English
Related papers

Related papers: Materials Discovery in Combinatorial and High-thro…

200 papers

Atomistic simulations have become a powerful tool in materials research due to the extremely fine spatial and temporal resolution provided by such techniques. In order to understand the fundamental principles which govern material behavior…

Materials Science · Physics 2014-08-26 Jason F. Panzarino , Timothy J. Rupert

We extend our study of Motion Planning via Manifold Samples (MMS), a general algorithmic framework that combines geometric methods for the exact and complete analysis of low-dimensional configuration spaces with sampling-based approaches…

Robotics · Computer Science 2015-09-17 Oren Salzman , Michael Hemmer , Dan Halperin

This comprehensive review discusses the development of scanning electron microscopy and the application of this technology in different fields such as biology, nanobiotechnology and biomedical science. Besides being a tool for high…

Quantitative Methods · Quantitative Biology 2023-11-02 Aniruddha Acharya

Super-resolution microscopy overcomes the diffraction limit of conventional light microscopy in spatial resolution. By providing novel spatial or spatio-temporal information on biological processes at nanometer resolution with molecular…

Biological Physics · Physics 2021-11-10 Tianjie Yang , Yaoru Luo , Wei Ji , Ge Yang

Two-dimensional, resonant scanners have been utilized in a large variety of imaging modules due to their compact form, low power consumption, large angular range, and high speed. However, resonant scanners have problems with non-optimal and…

Image and Video Processing · Electrical Eng. & Systems 2023-05-05 Zhanghao Sun , Ronald Quan , Olav Solgaard

Scanning tunneling microscopy (STM) has been a fundamental tool to characterize many-body effects in condensed matter systems, from extended solids to quantum dots. STM of molecules decoupled from the supporting conductive substrate has the…

Mesoscale and Nanoscale Physics · Physics 2011-01-14 Dimitrios Toroz , Massimo Rontani , Stefano Corni

Nanoparticles (NPs) are widely used in diverse application areas, such as medicine, engineering, and cosmetics. The size (or volume) of NPs is one of the most important parameters for their successful application. It is relatively…

Mesoscale and Nanoscale Physics · Physics 2016-06-06 Ravi Kiran Attota

Scanning tunneling microscopy (STM) has made tremendous progress in the study and understanding of both classical and unconventional superconductors. This has motivated a rapidly growing effort to apply the same techniques to the iron-based…

Superconductivity · Physics 2013-07-29 Can-Li Song , Jennifer E. Hoffman

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution,…

Materials Science · Physics 2023-09-27 Sue Sin Chong , Yi Sheng Ng , Hui-Qiong Wang , Jin-Cheng Zheng

Squeezing currently represents the leading strategy for quantum enhanced precision measurements of a single parameter in a variety of continuous- and discrete-variable settings and technological applications. However, many important…

Quantum Physics · Physics 2020-07-31 Manuel Gessner , Augusto Smerzi , Luca Pezzè

The recent decades have seen various attempts at accelerating the process of developing materials targeted towards specific applications. The performance required for a particular application leads to the choice of a particular material…

Transmission Electron Microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TEM have enabled high-volume and high-resolution data…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Josh Kacher , Yao Xie , Sven P. Voigt , Shixiang Zhu , Henry Yuchi , Jordan Key , Surya R. Kalidindi

Machine Learning tools are nowadays widely applied extensively to the prediction of the properties of molecular materials, using datasets extracted from high-throughput computational models. In several cases of scientific and technological…

Materials Science · Physics 2021-02-10 Fabio Le Piane , Matteo Baldoni , Francesco Mercuri

High-throughput approximations of quantum mechanics calculations and combinatorial experiments have been traditionally used to reduce the search space of possible molecules, drugs and materials. However, the interplay of structural and…

Quantum Physics · Physics 2019-10-29 Alain Tchagang , Julio Valdés

Time-resolved microscopy with the pump-probe protocol is one of the most important techniques for the investigation of dynamical processes at the nanoscale, thanks to the possibility of combining nanometric resolution imaging with…

Instrumentation and Detectors · Physics 2026-05-19 Simone Finizio , Tim A. Butcher , Sebastian Wintz , Markus Weigand , Jörg Raabe

We developed a scan mirror mechanism (SMM) that enable a slit-based spectrometer or spectropolarimeter to precisely and quickly map an astronomical object. The SMM, designed to be installed in the optical path preceding the entrance slit,…

Investigation of well-motivated parameter space in the theories of Beyond the Standard Model (BSM) plays an important role in new physics discoveries. However, a large-scale exploration of models with multi-parameter or equivalent solutions…

High Energy Physics - Phenomenology · Physics 2019-04-09 Jie Ren , Lei Wu , Jin Min Yang , Jun Zhao

The need of mathematically formulate relations between composite materials' properties and its resonance response is growing. This is due the fast technological advancement in micro-material manufacturing, present in chips for instance. In…

Mathematical Physics · Physics 2022-05-03 Taoufik Meklachi

Since the invention of the atomic force microscope (AFM) in 1986, there has been a drive to apply this scanning probe technique or a form of this technique to various disciplines in nanoscale science. Magnetic force microscopy (MFM) is a…

Instrumentation and Detectors · Physics 2017-04-28 Gustavo Cordova , Brenda Yasie Lee , Zoya Leonenko

Diffusion probabilistic models (DPMs) which employ explicit likelihood characterization and a gradual sampling process to synthesize data, have gained increasing research interest. Despite their huge computational burdens due to the large…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Yuheng Fan , Hanxi Liao , Shiqi Huang , Yimin Luo , Huazhu Fu , Haikun Qi