Results 61 to 70 of about 52,111 (205)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
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, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

The reduced order model problem in distributed parameter systems adaptive identification and control [PDF]

The reduced order model problem in distributed parameter systems adaptive identification and control is investigated. A comprehensive examination of real-time centralized adaptive control options for flexible spacecraft is ...
Johnson, C. R., Jr., Lawrence, D. A.
core   +1 more source

Stage‐Specific Roles of Deep Eutectic Solvents in Recycling of Spent Lithium‐Ion Batteries

Advanced Energy Materials, EarlyView.
Deep eutectic solvents (DESs) offer tunable acidity, redox, and coordination properties for selective recycling of spent lithium‐ion battery cathodes. Through co‐dissolution, single‐ and two‐metal separations, DESs enable sustainable recovery of critical metals for closed‐loop regeneration of battery‐grade materials, advancing a circular economy for ...
Jingxiu Wang, Yan Wang, Yanqiu Lyu, Jianfeng Mao, Zaiping Guo   +4 more
wiley   +1 more source

Hybridization of Homogeneous and Heterogeneous Catalysis to Develop a Novel Biocatalyst via Immobilization of Lipase on Surface Modified Mesoporous Silica Towards Biodiesel Synthesis Application

Advanced Energy and Sustainability Research, EarlyView.
The 3‐(methacryloyloxy)propyltrimethoxysilane surface functionalized SBA‐15 (MP‐SBA‐15) is used for the first time as a lipase carrier. The immobilized CAL‐B exhibits high thermal stability and superior catalytic activity. CAL‐B/SBA‐15 suggests that optimum hydrophobicity gives better catalytic activity.
Murugappan N., Ayumi Sato, Jiachen Ge, Arisa Yamada, Makoto Onaka, Yuki Nakamura, Masaru Ogura   +6 more
wiley   +1 more source

Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Advanced Energy and Sustainability Research, EarlyView.
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar, Arunkumar Chandrasekhar, Poongundran Selvaprabhu   +2 more
wiley   +1 more source

Agricultural Diversification at the Margin. Strategies and Determinants in Italian Mountain and Remote Areas

Agribusiness, EarlyView.
ABSTRACT This paper explores the convergence in on‐farm diversification strategies of agricultural holdings, between remote areas and more central ones. Using Italian farm‐level data, we explore the determinants of diversification strategies across farms.
Gianluca Grilli, Francesco Pagliacci, Paola Gatto   +2 more
wiley   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Torque‐Transmitting Architected Metamaterials for Flexible and Extendable Tubular Robotics

Advanced Intelligent Systems, EarlyView.
Soft and continuum robots commonly rely on fluid, tendon, or rod‐based power transmissions, to control robotic form and actuation. This study presents an architected structure, based on patterned straight‐line mechanisms, that enables simultaneous bending, extending, and torsionally rigid (BETR) transmission.
Sawyer Thomas, Aman Garg, Jeffery Lipton
wiley   +1 more source

Investigation of rank 2 and higher output feedback for pole placement [PDF]

A common feature of several pole placement techniques is discussed and the use of a dyadic feedback matrix is presented. The limitation of this design is examined and a design involving output feedback matrices of Rank greater than one is developed as a ...
Sridhar, B.
core   +1 more source