Related papers: Million-atom heat transport simulations of polycry…
We develop a neuroevolution-potential (NEP) framework for generating neural network based machine-learning potentials. They are trained using an evolutionary strategy for performing large-scale molecular dynamics (MD) simulations. A…
Graphene oxide (GO) exhibits rich chemical heterogeneity that strongly influences its structural, thermal, and mechanical properties, yet quantitatively linking reduction chemistry to heat transport remains challenging. In this work, we…
Molecular dynamics (MD) simulations play an important role in understanding and engineering heat transport properties of complex materials. An essential requirement for reliably predicting heat transport properties is the use of accurate…
Approach-to-equilibrium molecular dynamics simulations have been used to study thermal transport in nanocrystalline graphene sheets. Nanostructured graphene has been created using an iterative process for grain growth from initial seeds…
Path-integral molecular dynamics (PIMD) simulations are crucial for accurately capturing nuclear quantum effects in materials. However, their computational intensity and reliance on multiple software packages often limit their applicability…
Thermal conduction was explored and discussed through a combined theoretical and simulation approach in this work. The thermal conductivity k of polycrystalline graphene was calculated by molecular dynamics simulations based on a hexagonal…
We study the interfacial thermal conductance of grain boundaries (GBs) between monolayer graphene and hexagonal boron nitride (h-BN) sheets using a combined atomistic approach. First, realistic samples containing graphene/h-BN GBs with…
The performance potential for simulating quantum electron transport on graphical processing units (GPUs) is studied. Using graphene ribbons of realistic sizes as an example it is shown that GPUs provide significant speed-ups in comparison…
Most materials in available macroscopic quantities are polycrystalline. Graphene, a recently discovered two-dimensional form of carbon with strong potential for replacing silicon in future electronics, is no exception. There is growing…
Self-heating in next-generation, high-power-density field-effect transistor limits performance and complicates fabrication. Here, we introduce NEP-FET, a machine-learned framework for device-scale heat transport simulations of field-effect…
The recent fabrication of graphene nanoribbon (GNR) field-effect transistors poses a challenge for first-principles modeling of carbon nanoelectronics due to many thousand atoms present in the device. The state of the art quantum transport…
We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in [Fan et al., Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package…
Graphene has drawn wide attention due to its exceptional thermal conductivity but complete understanding of thermal characteristics of polycrystalline graphene is still elusive to date. For the first time, herein, we have systematically…
Establishing the structure-property relationship for grain boundaries (GBs) is critical for developing next generation functional materials, but has been severely hampered due to its extremely large configurational space. Atomistic…
In this letter, we investigate numerically (by non-equilibrium molecular dynamics) and analytically the thermal conductivity of nanoscale graphene disks (NGDs), and discussed the possibility to realize FGM with only one material, NGDs. We…
In low-dimensional systems, the combination of reduced dimensionality, strong interactions, and topology has led to a growing number of many-body quantum phenomena. Thermal transport, which is sensitive to all energy-carrying degrees of…
Purpose: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on GPUs. However, these usually use simplified models for non-elastic (NE) proton-nucleus interactions. Our primary goal is to build a…
Using non-equilibrium molecular dynamics (NEMD) simulation, we study thermal properties of the so-called nanoporous graphene (NPG) sheet which contains a series of nanoporous in an ordered way and was synthesized recently (Science 360…
We present systematic thermal conductivity measurements of suspended thin graphite ribbons, 234-527 nm thick, using a four-probe 3-omega method. Unlike recent reports of phonon hydrodynamics and exceptionally high thermal conductivity in…
We propose GrainGNN, a surrogate model for the evolution of polycrystalline grain structure under rapid solidification conditions in metal additive manufacturing. High fidelity simulations of solidification microstructures are typically…