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The article considers the simulation of the formation of a multilayer nanocomposite, the combination of elements of which gives rise to the effect of a spin valve. The relevance and importance of the effects in the field of spintronics and…
Advanced manufacturing (AM) technologies, such as nanoscale additive manufacturing process, enable the fabrication of nanoscale architected materials which has received great attention due to their prominent properties. However, few studies…
A supervised machine learning (ML) based computational methodology for the design of particulate multifunctional composite materials with desired thermal conductivity (TC) is presented. The design variables are physical descriptors of the…
Owing to the excellent catalysis properties of Ag-Au binary nanoalloy, nanostructured Ag-Au, such as Ag-Au nanoparticles and nanopillars, have been under intense investigation. To achieve high accuracy in molecular simulations of the Ag-Au…
Tailoring the performance of next-generation high entropy materials requires a deep understanding of the competition between entropy-driven random solid solution and enthalpy-driven chemical ordering. Investigating such order and disorder…
The work is devoted to the study of the processes of formation and analysis of the parameters of a functional nanostructure -- a superconducting spin valve, which is a multilayer structure consisting of ferromagnetic cobalt nanofilms…
This chapter presents an innovative framework for the application of machine learning and data analytics for the identification of alloys or composites exhibiting certain desired properties of interest. The main focus is on alloys and…
We investigated the complete thermodynamic cycle of aluminium nanoparticles through classical molecular dynamics simulations, spanning a wide size range from 200 atoms to 11000 atoms. The aluminium-aluminium interactions are modelled using…
Amorphous silicon (a-Si) is a widely studied non-crystalline material, and yet the subtle details of its atomistic structure are still unclear. Here, we show that accurate structural models of a-Si can be obtained by harnessing the power of…
The thermodynamics and kinetics of crystallization of nanoparticles, as opposed to bulk phases, may be influenced by surface and size effects. We investigate the importance of such factors in the crystallization process of gold, silver, and…
Except serving as an excellent gift on proper occasions, gold finds applications in life sciences, particularly in diagnostics and therapeutics. These applications were made possible by gold nanoparticles, which differ drastically from…
Aluminum alloys, the most widely utilized lightweight structural materials, predominantly depend on coherent complex-structured nano-plates to enhance their mechanical properties. Despite several decades of research, the atomic-scale…
The ability to design synthesis processes that are out of equilibrium has opened the possibility of creating nanomaterials with remarkable physico-chemical properties, choosing from a much richer palette of possible atomic architectures…
Metallography is crucial for a proper assessment of material's properties. It involves mainly the investigation of spatial distribution of grains and the occurrence and characteristics of inclusions or precipitates. This work presents an…
The development of new engineering alloy chemistries is a time consuming and iterative process. A necessary step is characterization of the nano/microstructure to provide a link between the processing and properties of each alloy chemistry…
Microstructure--property relationships are key to effective design of structural materials for advanced applications. Advances in computational methods enabled modeling microstructure-sensitive properties using 3D models (e.g., finite…
The details of phase separation of a Ni-6.5Al-9.9Mo aged at 978 K for aging times ranging from 0.125 to 1024 h are investigated by atom-probe tomography and lattice-kinetic Monte Carlo (LKMC) simulations. On the basis of the temporal…
Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML…
We propose tabular two-dimensional correlation analysis for extracting features from multifaceted characterization data, essential for understanding material properties. This method visualizes similarities and phase lags in structural…
Cryo-electron microscopy (cryo-EM) has become a major experimental technique to determine the structures of large protein complexes and molecular assemblies, as evidenced by the 2017 Nobel Prize. Although cryo-EM has been drastically…