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The discovery of high-$T_c$ conventional superconductivity in high-pressure hydrides has helped establish computational methods as a formidable tool to guide material discoveries in a field traditionally dominated by serendipitous…
Safety alignment in large language models (LLMs) is commonly implemented as a single static policy embedded in model parameters. However, real-world deployments often require context-dependent safety rules that vary across users, regions,…
Reliably ensuring Large Language Models (LLMs) follow complex instructions is a critical challenge, as existing benchmarks often fail to reflect real-world use or isolate compliance from task success. We introduce MOSAIC (MOdular Synthetic…
Motivated by the recent report of superconductivity above 200 K in ultra-dense hydrogen sulfide, we search for high-\tc\ conventional superconductivity in the phase diagram of the binary Li-S system, using {\em ab-initio} methods for…
Competition between magnetism and superconductivity can lead to unconventional and topological superconductivity. However, the experimental confirmation of the presence of Majorana edge states and unconventional pairing currently poses a…
Superconductor research has traditionally depended on experiments and theoretical approaches. However, the rapid advancement of data-driven methods and machine learning (ML) has opened avenues for accelerating superconductor discovery.…
"Topological Quantum Chemistry (TQC) links the chemical and symmetry structure of a given material with its topological properties. This field tabulates the data of the 10398 real-space atomic limits of materials, and solves the…
The Li$_2$S-P$_2$S$_5$ pseudo-binary system has been a valuable source of promising superionic conductors, with $\alpha$-Li$_3$PS$_4$, $\beta$-Li$_3$PS$_4$, HT-Li$_7$PS$_6$, and Li$_7$P$_3$S$_{11}$ having excellent room temperature Li-ion…
The concept of topological superconductivity has attracted immense interest in the physics community recently for several reasons: First, topological superconductors represent new phases of matter, topologically distinct from any other…
Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine cycler telemetry without access to the degradation region. We introduce…
Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and…
Machine learning interatomic potentials (MLIPs) offer near-ab initio accuracy with the efficiency of classical force fields, making them attractive for modeling electrolytes. Collecting a diverse training set is essential for their accuracy…
Ion transport in concentrated electrolytes plays a fundamental role in electrochemical systems such as lithium ion batteries. Nonetheless, the mechanism of transport amid strong ion-ion interactions remains enigmatic. A key question is…
The search for hydride compounds that exhibit high $T_c$ superconductivity has been extensively studied. Within the range of binary hydride compounds, the studies have been developed well including data-driven searches as a topic of…
This paper presents a method for achieving equilibrium in the ISING Hamiltonian when confronted with unevenly distributed charges on an irregular grid. Employing (Multi-Edge) QC-LDPC codes and the Boltzmann machine, our approach involves…
The International Large Detector (ILD) is a concept for a detector at the International Linear Collider, ILC. The ILC will collide electrons and positrons at energies of initially 500 GeV, upgradeable to 1 TeV. The ILC has an ambitious…
Single Positive Multi-Label Learning (SPMLL) addresses the challenging scenario where each training sample is annotated with only one positive label despite potentially belonging to multiple categories, making it difficult to capture…
Continual learning (CL) learns a sequence of tasks incrementally. There are two popular CL settings, class incremental learning (CIL) and task incremental learning (TIL). A major challenge of CL is catastrophic forgetting (CF). While a…
Colossal Ion Conductivity (CIC) is the phenomenon in which large changes in oxygen conductivity are observed when a solid state oxygen electrolyte is placed in a heterolayer super lattice. Several hypotheses have been posed concerning both…
Layered hybrid halide compounds offer promising functional properties, particularly tunable band gaps, conductivity, light harvesting thus making them prospective for applications in photovoltaics and optoelectronics. This study exemplifies…