A new technical paper titled “Deep-learning atomistic semi-empirical pseudopotential model for nanomaterials” was published ...
Northwestern Engineering researchers have developed a new framework using machine learning that improves the accuracy of interatomic potentials — the guiding rules describing how atoms interact — in ...
An integrative modeling workflow to understand with atomistic precision biomolecular dynamics from high-speed atomic force microscopy experiments. (Nanowerk News) High-speed atomic force microscopy ...
Predicting how continuous microscopic strains alter local bond lengths and hopping energies has required computationally taxing physics simulations, frustrating attempts to efficiently scan the ...
The cover image of 10/2024 issue of Bioconjugate Chemistry, displaying a tunable ligand-protected gold nanocluster as a drug delivery system with high affinity to integrin αvβ3, a key regulator of ...
There are many challenges in the development of a modern semiconductor chip, from front-end architecture simulation to final signoff. Volume manufacturing has its own set of challenges, while silicon ...
A new method could lead to more accurate predictions of how new materials behave at the atomic scale. Northwestern University researchers have developed a new framework using machine learning that ...
A collaboration team of researchers from the Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, the Institute of Transformative Bio-Molecules (WPI-ITbM), Graduate School of Science at ...
Researchers have used machine learning and supercomputer simulations to investigate how tiny gold nanoparticles bind to blood proteins. The studies discovered that favorable nanoparticle-protein ...
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