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Highly sensitive nuclear spin detection is crucial in many scientific areas including nuclear magnetic resonance spectroscopy (NMR), imaging (MRI) and quantum computing. The tiny thermal nuclear spin polarization represents a major obstacle…

The interface plays a critical role in electrochemical systems, driving the development of various theories to investigate properties at nanoscale and microscale levels, including the electrictrochemical double layer (EDL) theory and…

Materials Science · Physics 2025-04-08 Yitao He

The determination of nuclear symmetry energy, and in particular, its density dependence, is a long-standing problem for nuclear physics community. Previous studies have found that the product of electric dipole polarizability $\alpha_D$ and…

Nuclear Theory · Physics 2021-06-09 Zhengzheng Li , Yifei Niu , Wenhui Long

We propose a new, more efficient, and potentially cost effective, solid-state nuclear spin hyperpolarization method combining the Cross Effect mechanism and electron spin optical hyperpolarization in rotating solids. We first demonstrate…

Quantum Physics · Physics 2022-01-25 Frederic Mentink-Vigier , Vinayak Rane , Thierry Dubroca , Krishnendu Kundu

A novel hybrid method based on Mie theory and the Discrete Dipole Approximation (DDA) was developed to study the microscopic parameters governing the optical response of tunable photonic crystals (PC). The method is based on a two-step…

Nuclear Magnetic Resonance (NMR) spectroscopy leverages nuclear magnetization to probe molecules' chemical environment, structure, and dynamics, with applications spanning from pharmaceuticals to the petroleum industry. Despite its utility,…

Image and Video Processing · Electrical Eng. & Systems 2025-10-14 Sen Yan , Fabrizio Gabellieri , Etienne Goffinet , Filippo Castiglione , Thomas Launey

Battery prognostics and health management predictive models are essential components of safety and reliability protocols in battery management system frameworks. Overall, developing a robust and efficient battery model that aligns with the…

Data Analysis, Statistics and Probability · Physics 2022-12-05 Hamed Sadegh Kouhestani , Lin Liu , Ruimin Wang , Abhijit Chandra

The development of high-energy density solid-state batteries is critical for the achievement of carbon neutrality goals and the advancement of clean energy. Still, the fundamental understanding of lithium transport mechanisms and…

Two-dimensional (2D) electronic materials are of significant technological interest due to their exceptional properties and broad applicability in engineering. The transition from nanoscale physics, that dictates their stable…

Analysis of PDEs · Mathematics 2025-09-23 Shoham Sen , Yang Wang , Timothy Breitzman , Kaushik Dayal

Understanding the physics of structurally and chemically complex transition-metal oxide and polyanionic materials such as those used for battery electrodes is challenging, even at the level of pristine compounds. Yet these materials are…

Materials Science · Physics 2018-07-19 Khang Hoang , M D Johannes

Neural network potentials (NNPs) enable large-scale molecular dynamics (MD) simulations of systems containing >10,000 atoms with the accuracy comparable to ab initio methods and play a crucial role in material studies. Although NNPs are…

A deep neural network (DNN) has been developed to generate the distributions of nuclear charge density, utilizing the training data from the relativistic density functional theory and incorporating available experimental charge radii of…

Nuclear Theory · Physics 2024-07-09 Tian Shuai Shang , Hui Hui Xie , Jian Li , Haozhao Liang

The discrete and charge-separated nature of matter - electrons and nuclei - results in local electrostatic fields that are ubiquitous in nanoscale structures and are determined by their shape, material, and environment. Such fields are…

Solid-state electrolytes, by enabling lithium metal anodes, may significantly increase the energy density of current lithium-ion batteries. However, similar to their liquid counterparts, these hard and stiff electrolytes can still be…

Chemical Physics · Physics 2024-10-04 Rajeev Gopal , Longan Wu , Youngju Lee , Jinzhao Guo , Peng Bai

Neutron reflectometry (NR) is a powerful technique to probe surfaces and interfaces. NR is inherently an indirect measurement technique, access to the physical quantities of interest (layer thickness, scattering length density, roughness),…

A cell dynamics method for domain separation of diblock copolymers (DBCPs) interacting with nanoparticles (NPs) whose diffusion coefficients depend on chain configuration is proposed for self-assembly of DBCP/NP composites. Increasing NP…

Materials Science · Physics 2009-04-02 Fabio D. A. Aarao Reis

Nuclear magnetic resonance (NMR) schemes can be applied to micron-, and nanometer-sized samples by the aid of quantum sensors such as nitrogen-vacancy (NV) color centers in diamond. These minute devices allow for magnetometry of nuclear…

Quantum Physics · Physics 2021-07-19 C. Munuera-Javaloy , R. Puebla , J. Casanova

Si nanoparticles (NPs) have been actively developed as a hyperpolarized magnetic resonance imaging (MRI) contrast agent with an imaging window close to one hour. However, the progress in the development of NPs has been hampered by the…

We introduce an adhesion parameter that enables rapid screening for materials interfaces with high adhesion. This parameter is obtained by density functional theory calculations of individual single-material slabs rather than slabs…

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