Results 111 to 120 of about 50,039 (279)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Artificial Intelligence Powers Protein Functional Annotation

Advanced Science, EarlyView.
This review systematically summarizes how artificial intelligence advances protein functional annotation. It organizes existing methods into six unified modeling paradigms and analyzes their applications in Gene Ontology and Enzyme Commission prediction.
Wenkang Wang, Qiurong Yang, Min Zeng, Ruiqing Zheng, Min Li   +4 more
wiley   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
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

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

A New Hybrid Reference Vector and Grid-Based Evolutionary Algorithm for Dynamic Many-Objective Optimization

IEEE Access
Dynamic many-objective optimization problems (DMaOPs) are a class of problems involving more than three objectives. Their objective functions, search space, or constraints may change over time. Dynamic many-objective evolutionary algorithms (DMaOEAs) are
Adamo Henrique Rocha De Oliveira, Gideon Villar Leandro   +1 more
doaj   +1 more source

Assessing Photovoltaic Recycling Capacities and Policy Gaps in the European Union

Advanced Energy and Sustainability Research, EarlyView.
This study maps photovoltaic recycling capacity in the EU and key global regions, highlighting gaps between growing waste volumes and available infrastructure. It combines survey insights and policy analysis to identify recycling bottlenecks and offers recommendations to boost circularity in the solar sector.
Nieves Espinosa, Silvia Bobba, Cynthia E. L. Latunussa, Enrica Leccisi   +3 more
wiley   +1 more source

Economic and Environmental Tradeoffs in Cultivating Short Food Supply Chains With Urban Indoor Agriculture

Agribusiness, EarlyView.
ABSTRACT This study advances the literature on sustainable urban agriculture and alternative sustainable food production systems, which have gained momentum due to the need to strengthen regional food supply chains and meet the growing urban demand for fresh food. Indoor agriculture (IA) holds promise for year‐round cultivation of fresh produce even in
Joseph Seong, H. Christopher Peterson, Simone Valle de Souza   +2 more
wiley   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

AIChE Journal, EarlyView.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman, Zhe Li, Ilias Mitrai, Prodromos Daoutidis   +3 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source