Results 81 to 90 of about 553 (265)

Magnetoelectric Nanoparticles Enable Modulation of Cortical Networks by Low‐Intensity Static Magnetic Fields In Vitro

Advanced Science, EarlyView.
Neuromodulation strategies are increasingly needed to stimulate, restore, or replace altered neuronal activity in disease. Cobalt ferrite‐barium titanate (CFO–BTO) magnetoelectric nanoparticles convert low‐intensity static magnetic fields into local electrical modulation of cortical networks.
Nathalia Cancino‐Fuentes, Alejandro Suarez‐Perez, Elric Zhang, Hao Ye, Marta Bonato, Joana Covelo, Vitaly Pustovalov, Anton Guimera‐Brunet, Xavi Illa, Valentin Gantenbein, Cagatay M. Oral, Marta Parazzini, Salvador Pané, Maria V. Sanchez‐Vives   +13 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Not All Agreements Are Equal: Heterogeneous Effects of RTAs on Latin American Agri‐Food Exports, 1990–2019

Agribusiness, EarlyView.
ABSTRACT Since the final decade of the 20th century, Latin American countries have increasingly regarded the signing of regional trade agreements (RTAs) as a promising strategy for expanding their exports. Within this context, the main objective of this study is to assess the impact of RTAs on agri‐food exports in Latin America over the period 1990 ...
María‐Isabel Ayuda, Ignacio Belloc, Vicente Pinilla   +2 more
wiley   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

The approximate solution of a class of Fredholm integral equations with a weakly singular kernel

Journal of Computational and Applied Mathematics, 2011
The authors consider weakly singular integral equations and singular integral equations as \[ a(x) \varphi(x) + b(x)\int\limits^1_{-1} \frac{\varphi(y)}{(y-x)^\alpha}dy = f(x), \, |x| < 1, \, 0< \alpha \leq 1, \tag{1} \] where \(\varphi(x)\) is the unknown function. A method for finding the numerical solution of equation (1) is presented.
Esmail Babolian, A. Arzhang Hajikandi
openaire   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering

Advanced Intelligent Systems, EarlyView.
Robust feature discovery in incomplete multi‐view clustering is achieved by coupling RPCA‐based clean representation recovery with neural‐network‐assisted graph learning. The resulting RIMVC framework constructs cleaner and more discriminative graph‐structured representations from incomplete and noisy multi‐view data, improving clustering robustness ...
Ping Hu, Chenggang Lu, Rui Zhang, Haijun Yan, Yesong Xu   +4 more
wiley   +1 more source