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Compressive-shear fracture is commonly observed in rock-like materials. However, this fracture type cannot be captured by current phase field models (PFMs), which have been proven an effective tool for modeling fracture initiation,…
Ferromagnetic electrodes chemically bonded with thiol functionalized molecules can produce novel molecular spintronics devices. However, major challenges lie in developing Ferromagnetic electrodes based commercially viable device…
The electronics and semiconductor industry is a prominent consumer of per- and poly-fluoroalkyl substances (PFAS), also known as forever chemicals. PFAS are persistent in the environment and can bioaccumulate to ecological and human toxic…
Various aspects of the methods of physical and physicochemical modification of components of filled thermoplastic composite materials are analyzed, aimed at improving the surface properties of the fillers and the technological properties of…
Phosphorene, the single- or few-layer form of black phosphorus, was recently rediscovered as a twodimensional layered material holding great promise for applications in electronics and optoelectronics. Research into its fundamental…
Fatigue properties of additively manufactured (AM) materials depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluation inevitably requires…
In this contribution to the special issue on magnetoelectrics and their applications, we focus on some single phase multiferroics theoretically predicted and/or experimentally discovered by the authors in recent years. In these materials,…
Discrete Fourier transforms~(DFTs) over finite fields have widespread applications in digital communication and storage systems. Hence, reducing the computational complexities of DFTs is of great significance. Recently proposed cyclotomic…
Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the…
Matrix factorization (MF) is a versatile learning method that has found wide applications in various data-driven disciplines. Still, many MF algorithms do not adequately scale with the size of available datasets and/or lack…
Ferroics and multiferroics are unique objects for fundamental physical research of complex nonlinear processes and phenomena, which occur in them in micro and nanoscale. Due to the possibility of their physical properties control by size…
Recent metamaterial (MM) research faces several problems when using metal-based plasmonic components as building blocks for MMs. The use of conventional metals for MMs is limited by several factors: metals such as gold and silver have high…
Functionally graded materials (FGMs) represent a promising class of advanced materials designed with tailored microstructures to achieve optimized mechanical, thermal, and functional properties across varying gradients. The strategic…
Multicomponent alloying has displayed extraordinary potential for producing exceptional structural and functional materials. However, the synthesis of single-phase, multi-principal covalent compounds remains a challenge. Here we present a…
Most state-of-the-art top-N collaborative recommender systems work by learning embeddings to jointly represent users and items. Learned embeddings are considered to be effective to solve a variety of tasks. Among others, providing and…
Preconditioning is a key component of MCMC algorithms that improves sampling efficiency by facilitating exploration of geometrically complex target distributions through an invertible map. While linear preconditioners are often sufficient…
Metal-organic frameworks (MOFs) are constructed from a combination of inorganic and organic units to produce materials which display high porosity, among other unique and exciting properties. MOFs have shown promise in many wide-ranging…
Although the tailored metal active sites and porous architectures of MOFs hold great promise for engineering challenges ranging from gas separations to catalysis, a lack of understanding of how to improve their stability limits their use in…
Cyclotomic fast Fourier transforms (CFFTs) are efficient implementations of discrete Fourier transforms over finite fields, which have widespread applications in cryptography and error control codes. They are of great interest because of…
While copper-graphene (Cu/Gr) composites have been promising materials due to their theoretically high strength and conductivity, their design has been hampered by the large number of variables affecting their properties. We applied four…