We have developed a method to simulate behavior of nanoporous materials in a molecular dynamics code. The nanoporous solid is produced via a spinodal decomposition of a material brought from a supercritical fluid into the two phase (liquid-vapor) region and then quenching and freezing the liquid into an interconnected nanoporous solid. We have simulated, at the atomic level, compression in crystal/nanoporous configurations, demonstrating that this is a powerful technique for studying the equation-of-state of cold and warm dense matter. By performing compression simulations relevant to high energy density physics experiments, we have been able to elucidate experimental measurement by identifying governing microscopic mechanisms.
Structure is the most distinctive feature of nanoporous metals. The intricate maze of rounded shapes, where ligaments and pores run after each other disorderly, strikes imagination no less than it imparts properties that, tuned by size effects, have no counterpart in the bulk form. Indisputably, nanoporous Au has been the absolute protagonist of the field of study, unveiling the disrupting potential of nanoporous metals in areas ranging from catalysis to energy and sensing. Here, we still focus on nanoporous Au, addressing the long-standing issue of mechanical properties in nanoporous metals. …
We study the structural and mechanical properties of nanoporous (NP) carbon materials by extensive atomistic machine-learning (ML) driven molecular dynamics (MD) simulations. To this end, we retrain a ML Gaussian approximation potential (GAP) for carbon by recalculating the a-C structural database of Deringer and Csányi [Phys. Rev. B 2017, 95, 094203] adding van der Waals interactions. Our GAP enables a notable speedup and improves the accuracy of energy and force predictions. We use the GAP to thoroughly study the atomistic structure and pore-size distribution in computational NP carbon sampl…
Max-Planck-Institut für Eisenforschung（马克斯·普朗克钢铁研究所）；Technische Universität Darmstadt（达姆施塔特工业大学）；DeepMetis
The elastic properties of materials derive from their electronic and atomic nature. However, simulating bulk materials fully at these scales is not feasible, so that typically homogenized continuum descriptions are used instead. A seamless and lossless transition of the constitutive description of the elastic response of materials between these two scales has been so far elusive. Here we show how this problem can be overcome by using Artificial Intelligence (AI). A Convolutional Neural Network (CNN) model is trained, by taking the structure image of a nanoporous material as input and the corre…
The granular nanoporous carbon medium, made of the cylindrical coal granules of the adsorbent of SKT 3, at an influence by the high pressures from 1MPa to 3GPa has been researched. The eight consecutive stages of the materials specific volume change, which is characterized by a certain dependence of the volume change on the pressure change, have been registered. It is shown that there is a linear dependence on the double log log plot of the materials specific volume change on the pressure for an every stage of considered process. The two stages are clearly distinguished such as a stage of mate…
We report a molecular dynamics (MD) simulation study of reverse osmosis desalination using nanoporous monolayer graphene passivated by SiH$_2$ and Si(OH)$_2$ functional groups. A highly accurate and detailed polarizable molecular mechanics force field model was developed for simulating graphene nanopores of various sizes and geometries. The simulated water fluxes and ion rejection percentages are explained using detailed atomistic mechanisms derived from analysis of the simulation trajectories. Our main findings are: (1) The Si(OH)$_2$ pores possess superior ion rejection rates due to selectiv…
Designing platforms to control phase-coherence and interference of electron waves is a cornerstone for future quantum electronics, computing or sensing. Nanoporous graphene (NPG) consisting of linked graphene nanoribbons has recently been fabricated using molecular precursors and bottom-up assembly [Moreno et al., Science 360, 199 (2018)] opening an avenue for controlling the electronic current in a two-dimensional material. By simulating electron transport in real-sized NPG samples we predict that electron waves injected from the tip of a scanning tunneling microscope (STM) behave similarly t…
Nanoporous metals or nanofoams are a promising material class that is considered for sensing, actuation, and catalysis. To date, they mostly based on simple noble metals such as nanoporous gold, which exhibit peculiar stress-strain response different from the bulk material. At the same time bulk alloys such as NiTi feature a reversible martensitic phase transition giving rise to interesting shape memory and superelastic effects. Combining the rich mechanics of NiTi with the geometrical features of a nanofoam is expected to improve the mechanical performance of this material. In this atomistic …
The total energy of acoustic emission (AE) events in externally stressed materials diverges when approaching macroscopic failure. Numerical and conceptual models explain this accelerated seismic release (ASR) as the approach to a critical point that coincides with ultimate failure. Here, we report ASR during soft uniaxial compression of three silica-based (SiO$_2$) nanoporous materials. Instead of a singular critical point, the distribution of AE energies is stationary and variations in the activity rate are sufficient to explain the presence of multiple periods of ASR leading to distinct brit…
Silicon (Si) is one of the most abundant elements on Earth, and it is the most important and widely used semiconductor, constituting the basis of modern electronic devices. Despite extensive study, some properties of Si remain elusive. For example, the behaviour of Si under high pressure, in particular at the ultra-high strain rates characteristic of dynamic compression, has been a matter of debate for decades. A detailed understanding of how Si deforms is crucial for a variety of fields, ranging from planetary science to materials design. Simulations suggest that in Si the shear stress genera…
