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High throughput experimental methods are known to accelerate the rate of research, development, and deployment of electronic materials. For example, thin films with lateral gradients in composition, thickness, or other parameters have been…

Applied Physics · Physics 2020-02-19 Yanbing Han , Sage Bauers , Qun Zhang , Andriy Zakutayev

Efficient synthesis recipes are needed both to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Oftentimes the solid-state synthesis of multicomponent oxides is…

Materials Science · Physics 2024-04-10 Jiadong Chen , Samuel R. Cross , Lincoln J. Miara , Jeong-Ju Cho , Yan Wang , Wenhao Sun

Electron transfer with changing occupation in the 4f subshell poses a considerable challenge for quantitative predictions in quantum chemistry. Using the example of cerium oxide, we identify the main deficiencies of common…

Chemical Physics · Physics 2021-12-07 Tobias Schäfer , Nathan Daelman , Núria López

Split computing ($\neq$ split learning) is a promising approach to deep learning models for resource-constrained edge computing systems, where weak sensor (mobile) devices are wirelessly connected to stronger edge servers through channels…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Yoshitomo Matsubara , Matteo Mendula , Marco Levorato

Material research is a key frontier in advancing superconducting qubit and circuit performance. In this work, we develop a simple and broadly applicable framework for accurately characterizing two-level system (TLS) loss using internal…

Superconductivity · Physics 2025-07-17 Guy Moshel , Sergei Masis , Moshe Schechter , Shay Hacohen-Gourgy

Transition metal (TM) oxides play an increasingly important role in technology today including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic…

Materials Science · Physics 2015-09-30 Dong-Hwa Seo , Alexander Urban , Gerbrand Ceder

Designing superconducting quantum hardware requires simulation tools that can account for various deviations from ideal scenarios. This, in turn, requires approaches that automatically detect certain structures and leverage them to make the…

Quantum Physics · Physics 2026-05-28 Adrien Moulinas , Xavier Waintal

Molecular dynamics simulations are a powerful tool to study diffusion processes in battery electrolyte and electrode materials. From a single molecular dynamics simulation many properties relevant to diffusion can be obtained, including the…

Chemical Physics · Physics 2018-07-09 Niek J. J. de Klerk , Eveline van der Maas , Marnix Wagemaker

Understanding strongly correlated systems is essential for advancing quantum chemistry and materials science, yet conventional methods like Density Functional Theory (DFT) often fail to capture their complex electronic behavior. To address…

Chemical Physics · Physics 2025-09-01 Archith Rayabharam , N. R. Aluru

Defect engineering is a key strategy to control resistive switching (RS) in oxide-based memristive devices, where oxygen vacancy (OV) dynamics governs filament formation and rupture. We investigate the effect of Ag nanoparticles (AgNPs)…

Mesoscale and Nanoscale Physics · Physics 2026-03-02 R. Leal Martir , A. J. T. van der Ree , M. H. Aguirre , G. Palasantzas , D. Rubi , M. J. Sánchez

Quantum processors using superconducting qubits suffer from dielectric loss leading to noise and dissipation. Qubits are usually designed as large capacitor pads connected to a non-linear Josephson junction (or SQUID) by a superconducting…

Alternative computing paradigms open the door to exploiting recent innovations in computational hardware to probe the fundamental thermodynamic limits of information processing. One such paradigm employs superconducting quantum interference…

Statistical Mechanics · Physics 2024-07-03 Christian Z. Pratt , Kyle J. Ray , James P. Crutchfield

The lack of a mechanistic framework for chemical reactions forming inorganic extended solids presents a challenge to accelerated materials discovery. We demonstrate here a combined computational and experimental methodology to tackle this…

The dielectric environment surrounding semiconductors plays a crucial role in determining device performance, a role that becomes especially pronounced in atomically thin semiconductors where charge carriers are confined within a few atomic…

Twisted oxide membranes represent a promising platform for exploring moire physics and emergent quantum phenomena. However, the presence of amorphous interfacial dead layers in conventional oxide heterostructures impedes coherent coupling…

Materials Science · Physics 2026-01-30 Young-Hoon Kim , Reza Ghanbari , Min-Hyoung Jung , Young-Min Kim , Ruijuan Xu , Miaofang Chi

The precipitous rise of consumer network applications reiterates the urgency to redefine computing hardware with low power footprint. Neuromorphic computing utilizing correlated oxides offers an energy-efficient solution. By designing…

Niobium offers the benefit of increased operating temperatures and frequencies for Josephson junctions, which are the core component of superconducting devices. However existing niobium processes are limited by more complicated fabrication…

Quantum Physics · Physics 2024-02-23 Alexander Anferov , Kan-Heng Lee , Fang Zhao , Jonathan Simon , David I. Schuster

As networks advance toward the Sixth Generation (6G), management of high-speed and ubiquitous connectivity poses major challenges in meeting diverse Service Level Agreements (SLAs). The Zero Touch Network (ZTN) framework has been proposed…

Networking and Internet Architecture · Computer Science 2025-04-01 Tamizhelakkiya K , Dibakar Das , Jyotsna Bapat , Debabrata Das , Komal Sharma

Layered transition metal oxides (TMO) are widely used as cathode materials in Na/Li batteries. The open-circuit voltage (OCV), which determines the energy density (together with capacity), is among the key physical and chemical factors…

Materials Science · Physics 2025-07-17 Sourav Baiju , Konstantin Köster , Mark Huijben , Payam Kaghazhi

Meta-learning algorithms for active learning are emerging as a promising paradigm for learning the ``best'' active learning strategy. However, current learning-based active learning approaches still require sufficient training data so as to…

Machine Learning · Computer Science 2019-09-10 Jingyu Shao , Qing Wang , Fangbing Liu