English
Related papers

Related papers: Atomistic Models of Amorphous Metal-Organic Framew…

200 papers

The fully atomistic modeling of real-size plasmonic nanostructures is computationally demanding, therefore most calculations are limited to small-to-medium sized systems. However, plasmonic properties strongly depend on the actual shape and…

Computational Physics · Physics 2022-09-13 Piero Lafiosca , Tommaso Giovannini , Michele Benzi , Chiara Cappelli

We propose a novel representation of crystalline materials named orbital-field matrix (OFM) based on the distribution of valence shell electrons. We demonstrate that this new representation can be highly useful in mining material data. Our…

Controlling polymorphism in molecular crystals is crucial in the pharmaceutical, dye, and pesticide industries. However, its theoretical description is extremely challenging, due to the associated long timescales ($ > 1 \, \mu s$). We…

Chemical Physics · Physics 2023-02-09 Oren Elishav , Roy Podgaetsky , Olga Meikler , Barak Hirshberg

Phoretic particles exploit local self-generated physico-chemical gradients to achieve self-propulsion at the micron scale. The collective dynamics of a large number of such particles is currently the focus of intense research efforts, both…

Fluid Dynamics · Physics 2020-01-15 Akhil Varma , Sebastien Michelin

Metal-organic frameworks (MOFs) are a family of materials that have high porosity and structural tunability and hold great potential in various applications, many of which requiring a proper understanding of the thermal transport…

Materials Science · Physics 2023-08-04 Penghua Ying , Ting Liang , Ke Xu , Jin Zhang , Jianbin Xu , Zheng Zhong , Zheyong Fan

Electronic circular dichroism is an important optical phenomenon offering insights into chiral molecular materials. On the other hand, metal-organic frameworks (MOFs) are a novel group of crystalline porous thin-film materials that provide…

The development of novel materials in recent years has been accelerated greatly by the use of computational modelling techniques aimed at elucidating the complex physics controlling microstructure formation in materials, the properties of…

Materials Science · Physics 2025-11-14 Damien Pinto , Michael Greenwood , Nikolas Provatas

Rapid solidification leads to unique microstructural features, where a less studied topic is the formation of various crystalline defects, including high dislocation densities, as well as gradients and splitting of the crystalline…

Amorphization during severe plastic deformation has been observed in various crystalline materials, yet its underlying mechanisms remain poorly understood. This study introduces a novel phase-field model at the mesoscale, integrating…

Materials Science · Physics 2025-10-10 Yuntong Huang , Shuyang Dai , Chuqi Chen , Yang Xiang

Atomic force microscopy (AFM) is a key tool for characterising nanoscale structures, with functionalised tips now offering detailed images of the atomic structure. In parallel, AFM simulations using the particle probe model provide a…

Materials Science · Physics 2025-09-03 Jie Huang , Niko Oinonen , Fabio Priante , Filippo Federici Canova , Lauri Kurki , Chen Xu , Adam S. Foster

Precise modelling of a signal in processes with multiple observables, exhibiting a complex dependency on the underlying parameters, is often a difficult and challenging task. Predicting the results of experimental measurements in…

High Energy Physics - Phenomenology · Physics 2025-12-16 Nikita Belyaev , Rostislav Konoplich , Kirill Prokofiev

Preparing realistic atom-scale models of amorphous silicon (a-Si) is a decades-old condensed matter physics challenge. Herein, we combine the Activation Relaxation Technique nouveau (ARTn) to a Moment Tensor Potential (MTP) to generate…

Disordered Systems and Neural Networks · Physics 2025-03-25 Karim Zongo , Hao Sun , Claudiane Ouellet-Plamondon , Normand Mousseau , Laurent Karim Béland

Polymorphism is ubiquitous in crystalline solids. Amorphous solids, such as glassy water and silicon, may undergo amorphous-to-amorphous transitions (AATs). The nature of AATs remains ambiguous, due to diverse system-dependent behaviors and…

Machine learning (ML) of quantum mechanical properties shows promise for accelerating chemical discovery. For transition metal chemistry where accurate calculations are computationally costly and available training data sets are small, the…

Materials Science · Physics 2017-11-07 Jon Paul Janet , Heather J. Kulik

Crack-templated networks, metallic frameworks fabricated from crack patterns in sacrificial thin films, can exhibit high optical transmittance, high electric conductivity, and a host of other properties attractive for applications. Despite…

Applied Physics · Physics 2022-06-08 Jaeuk Kim , Thomas M. Truskett

Alternating patterns of small and large amplitude oscillations occur in a wide variety of physical, chemical, biological and engineering systems. These mixed-mode oscillations (MMOs) are often found in systems with multiple time scales.…

Dynamical Systems · Mathematics 2014-06-24 Christian Kuehn

Predictive computational modeling of polymer materials is necessary for the efficient design of composite materials and the corresponding processing methods. Molecular dynamics (MD) modeling is especially important for establishing accurate…

Materials Science · Physics 2021-11-23 G. M. Odegard , S. U. Patil , P. Deshpande , K. Kanhaiya , J. Winetrout , H. Heinz , S. Shah , M. Maiaru

Complexions are phase-like interfacial features that can influence a wide variety of properties, but the ability to predict which material systems can sustain these features remains limited. Amorphous complexions are of particular interest…

Materials Science · Physics 2017-08-22 Jennifer D. Schuler , Timothy J. Rupert

Topological properties of solid states have sparked considerable recent interest due to their importance in the physics of lattices with a non-trivial basis and their potential in the design of novel materials. Here we describe an…

Applied Physics · Physics 2020-02-19 Henning U. Voss , Douglas J. Ballon

Generative models and machine learning promise accelerated material discovery in MOFs for CO2 capture and water harvesting but face significant challenges navigating vast chemical spaces while ensuring synthetizability. Here, we present…