Results 81 to 90 of about 212,411 (244)
Untangling Inositol (Pyro)Phosphate Biology Through Emerging Technologies
Inositol (pyro)phosphates represent a vital class of intracellular messengers that govern multiple biological processes. The last decade has experienced a surge of interest in the functions of this class of signaling molecules, primarily due to the introduction of several innovative analytical technologies.
Adolfo Saiardi +5 more
wiley +1 more source
Computational and structure‐guided arginine scanning rewires the DNA‐binding interface of APE1 to create APE1‐Evo, a hyperactive yet specific AP endonuclease. Integrated into the NAPTUNE‐V2.0 cascade, APE1‐Evo enables amplification‐free, multiplex viral RNA sensing for dengue virus and influenza A/B, highlighting a general strategy for engineering ...
Junlan Wang +20 more
wiley +1 more source
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
ABSTRACT Layered 2D materials are considered as promising for memristive applications due to their ultimate vertical scalability compared to conventional semiconductor films and pronounced hysteresis properties. Bias‐resolved Raman and Photoluminescence mapping is used to quantify strain from phonon shifts and carrier density from the exciton‐trion ...
Vladislav Kurtash +4 more
wiley +1 more source
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source
From Flexible to Conformable Pressure Sensors: Mechanisms, Materials, and Biomedical Applications
This review highlights recent progress, challenges and future opportunities in pressure sensing for advanced biomedical applications. We summarize key transduction mechanisms and emerging material strategies, discuss representative wearable and implantable applications for continuous physiological monitoring and provide a focused perspective on barrier
Rishabh B. Mishra +2 more
wiley +1 more source
Environmental Effects on RRAM Cells Based on 2D Halide Perovskite Materials
RRAM offers high speed, scalability, and low power, positioning it as a next‐generation non‐volatile memory. Two‐dimensional halide perovskites show promise due to tunable optoelectronic properties and flexible processing but suffer from environmental sensitivity. This review examines degradation from humidity, temperature, light, and strain, discusses
Mojtaba Joodaki +3 more
wiley +1 more source
Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee +3 more
wiley +1 more source
Emerging Materials and Future Strategies for Solid Oxide Electrochemical Cells
Solid oxide electrochemical cells operate under strongly coupled electrochemical and thermodynamic conditions, where performance is constrained by interactions among crystal structure, defect chemistry, and interfacial evolution. This review, based on a structure‐defect‐property‐durability framework, reveals the roles of lattice symmetry and defect ...
Qiuchun Lu +4 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source

