Results 61 to 70 of about 105,360 (214)

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations

Advanced Electronic Materials, EarlyView.
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka, Akito Tateyama, Hina Kitano, Takashi Nakanishi, Kazuya Terabe, Takashi Tsuchiya   +5 more
wiley   +1 more source

Bridging Performance and Fate: A Framework for Sustainable, Composite‐Based Flexible Electronic Systems

Advanced Electronic Materials, EarlyView.
Composite‐based flexible electronics integrate biodegradable polymers, conductive networks, and multilayer device architectures to balance electrical performance, mechanical durability, and controlled degradation. Interfacial engineering and encapsulation regulate transport stability and operational lifetime, while programmed disassembly enables ...
Sayam, Sangho Cho
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

Proposal for a Comprehensive Definition of Budget Impact Analysis [PDF]

Value in Health, 2014
openaire   +2 more sources

Organic Photoelectrochemical Cells Beyond Performance: Interface and Catalyst Engineering for Durability

Advanced Energy Materials, EarlyView.
Organic photoelectrochemical cells based on π‐conjugated semiconductors offer a versatile platform for solar fuel generation. This review outlines operating principles, device architectures, and key metrics, and highlights advances in p‐ and n‐type photoelectrodes, interfacial engineering, and catalyst integration.
Jaehyeong Kim, Jung Min Ha, Yeonjeong Lee, Seung Won Oh, Wangyeon Lee, Munsu Kwon, Soonyong Lee, Jin Young Kim, Han Young Woo   +8 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Kenyan Farmers' Policy Priorities During Economic Crisis and Stability: Insights From a Best‐Worst Scaling Experiment

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Amid rising food and fertilizer prices, understanding farmers' policy preferences is critical for effective crisis response. We use best‐worst scaling experiment to assess Kenyan mobile‐owning crop farmers' preferences for government support under high and normal price scenarios.
Mywish K. Maredia, John Olwande, Jacob Ricker‐Gilbert, David L. Mather, Nicole M. Mason   +4 more
wiley   +1 more source

Sustainable Productivity Growth in Agriculture: The Role of Shifts in R&D Investments and Technology

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT The objective of the paper is to evaluate the long‐term prospects of sustainable productivity growth linked to plausible assumptions on public agricultural R&D investments as the key productivity driver. Second, it investigates the role of changing R&D focus from yield maximization to input saving technologies (fertilizers and pesticides). The
Zuzana Smeets Křístková, Michiel van Dijk, Robert M'Barek, Hans van Meijl, Tomas Ratinger   +4 more
wiley   +1 more source

Ban Glyphosate—Does It Affect the Swedish Farmers' Willingness to Grow Cover Crops?

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT The cultivation of cover crops is one of the new Eco‐scheme practices introduced in Sweden. This study examines how the design of policy attributes of these schemes influences farmers' willingness to grow cover crops on arable land, with particular focus on the potential impact of a glyphosate ban.
Vivian Wei Huang, Anna Kristina Edenbrandt, Elin Röös   +2 more
wiley   +1 more source