental investigation of matter under extreme densities and temperatures as they occur for example in astrophysical objects and nuclear fusion applications constitutes one of the most active frontiers at the interface of material…

High speed machining has been improved thanks to considerable advancement on the tools (optimum geometry, harder materials), on machined materials (increased workability and machining capacity for harder workpieces) and finally on the…

Classical Physics · Physics 2009-09-29 Olivier Cahuc , Alain Gérard

Micromechanical constitutive parameters are important for many engineering materials, typically in microelectronic applications and material design. Their accurate identification poses a three-fold experimental challenge: (i) deformation of…

Soft Condensed Matter · Physics 2023-02-08 O. Rokoš , R. H. J. Peerlings , J. P. M. Hoefnagels , M. G. D. Geers

Autonomous experimentation systems have been used to greatly advance the integrated computational materials engineering (ICME) paradigm. This paper outlines a framework that enables the design and selection of data collection workflows for…

Materials Science · Physics 2022-06-20 Rohan Casukhela , Sriram Vijayan , Joerg R. Jinschek , Stephen R. Niezgoda

The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and error, and luck. We propose a methodology that can…

Machine Learning · Statistics 2017-07-20 Julia Ling , Max Hutchinson , Erin Antono , Sean Paradiso , Bryce Meredig

X-ray diffraction is ideal for probing sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and…

Materials Science · Physics 2025-01-10 Rachel E. Lim , Shun-Li Shang , Chihpin Chuang , Thien Q. Phan , Zi-Kui Liu , Darren C. Pagan

Control of surface texture in strip steel is essential to meet customer requirements during galvanizing and temper rolling processes. Traditional methods rely on post-production stylus measurements, while on-line techniques offer…

Machine Learning · Computer Science 2023-10-03 Alex Milne , Xianghua Xie

Using a partitioned-energy thermodynamic framework which assigns energy to that of atomic configurational stored energy of cold work and kinetic-vibrational, we derive an important constraint on the Taylor-Quinney coefficient, which…

Materials Science · Physics 2020-07-09 Charles K. C. Lieou , Curt A. Bronkhorst

For manufacturing of aerospace composites, several parts may be processed simultaneously using convective heating in an autoclave. Due to uncertainties including tool placement, convective Boundary Conditions (BCs) vary in each run. As a…

Machine Learning · Computer Science 2021-07-20 Keith D. Humfeld , Dawei Gu , Geoffrey A. Butler , Karl Nelson , Navid Zobeiry

In computational materials science, mechanical properties are typically extracted from simulations by means of analysis routines that seek to mimic their experimental counterparts. However, simulated data often exhibit uncertainties that…

Data Analysis, Statistics and Probability · Physics 2017-12-07 Paul N. Patrone , Anthony J. Kearsley , Andrew M. Dienstfrey

Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently…

Materials Science · Physics 2024-01-02 David Guirguis , Conrad Tucker , Jack Beuth