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Although 19F has high potential to serve as a background-free molecular marker in bioimaging, the molar amount of marker substance is often too small to enable 19F MR imaging or 19F NMR spectroscopy with a sufficiently high signal-to-noise…

Chemical Physics · Physics 2022-05-24 Johannes Bernarding , Christian Bruns , Isabell Prediger , Markus Plaumann

Nuclear physics experiments are always in need of more and more advanced detection systems. During the last years relevant technological developments have come out with many improvements in terms of performance and compactness of detector…

Instrumentation and Detectors · Physics 2021-01-26 Paolo Finocchiaro

The combination of a powerful and broadly applicable nuclear hyperpolarization technique with emerging (near-)zero-field modalities offer novel opportunities in a broad range of nuclear magnetic resonance spectroscopy and imaging…

Over recent decades, the value of conducting experiments at lower frequencies and in inhomogeneous and/or time-variable fields has grown. For example, an interest in the nanoscale heterogeneities of hydration dynamics demands increasingly…

Chemical Physics · Physics 2022-11-23 Alec A. Beaton , Alexandria Guinness , John M. Franck

Electrochemical impedance spectra for battery electrodes are usually interpreted using models that assume isotropic active particles, having uniform current density and symmetric diffusivities. While this can be reasonable for amorphous or…

Chemical Physics · Physics 2013-09-24 J. Song , M. Z. Bazant

Efficient polarization of organic molecules is of extraordinary relevance when performing nuclear magnetic resonance (NMR) and imaging. Commercially available routes to dynamical nuclear polarization (DNP) work at extremely…

Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…

Materials Science · Physics 2021-10-06 Jian-Min Zuo , Renliang Yuan , Yu-Tsun Shao , Haw-Wen Hsiao , Saran Pidaparthy , Yang Hu , Qun Yang , Jiong Zhang

The recently published DeePMD model (https://github.com/deepmodeling/deepmd-kit), based on a deep neural network architecture, brings the hope of solving the time-scale issue which often prevents the application of first principle molecular…

Computational Physics · Physics 2019-10-23 Aris Marcolongo , Tobias Binninger , Federico Zipoli , Teodoro Laino

Proton exchange membrane fuel cells hold promise as energy conversion devices for hydrogen-based power generation and storage. However, the slow kinetics of the oxygen reduction at the cathode imposes the need for highly active catalysts,…

Materials Science · Physics 2023-03-21 Se-Ho Kim , Hosun Jun , Kyuseon Jang , Pyuck-Pa Choi , Baptiste Gault , Chanwon Jung

Wireless sensor networks (WSNs) have become a promising solution for structural health monitoring (SHM), especially in hard-to-reach or remote locations. Battery-powered WSNs offer various advantages over wired systems, however limited…

Machine Learning · Computer Science 2025-03-25 Jong-Hyun Jeong , Hongki Jo , Qiang Zhou , Tahsin Afroz Hoque Nishat , Lang Wu

Supported metal nanoparticle (NP) catalysts are vital for the sustainable production of chemicals, but their design and implementation are limited by the ability to identify and characterize their structures and atomic sites that are…

A deep learning model is employed to address the challenging problem of V2O5 nanoparticle segmentation and the correlation between the chemical composition and the geometrical features of lithiated V2O5 nanoparticles as an exemplar of a…

Accurate forecasting of battery health indicators, including remaining capacity and lifetime, is of paramount importance for ensuring the reliability, safety, and operational efficiency of applications such as electric vehicles and large…

Signal Processing · Electrical Eng. & Systems 2026-05-29 Athanasios Koukosias , Vasileios Tzanidakis , Sotiris Athanasiou , Kostas Kolomvatsos

Optical neural networks are emerging as a powerful and versatile tool for processing optical signals directly in the optical domain with superior speed, integrability, and functionality. Their application to optical polarization enables…

Optics · Physics 2025-06-24 Alessandro Petrini , Claudio Conti , Davide Pierangeli

Deep neural networks (DNNs) have been expanded into medical fields and triggered the revolution of some medical applications by extracting complex features and achieving high accuracy and performance, etc. On the contrast, the large-scale…

Image and Video Processing · Electrical Eng. & Systems 2019-11-07 Hongjia Li , Sheng Lin , Ning Liu , Caiwen Ding , Yanzhi Wang

Magnetic resonance imaging in ultra-low fields is often limited by mediocre signal-to-noise ratio hindering a higher resolution. Overhauser dynamic nuclear polarisation (O-DNP) using nitroxide radicals has been an efficient solution for…

We elaborate the possibility of using the atomic radiative emission of neutrino pair (RENP) to probe the neutrino electromagnetic properties, including magnetic and electric dipole moments, charge radius, and anapole. With the typical O(eV)…

High Energy Physics - Phenomenology · Physics 2023-12-22 Shao-Feng Ge , Pedro Pasquini

The adsorption of DNA or other polyelectrolyte molecules on charged membranes is a recurrent motif in soft matter and bionanotechnological systems. Two typical situations encountered are the deposition of single DNA chains onto substrates…

Soft Condensed Matter · Physics 2016-10-19 Sahin Buyukdagli , Ralf Blossey

Fast and reliable validation of novel designs in complex physical systems such as batteries is critical to accelerating technological innovation. However, battery research and development remain bottlenecked by the prohibitively high time…

Machine Learning · Computer Science 2025-09-26 Jiawei Zhang , Yifei Zhang , Baozhao Yi , Yao Ren , Qi Jiao , Hanyu Bai , Weiran Jiang , Ziyou Song

Neutrinoless double beta-decay(DBD) is of current interest in high-sensitivity frontiers of particle physics. The decay is very sensitive to Majorana neutrinos masses, neutrino CP phases, right-handed weak interactions and others, which are…

Nuclear Experiment · Physics 2020-12-14 Hiroyasu Ejiri