Results 1 to 10 of about 151 (87)

Multispectral UV Imaging on Capacitive CMOS Arrays Enabled by Solution‐Processed Metal‐Oxide Nanoparticles

Advanced Science, EarlyView.
Ultraviolet (UV) imagers are important for a variety of applications but often require dedicated semiconductor process flows. Here, a versatile capacitive CMOS platform is transformed into a visible‐blind, multispectral UV imager through post‐CMOS functionalization with solution‐processed metal‐oxide nanoparticles. The UV‐induced photodielectric effect
Suman Kundu, Tao Shen, Kai Betlem, Murali K. Ghatkesar, Peter G. Steeneken, Frans P. Widdershoven   +5 more
wiley   +1 more source

Optimized Wavy Thermal Radiative Analysis of Electrochemically Ternary Hybrid Nanomaterials Affected by an Induced Magnetic Force: An ANN‐Based Levenberg–Marquardt Backpropagation Approach

Advanced Physics Research, EarlyView.
This diagram illustrates the wavy flow configuration of the model in a Cartesian coordinate system. It represents the heat and mass transfer characteristics of ternary hybrid nanofluids over a vertically wavy surface in the presence of an induced magnetic field and double‐diffusive mixed convection.
Latif Ahmad, Saleem Javed, Umair Khan, Muhammad Iqbal, Syed Modassir Hussain   +4 more
wiley   +1 more source

Nitric Oxide in Cancer: Mechanisms, Dual Role, and Therapeutic Strategies

MedComm – Oncology, Volume 5, Issue 3, September 2026.
Nitric oxide exerts concentration‐dependent dual roles in cancer, functioning as either a tumor promoter or suppressor. This review comprehensively examines NO's multifaceted regulation of tumor biology, including S‐nitrosylation signaling, metabolic reprogramming, immunemodulation, and therapy resistance, and highlights emerging therapeutic strategies
Jia Shao, Honghua Zhang, Jingyu Chen, Ziyu Qian, Ning Zhang, Yihua Zhang, Hui Ye, Jianbing Wu, Zhangjian Huang   +8 more
wiley   +1 more source

Deep Learning for Protein Modeling: From Single Structure to Bound Complex and Thermodynamic Ensemble, With a Focus on Architectural Design

WIREs Computational Molecular Science, Volume 16, Issue 5, September/October 2026.
Protein deep learning is moving from single structure prediction toward bound complex modeling and conformational ensemble generation. An architectural perspective shows how symmetry, evolutionary information, generative sampling, and energetic grounding shape performance and generalization.
Daniele Angioletti, Matteo Carli, Marco Nobile, Vittorio Limongelli   +3 more
wiley   +1 more source

Numerical Identification of Stationary States and Their Stability in a Model of Quantum Droplets

Studies in Applied Mathematics, Volume 157, Issue 3, September 2026.
ABSTRACT In this work, we are motivated by a recent variant of the nonlinear Schrödinger (NLS) equation describing cold, dilute atomic condensates with quantum fluctuation effects. Our goal is to develop robust numerical methods capable of uncovering diverse stationary solutions in such NLS models.
Sun Lee, Panayotis G. Kevrekidis, Wenrui Hao   +2 more
wiley   +1 more source

Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic

Communications on Pure and Applied Mathematics, Volume 79, Issue 8, Page 1973-2102, August 2026.
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley   +1 more source

Nordgren PINNs to VQE: Advancing Hydraulic Fracturing Simulations in Shale Reservoirs

International Journal for Numerical and Analytical Methods in Geomechanics, Volume 50, Issue 12, Page 4863-4878, 25 August 2026.
ABSTRACT This study advances hydraulic fracturing simulations in shale reservoirs using two computational paradigms, Physics‐Informed Neural Networks (PINNs) and the Variational Quantum Eigensolver (VQE). PINNs were employed to solve Nordgren's equation, which governs fracture width evolution, by embedding physical laws into the neural network ...
Dennis Delali Kwesi Wayo, Sonny Irawan, Mohd Zulkifli Bin Mohamad Noor, Mudasar Zafar, Shynar Juziyeva, Camila Martins Saporetti, Leonardo Goliatt, Randy Hazlett   +7 more
wiley   +1 more source

Efficient Tensor Completion Algorithms for Highly Oscillatory Operators

Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.
ABSTRACT We address the problem of recovering highly oscillatory operators, represented as n×n$$ n\times n $$ matrices with a fixed set of observed entries. Given that these matrices can be well compressed by butterfly matrix decomposition of L=𝒪(logn) levels requiring only O(nlogn)$$ O\left(n\log n\right) $$ degrees of freedom, we propose a novel ...
Navjot Singh, Edgar Solomonik, Xiaoye Sherry Li, Yang Liu   +3 more
wiley   +1 more source

Synergistic Engineering of Nanostructures via Anodic Aluminum Oxide Templates and Atomic Layer Deposition: Design Principles, Mechanisms, and Applications

Small Structures, Volume 7, Issue 8, August 2026.
Anodic aluminum oxide (AAO) templates combined with atomic layer deposition (ALD) constitute a synergistic platform for engineering functional nanostructures within highly ordered, high‐aspect‐ratio porous architectures. By linking precursor transport modeling, surface chemistry control, and tailored ALD strategies, this review establishes a unified ...
Hyeon Joon Choi, Neul Ha, Jisu Jung, Ryeowon Kim, S. Joon Kwon, Sunghak Park, Wooseok Yang, Hyunjung Shin   +7 more
wiley   +1 more source

Modeling Transient Flow in Heterogeneous Aquifers With the Mixed Pressure‐Velocity Formulation of Physics Informed Neural Networks

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Physics‐Informed Neural Networks (PINNs) have emerged as a powerful framework for modeling groundwater flow using deep learning neural networks, particularly in scenarios where traditional data‐driven approaches are limited by the scarcity of data.
Adhish Virupaksha, Marwan Fahs, Hussein Hoteit, Thomas Nagel, François Lehmann   +4 more
wiley   +1 more source