Results 141 to 150 of about 1,147,666 (317)
Heterojunctions combining halide perovskites with low‐dimensional materials enhance optoelectronic devices by enabling precise charge control and improving efficiency, stability, and speed. These synergies advance flexible electronics, wearable sensors, and neuromorphic computing, mimicking biological vision for real‐time image analysis and intelligent
Yu‐Jin Du+11 more
wiley +1 more source
Flow‐Induced Vascular Remodeling on‐Chip: Implications for Anti‐VEGF Therapy
Flow‐induced vascular remodeling plays a critical role in network stabilization and function. Using a vasculature‐on‐chip system, this study reveals how physiological VEGF levels and flow affect vascular remodeling and provides insights into tumor vessel normalization.
Fatemeh Mirzapour‐Shafiyi+6 more
wiley +1 more source
Machine Learning Accelerates Raman Computations from Molecular Dynamics for Materials Science
Raman spectroscopy is a powerful experimental technique for characterizing molecules and materials that is used in many laboratories. First-principles theoretical calculations of Raman spectra are important because they elucidate the microscopic effects underlying Raman activity in these systems.
Egger, David A.+2 more
openaire +2 more sources
High‐Performance Millimeter Scale Electromagnetic Generator
A high‐performance millimeter‐scale electromagnetic generator (mmEMG) is developed using magnetic flux concentrator (MFC) films on both coil ends to enhance magnetic flux. Through simulations and experiments, structural and magnetic properties are optimized, achieving a 5.6‐fold electrical output improvement.
Jin Pyo Lee+5 more
wiley +1 more source
Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery
This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer+10 more
wiley +1 more source
Atomic Size Misfit for Electrocatalytic Small Molecule Activation
This review explores the application and mechanisms of atomic size misfit in catalysis for small molecule activation, focusing on how structural defects and electronic properties can effectively lower the energy barriers of chemical bonds in molecules like H2O, CO2, and N2.
Ping Hong+3 more
wiley +1 more source
Implementation of a Computer Science Career Guidance Website that Makes Use of Machine Learning
Parth Lokhande+4 more
openalex +1 more source
Machine Learning Guided Design of Nerve‐On‐A‐Chip Platforms with Promoted Neurite Outgrowth
Compared to labor‐intensive trial‐and‐error experimentation, a machine learning (ML)‐guided workflow, incorporating cell viability assays, data augmentation, ensemble modeling, and model interpretation, is developed to accelerate nerve‐on‐a‐chip optimization and uncover data‐driven design principles.
Tsai‐Chun Chung+8 more
wiley +1 more source
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto+8 more
wiley +1 more source
Bimetallic Nanoparticles as Cocatalysts for Photocatalytic Hydrogen Production
Recent developments have introduced bimetallic nanoparticles as effective cocatalysts for photocatalytic systems. This review explores the rapidly expanding research on bimetallic cocatalysts for photocatalytic production of hydrogen, emphasizing the creation of carrier‐selective contacts, localized surface plasmon resonance effects, methodologies for ...
Yufen Chen+4 more
wiley +1 more source