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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…
We propose an active learning method for discovering low-dimensional structure in high-dimensional Gaussian process (GP) tasks. Such problems are increasingly frequent and important, but have hitherto presented severe practical…
The oxidation of NO molecules on epoxy-functionalized highly oriented pyrolytic graphite, thermalized at 300 K, was studied by means of ab initio molecular dynamics (AIMD) calculations. Four collision energies and two different orientations…
The rising energy demands of conventional AI systems underscore the need for efficient computing technologies like brain-inspired computing. Physical reservoir computing (PRC), leveraging the nonlinear dynamics of physical systems for…
Structure-property relationships is a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural…
We report an ab initio evaluation of the surface energy of a simple metal, performed via a coupling-constant integration over the dynamical density-response function. The rapid rate of change of the electron density at the surface is…
Axion insulators are magnetic topological insulators in which the non-trivial $\mathbb{Z}_2$ index is protected by inversion symmetry instead of time-reversal symmetry. The naturally gapped surfaces of axion insulators give rise to a…
IR drop analysis is essential in physical chip design to ensure the power integrity of on-chip power delivery networks. Traditional Electronic Design Automation (EDA) tools have become slow and expensive as transistor density scales. Recent…
Taking into account the regional characteristics of intrinsic and extrinsic properties of space is an essential issue in architectural design and urban renewal, which is often achieved step by step using image and graph-based GANs. However,…
Indium phosphide and derived compound semiconductors are materials often involved in high-efficiency solar water splitting due to their versatile opto-electronic properties. Surface corrosion, however, typically deteriorates the performance…
We study the initial interaction of adsorbed H2O with P-rich and Ga-rich GaP(100) surfaces. Atomically well defined surfaces are prepared by metal-organic vapour phase epitaxy and transferred contamination-free to ultra-high vacuum, where…
Gaussian process regression (GPR) is a useful technique to predict composition--property relationships in glasses as the method inherently provides the standard deviation of the predictions. However, the technique remains restricted to…
Understanding and controlling the atomic structure of polar oxide surfaces is essential for unraveling surface reactivilty and designing advanced catalytic materials. Among these, the polar CeO2(100) surface is a prototypical and…
Layered lithium intercalating transition metal (TM) oxides are promising cathode materials for Li-ion batteries. Here we scrutinize the recently developed strongly constrained and appropriately normed (SCAN) density functional method to…
The covalent functionalization of graphene represents a main topic in the growing field of nano materials. The reductive exfoliation of graphite with concomitant functionalization of the respective graphenide intermediates provides a…
Many modern data sets are sampled with error from complex high-dimensional surfaces. Methods such as tensor product splines or Gaussian processes are effective/well suited for characterizing a surface in two or three dimensions but may…
Lithium plating during fast charging is a critical degradation mechanism that accelerates capacity fade and can trigger catastrophic safety failures. Recent work has shown that plating onset can manifest in incremental-capacity analysis as…
Higher-dimensional orthogonal packing problems have a wide range of practical applications, including packing, cutting, and scheduling. Previous efforts for exact algorithms have been unable to avoid structural problems that appear for…
Structural prediction for the discovery of novel materials is a long sought after goal of computational physics and materials sciences. The success is rather limited for methods such as the simulated annealing method (SA) that require…
We develop a thermodynamic description of accumulation-layer heterostructures in which the induced sheet density is partitioned between the near-interface accumulation-layer charge and a complementary screening charge in the surrounding…