Mullins' theory predicts the buildup of adatoms during surface diffusion at the edges of grooves where grain boundaries emerge to the surface of a polycrystalline film. However, the mesoscopic nature of this theory prevents the identification of the atomic scale physical mechanisms involved in this phenomenon. Here, we interpret the buildup of adatoms in atomistic terms through a mean-field rate-equation model and demonstrate both its kinetic nature and its impact on the intrinsic stress in these systems. Furthermore, the model provides estimates of the surface profile of intrinsic stress, of …
The ion-bombardment induced nanopatterning of Si(001) has been simulated by atomistic simulations with and without Fe impurity. The surface contamination has been simulated by using a new force field developed for FeSi. This is a fitted bond order potential (BOP) given for Si and for Fe by Albe et al. This BOP formula has been optimized simultaneously for FeSi, Si and for Fe. Using this new force field we are able to follow the ion-beam assisted deposition for Si in the presence of Fe contamination in the surface region. As an overall result, we get an unexpectedly rich variety of nanopatterns…
We use our recently proposed accelerated dynamics algorithm (Tiwary & van de Walle, 2011) to calculate temperature and stress dependence of activation free energy for surface nucleation of dislocations in pristine Gold nanopillars under realistic loads. While maintaining fully atomistic resolution, we achieve the fraction of a second time-scale regime. We find that the activation free energy depends significantly on the driving force (stress or strain) and temperature, leading to very high activation entropies. We also perform compression tests on Gold nanopillars for strain rates varying betw…
A detailed understanding of the material response to rapid compression is challenging and demanding. For instance, the element gold under dynamic compression exhibits complex phase transformations where there exist some large discrepancies between experimental and theoretical studies. Here, we combined large-scale molecular dynamics simulations with a deep potential to elucidate the dynamic compression processes of gold from an atomic level. The potential is constructed by accurately reproducing the free energy surfaces of density-functional-theory calculations for gold, from ambient condition…
Due to critical environmental issues there is a pressing need to switch from current refrigeration methods based on compression of greenhouse gases to novel solid-state cooling technologies. Solid-state cooling capitalizes on the thermal response of materials to external fields named "caloric effect". The barocaloric (BC) effect driven by hydrostatic pressure is particularly promising from a technological point of view since typically presents larger cooling potential than other caloric variants (e.g., magnetocaloric and electrocaloric effects driven by magnetic and electric fields, respective…
The diffusion of iodine defects has been considered the most important degradation mechanism of methylammonium lead iodine (MAPI) in solar cells. The present study demonstrates the importance of the pressure inside this material on the dynamics of iodine defects, using molecular dynamics simulations. It is known that the diffusion coefficient of an iodine vacancy is an order of magnitude higher than that of interstitial iodine. We show that this difference systematically increases with increased tensile strain and that both diffusion coefficients tend to zero when a compressive strain is appli…
Molecular dynamics simulations are performed to provide a detailed understanding of the functional degradation of shape memory alloys at small scale. The origin of the experimentally reported accumulation of plastic deformation and the anomalous sudden increase of the residual strain under cyclic mechanical loading are explained by detailed insights into the relevant atomic scale processes. Our work reveals that the mechanical response of shape-memory-alloy pillars under cyclic compression is significantly influenced by the presence of an amorphous-like surface region as experimentally induced…
Machine learning has emerged as a powerful tool for the analysis of mesoscopic and atomically resolved images and spectroscopy in electron and scanning probe microscopy, with the applications ranging from feature extraction to information compression and elucidation of relevant order parameters to inversion of imaging data to reconstruct structural models. However, the fundamental limitation of machine learning methods is their correlative nature, leading to extreme susceptibility to confounding factors. Here, we implement the workflow for causal analysis of structural scanning transmission el…
Train for Accuracy, Execute at Scale: Architecture-Preserving Inference for Equivariant Atomistic Foundation Models
Beijing Institute of Technology（北京理工大学）；Zhongguancun Academy（中关村学院）；Zhongguancun Institute of Artificial Intelligence（中关村人工智能研究院）；Kairos Materials；National University of Singapore（新加坡国立大学）
Ionic liquids are widely used as electrolytes in electrochemical devices. In this context, many experimental and theoretical approaches have been recently developed for characterizing their interface with electrodes. In this perspective article, we review the most recent advances in the field of computer simulations (mainly molecular dynamics). A methodology for simulating electrodes at constant electrical potential is presented. Several types of electrode geometries have been investigated by many groups in order to model planar, corrugated and porous materials and we summarize the results obt…
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
Bohai University（渤海大学）；The Chinese University of Hong Kong（香港中文大学）；Chalmers University of Technology（查尔姆斯理工大学）；Shenzhen Technology University（深圳职业技术大学）；Shenzhen University（深圳大学）；Xinyu University（新余学院）；University of Science and Technology Beijing（北京科技大学）
We perform a systematic study of the characteristics of shear transformation zones (STZs) that nucleate at free surfaces of two-dimensional amorphous solids subject to tensile loading using two different atomistic simulation methods, the standard athermal, quasistatic (AQ) approach and our recently developed self-learning metabasin escape (SLME) method to account for the finite temperature and strain-rate effects. In the AQ, or strain-driven limit, the nonaffine displacement fields of surface STZs decay exponentially away from their centers at similar decay rates as their bulk counterparts, th…
