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We demonstrate a machine learning approach designed to extract hidden chemistry/physics to facilitate new materials discovery. In particular, we propose a novel method for learning latent knowledge from material structure data in which…
Carbon fiber and graphene-based nanostructures such as carbon nanotubes (CNTs) and defective structures have extraordinary potential as strong and lightweight materials. A longstanding bottleneck has been lack of understanding and…
The iron pnictide and chalcogenide compounds are a subject of intensive investigations due to their high temperature superconductivity.\cite{a-LaFeAsO} They all share the same structure, but there is significant variation in their physical…
High-throughput computational screening has emerged as a critical component of materials discovery. Direct density functional theory (DFT) simulation of inorganic materials and molecular transition metal complexes is often used to describe…
In the presence of strong electronic spin correlations, the hyperfine interaction imparts long-range coupling between nuclear spins. Efficient protocols for the extraction of such complex information about electron correlations via magnetic…
The addition of transition metals (TM) to III-V semiconductors radically changes their electronic, magnetic and structural properties. In contrast to the conventional semiconductor alloys, the lattice parameter in magnetic semiconductor…
In this contribution we would like to revisit the problems of ferromagnetism (F) and antiferromagnetism (AF) in the pure itinerant model. These methods can be extended later to the superconducting materials. In our model we assume the…
Iron, cobalt and nickel are archetypal ferromagnetic metals. In bulk, electronic conduction in these materials takes place mainly through the $s$ and $p$ electrons, whereas the magnetic moments are mostly in the narrow $d$-electron bands,…
The landscape of condensed matter physics is facing an unprecedented data surge driven by high-throughput ab initio workflows and rapidly expanding experimental datasets. Traditional first-principles methods such as Density Functional…
It was recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth's anomaly magnetic field immersed in overwhelming complex…
The unusual properties of elemental plutonium have long been a puzzle. It has been suggested that these properties may be related to quantum criticality [G. Chapline, J. L. Smith LA Sci 26 (2000) 1]. In this talk we will describe some…
Development of next-generation electronic devices for applications call for the discovery of quantum materials hosting novel electronic, magnetic, and topological properties. Traditional electronic structure methods require expensive…
Fermionic atoms in an optical superlattice can realize a very peculiar Anderson lattice model in which impurities interact with each other through a discretized set of delocalized levels. We investigate the interplay between Kondo effect…
We have performed Density Functional Theory (DFT) based calculations to investigate the effects of stacking patterns on the electronic and magnetic properties of several Nitride MXenes. MXenes, a relatively new addition to the family of…
This work provides a theoretical exploration of the thermodynamic stability and magnetic behaviour of previously unknown ternary Li AgII F compounds. Convex-hull analysis shows that all predicted structures lie slightly above the LiF plus…
HoNiSi$_{3}$ is an intermetallic compound characterized by two successive antiferromagnetic transitions at $T_{N1} = 6.3$ K and $T_{N2} = 10.4$ K. Here, its zero-field microscopic magnetic structure is inferred from resonant x-ray magnetic…
We performed a systematic search for low-energy structures of binary iron silicide over a wide range of compositions using the crystal structure prediction method based on adaptive genetic algorithm. 36 structures with formation energies…
The electronic structure of magnetic lanthanide atoms is fascinating from a fundamental perspective. They have electrons in a submerged open 4f shell lying beneath a filled 6s shell with strong relativistic correlations leading to a large…
The investigation of magnetic energy landscapes and the search for ground states of magnetic materials using ab initio methods like density functional theory (DFT) is a challenging task. Complex interactions, such as superexchange and…
A novel feature of the iron arsenides is the magnetoelastic coupling between the long wavelength in-plane strains of the lattice and the collective spin fluctuations of the electrons near the magnetic ordering wavevectors. Here, we study…