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We investigate the feasability of improving the semi-empirical density functional based tight-binding method (DFTB) through a general and transferable many-body repulsive potential for pure silicon using a common machine-learning framework.…

Materials Science · Physics 2022-02-23 Dylan Bissuel , Tristan Albaret , Thomas A. Niehaus

The acceleration of lithium tube segments with the length one centimeter, diameter sixteen microns wall thickness one nanometer is considered. These segments are electrically charged by proton beams produced by an electron beam source.…

Plasma Physics · Physics 2013-11-22 S. N. Dolya

Color centers in diamond are widely explored as qubits in quantum technologies. However, challenges remain in the effective and efficient integration of these diamond-hosted qubits in device heterostructures. Here, nanoscale-thick uniform…

Three-dimensional topological semimetals host a range of interesting quantum phenomena related to band crossing that give rise to Dirac or Weyl fermions, and can be potentially engineered into novel quantum devices. Harvesting the full…

A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is proposed, in which parameters are embedded into a low-cost, low-level (LL) ab initio theory and adjusted to obtain agreement…

Chemical Physics · Physics 2013-11-15 Matteus Tanha , Shiva Kaul , Alex Cappiello , Geoffrey J. Gordon , David J. Yaron

Nanobeam optomechanical crystals, in which localized GHz frequency mechanical modes are coupled to wavelength-scale optical modes, are being employed in a variety of experiments across different material platforms. Here, we demonstrate the…

Applied Physics · Physics 2018-07-12 Karen E. Grutter , Marcelo Davanço , Krishna C. Balram , Kartik Srinivasan

At the heart of the flourishing field of machine learning potentials are graph neural networks, where deep learning is interwoven with physics-informed machine learning (PIML) architectures. Various PIML models, upon training with density…

Machine-learned interatomic potentials are fast becoming an indispensable tool in computational materials science. One approach is the ephemeral data-derived potential (EDDP), which was designed to accelerate atomistic structure prediction.…

While phase-change materials (PCMs) composed of chalcogenide have different crystallization mechanisms (CM), such as nucleation-dominated Ge2Sb2Te5 (GST) and growth-dominated GeTe (GT), revealing the essential reason of CM as well as the…

Two-dimensional ternary locally resonant phononic crystals used to consist of cylindrical scatterers with uniform coatings in their exterior. An alternative coating scheme with a comblike profile is proposed and investigated in this letter.…

Materials Science · Physics 2013-12-05 Yan-Feng Wang , Yue-Sheng Wang , Litian Wang

Semi-empirical interatomic potentials have been developed for Al, alpha-Ti, and gamma-TiAl within the embedded atomic method (EAM) by fitting to a large database of experimental as well as ab-initio data. The ab-initio calculations were…

Materials Science · Physics 2009-11-10 Rajendra R. Zope , Y. Mishin

New interatomic potentials describing defects, plasticity and high temperature phase transitions for Ti are presented. Fitting the martensitic hcp-bcc phase transformation temperature requires an efficient and accurate method to determine…

Materials Science · Physics 2016-12-12 M. I. Mendelev , T. L. Underwood , G. J. Ackland

The wafer scale integration of carbon nanotubes (CNT) remains a challenge for electronic and electromechanical applications. We propose a novel CNT integration process relying on the combination of controlled capillary assembly and buried…

We present a scalable method for electrically tuning multiple spatially separated quantum dots embedded in photonic crystal waveguides. Ion implantation into the top p-doped layer of a p-i-n diode creates high-resistivity tracks, providing…

Modern electronic structure theories can predict and simulate a wealth of phenomena in surface science and solid-state physics. In order to allow for a direct comparison with experiment, such ab initio predictions have to be made in the…

Materials Science · Physics 2020-04-15 Thomas Gruber , Ke Liao , Theodoros Tsatsoulis , Felix Hummel , Andreas Grüneis

Computing equilibrium concentrations of molecular complexes is generally analytically intractable and requires numerical approaches. In this work we focus on the polymer-monomer level, where indivisible molecules (monomers) combine to form…

Data Structures and Algorithms · Computer Science 2025-08-25 Hamidreza Akef , Minki Hhan , David Soloveichik

For a capacitor made of a semiconducting carbon nanotube (CNT) suspended above a metallic gate, Coulomb correlations between individual electrons can lead to a capacitance that is much larger than the geometric capacitance. We argue that…

Strongly Correlated Electrons · Physics 2015-04-22 Han Fu , B. I. Shklovskii , Brian Skinner

We present an approach for rapid conformational analysis of semi-flexible liquid crystals. We use a simple graphical user interface (GUI) tool that leverages rules-based methods for efficient generation of bend-angle distributions, offering…

Soft Condensed Matter · Physics 2024-08-29 Jordan L. Hobbs , Calum J. Gibb , Ewan Cruickshank , Rebecca Walker , Richard J. Mandle

This study investigates the torsional mechanical properties of pristine iron (Fe) and carbon-doped iron (FeC) nanowires with [001] orientation through molecular dynamics simulations utilizing the Modified Embedded Atom Method (MEAM)…

Materials Science · Physics 2025-07-16 Charith L. Hirimuthugodage , Laalitha S. I. Liyanage , K. G. S. H. Gunawardana

The embedding method for the calculation of the conductance through interacting systems connected to single channel leads is generalized to obtain the full complex transmission amplitude that completely characterizes the effective…

Mesoscale and Nanoscale Physics · Physics 2015-06-04 Rafael A. Molina , Peter Schmitteckert , Dietmar Weinmann , Rodolfo A. Jalabert , Philippe Jacquod