Results 121 to 130 of about 1,153,224 (274)
IEEE AccessThe experimental identification of an unknown system, and the blind system identification (BSI) methods, allows engineers to establish mathematical models that represent the real system behavior.
C. A. L. Segura
doaj +1 more source
Advanced Materials, EarlyView.This work explores the MOF landscape to select a single, optimal candidate for successfully delivering cancer drugs (gemcitabine, paclitaxel, SN‐38) into tough pancreatic tumors. Machine learning and simulations guide this search, demonstrating colloidal stability, excellent biocompatibility, cellular uptake, and sustained release.
Francesca Melle +9 more
wiley +1 more source
A Bio‐Inspired Perspective on Materials Sustainability
Advanced Materials, EarlyView.This perspective discusses natural materials as inspiration for sustainable engineering designs and the processing of materials. First, circularity, longevity, parsimony, and activity are presented as essential material paradigms. The perspective then uses many examples of natural and technical materials to introduce principles such as oligo ...
Wolfgang Wagermaier +2 more
wiley +1 more source
Advanced Materials, EarlyView.The SciAgents AI model drives hypothesis generation by harnessing multi‐agent graph reasoning, extracting insights from knowledge graphs constructed from scientific papers. Each agent plays a specific role: the Ontologist defines concepts, the Scientists draft and refine proposals, and the Critic reviews.
Alireza Ghafarollahi, Markus J. Buehler
wiley +1 more source
Advanced Materials, EarlyView.The rise of lead halide perovskite semiconductors has enabled high‐performance LEDs with internal quantum efficiencies approaching 100%. In order to further enhance the external quantum efficiencies limited by light outcoupling effects, in this account, the strategies for reducing energy dissipation through the substrate, waveguide, and evanescent ...
Tommaso Marcato +2 more
wiley +1 more source
Is Algorithmic Stability Testable? A Unified Framework under Computational Constraints [PDF]
arXivAlgorithmic stability is a central notion in learning theory that quantifies the sensitivity of an algorithm to small changes in the training data. If a learning algorithm satisfies certain stability properties, this leads to many important downstream implications, such as generalization, robustness, and reliable predictive inference.
arxiv
Advanced Materials, EarlyView.This review describes recent developments in the design and synthesis of metal–organic frameworks (MOF)/textile composites for the detoxification of chemical warfare agent and simulants with extensive discussion on the advantages and disadvantages of different methods.
Zhihua Cheng +4 more
wiley +1 more source
Kernel-Based Learning of Stable Nonlinear Systems [PDF]
arXivLearning models of dynamical systems characterized by specific stability properties is of crucial importance in applications. Existing results mainly focus on linear systems or some limited classes of nonlinear systems and stability notions, and the general problem is still open.
arxiv
Advanced Materials, EarlyView.Protein can undergo liquid–liquid phase separation and liquid‐to‐solid transition to form liquid condensates and solid aggregates. These phase transitions can be influenced by post‐translational modifications, mutations, and various environmental factors.
Tianchen Li +3 more
wiley +1 more source
Adsorption and Separation by Flexible MOFs
Advanced Materials, EarlyView.Flexible metal–organic frameworks (MOFs) present significant potential for gas storage and separation due to their structural dynamic. This review explores the rationale behind the flexible MOFs' enhanced working capacity and separation factors. It also addresses key challenges, including phase transition kinetics, crystal robustness, cycling, shaping,
Irena Senkovska +4 more
wiley +1 more source