Results 41 to 50 of about 9,690 (264)

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

Advanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio, Jonas Elsborg, Elif Coşkun, Andreas Burger, Pradipkumar Manubhai Leuaa, Thu Pham Anh Phan, Jin Hyun Chang, Christodoulos Chatzichristodoulou   +7 more
wiley   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Epistemological gaps in medical education: a bibliometric and criticalanalysis of contemporary academic discourse [PDF]

Revista de Știinţe Educaţiei
Contemporary medical education is shaped by imperatives of efficiency, measurability and standardisation, often to the detriment of epistemological reflection. This study investigates how epistemological themes—critical reflection, uncertainty, epistemic
Radu-Mihai DUMITRESCU
doaj   +1 more source

Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas [PDF]

Natural Hazards and Earth System Sciences, 2018
This paper discusses how epistemic uncertainties are currently considered in the most widely occurring natural hazard areas, including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and ...
K. J. Beven, K. J. Beven, S. Almeida, W. P. Aspinall, P. D. Bates, S. Blazkova, E. Borgomeo, J. Freer, K. Goda, J. W. Hall, J. C. Phillips, M. Simpson, P. J. Smith, P. J. Smith, D. B. Stephenson, T. Wagener, T. Wagener, M. Watson, K. L. Wilkins   +18 more
doaj   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

CAPO: Causal-Adaptive Preference Optimization for Diffusion Models via Causal Inference Uncertainty

IEEE Access
Post-training alignment of diffusion models based on human feedback uniformly applies equal weights to all preference pairs, ignoring the inherent aleatoric and epistemic uncertainty in feedback, leading to overfitting on noisy signals and insufficient ...
Sihan Hu
doaj   +1 more source

Epistemic Wrapping for Uncertainty Quantification

CoRR
Uncertainty estimation is pivotal in machine learning, especially for classification tasks, as it improves the robustness and reliability of models. We introduce a novel `Epistemic Wrapping' methodology aimed at improving uncertainty estimation in classification.
Maryam Sultana, Neil Yorke-Smith, Kaizheng Wang, Shireen Kudukkil Manchingal, Muhammad Mubashar, Fabio Cuzzolin   +5 more
openaire   +3 more sources

Ethical Precision in Nanoscale Brain Interfacing

Advanced Science, EarlyView.
As brain interfaces approach the nanoscale, precision no longer only measures—it knows, predicts, and potentially reshapes the mind. This work argues that traditional ethics fails under such conditions and proposes a shift toward continuous, operation‐based governance using the recovery–discovery framework to track, constrain, and responsibly steer ...
Guilherme Wood
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source