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Programmable electron-beam scanning offers new opportunities to improve dose efficiency and suppress scan-induced artifacts in scanning transmission electron microscopy. Here, we systematically benchmark the impact of non-raster…

Additive manufacturing (AM) enables the development of high-performance architected cellular materials, emphasizing the growing importance of establishing programmable and predictable energy absorption capabilities. This study evaluates the…

Applied Physics · Physics 2024-02-27 Mattia Utzeri , Marco Sasso , Vikram S. Deshpande , S. Kumar

Integrating topology optimization and additive manufacturing (AM) technology can facilitate innovative product development. However, laser powder bed fusion, which is the predominant method in metal AM, can lead to issues such as residual…

Computational Engineering, Finance, and Science · Computer Science 2024-12-19 Takao Miki

Additive manufacturing (AM) allows for manufacturing of complex three-dimensional geometries not typically realizable with standard subtractive manufacturing practices. The internal microstructure of a 3D printed component can have a…

Computational Engineering, Finance, and Science · Computer Science 2025-09-17 Lucas Gallup , Kevin N. Long , Devin J. Roach , William D. Reinholtz , Adam Cook , Craig M. Hamel

Despite decades of research, the ultimate goal of nanotechnology--top-down manipulation of individual atoms--has been directly achieved with only one technique: scanning probe microscopy. In this Review, we demonstrate that scanning…

Correlated with the trend of increasing degrees of freedom in robotic systems is a similar trend of rising interest in Spatio-Temporal systems described by Partial Differential Equations (PDEs) among the robotics and control communities.…

Robotics · Computer Science 2021-02-19 Ethan N. Evans , Andrew P. Kendall , Evangelos A. Theodorou

The development of novel materials in recent years has been accelerated greatly by the use of computational modelling techniques aimed at elucidating the complex physics controlling microstructure formation in materials, the properties of…

Materials Science · Physics 2025-11-14 Damien Pinto , Michael Greenwood , Nikolas Provatas

The ability to spatially modulate the electronic properties of solids has led to landmark discoveries in condensed matter physics as well as new electronic applications. Although crystals of strongly correlated metals exhibit a diverse set…

Liquid metals (LM) are embedded in an elastomer matrix to obtain soft composites with unique thermal, dielectric, and mechanical properties. They have applications in soft robotics, biomedical engineering, and wearable electronics. By…

Materials Science · Physics 2025-07-25 Abhijith Thoopul Anantharanga , Mohammad Saber Hashemi , Azadeh Sheidaei

Microstructure often dictates materials performance, yet it is rarely treated as an explicit design variable because microstructure is hard to quantify, predict, and optimize. Here, we introduce an image centric, closed-loop framework that…

Materials Science · Physics 2025-05-14 Geunho Choi , Changhwan Lee , Jieun Kim , Insoo Ye , Keeyoung Jung , Inchul Park

Tailoring microstructures represents a daunting goal in materials science. Here, an innovative proposition is to utilize grain boundary (GB) complexions (a.k.a. interfacial phases) to manipulate microstructural evolution, which is…

Materials Science · Physics 2023-09-19 Qizhang Yan , Chongze Hu , Jian Luo

We have fabricated Pt-containing granular metals by focused electron beam induced deposition from the $(CH_3)_3CH_3C_5H_4Pt$ precursor gas. The granular metals are made of platinum nanocrystallites embedded in a carbonaceous matrix. We have…

Materials Science · Physics 2015-05-27 F. Porrati , R. Sachser , C. H. Schwalb , A. S. Frangakis , M. Huth

Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However,…

Applied Physics · Physics 2019-05-08 Christoph Meier , Ryan W. Penny , Yu Zou , Jonathan S. Gibbs , A. John Hart

Polarization dynamics in ferroelectric materials are explored via the automated experiment in Piezoresponse Force Spectroscopy. A Bayesian Optimization framework for imaging is developed and its performance for a variety of acquisition and…

Disordered Systems and Neural Networks · Physics 2021-06-24 Rama K. Vasudevan , Kyle Kelley , Jacob Hinkle , Hiroshi Funakubo , Stephen Jesse , Sergei V. Kalinin , Maxim Ziatdinov

This paper presents a novel trajectory optimization formulation to solve the robotic assembly of the belt drive unit. Robotic manipulations involving contacts and deformable objects are challenging in both dynamic modeling and trajectory…

Robotics · Computer Science 2021-06-22 Shiyu Jin , Diego Romeres , Arvind Ragunathan , Devesh K. Jha , Masayoshi Tomizuka

Electroporation (EP), the temporary or permanent permeabilization of the cell membrane induced by an electric field, is the basis of various applications in medicine and food processing. In EP-based protocol optimization in terms of pulse…

Medical Physics · Physics 2024-03-22 Guillermo Marshall , Alejandro Soba

Al1-xScxN has attracted significant interest due to its large remnant polarization and low processing temperature when compared to other ferroelectric material systems. However, device dielectric failure before ferroelectric switching…

Materials Science · Physics 2025-11-25 Yinuo Zhang , Walter J. Smith , Giovanni Esteves , Eric A. Stach , Thomas E. Beechem , Roy H. Olsson

An optimal control strategy is developed to construct nanostructures of desired geometry along line segments by means of directed self-assembly of charged particles. Such a control strategy determines the electric potentials of a set of…

Dynamical Systems · Mathematics 2016-03-02 Arash Komaee , Paul I. Barton

In this work, the effect of building direction on the microstructure evolution of laser-powder bed fusion (LPBF) processed AlSi10Mg alloy was investigated. The building direction, as shown in experimentally fabricated parts, can influence…

To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-based…