Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Artificial Intelligence Meets Micro/Nanorobotics
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever +6 more
wiley +1 more source
Lessons from PrEP: A Qualitative Study Investigating How Clinical and Policy Experts Weigh Ethics and Evidence When Evaluating Preventive Medications for Use in Pregnant and Breastfeeding Women. [PDF]
Beima-Sofie KM +6 more
europepmc +1 more source
Experts and the science-policy interface in China’s climate policy
This thesis explores the ways in which experts engage in China’s climate policies at four different administrative levels (i.e. international, national, provincial, and prefectural) and how politics simultaneously influences the science-policy interface (SPI) in an authoritarian context and a multi-level governance framework.First, experts play an ...
openaire +1 more source
Scalable Task Planning via Large Language Models and Structured World Representations
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari +4 more
wiley +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang +14 more
wiley +1 more source
Relative contributions of recommended food environment policies to improve population nutrition: results from a Delphi study with international food policy experts. [PDF]
Mahesh R +3 more
europepmc +1 more source
Auditory–Tactile Congruence for Synthesis of Adaptive Pain Expressions in RoboPatients
In this work, we explore auditory–tactile congruence for synthesizing adaptive vocal pain expressions in robopatients. Using a robopatient platform that integrates vocal pain sounds with palpation forces, we conducted 7680 trials across 20 participants.
Saitarun Nadipineni +4 more
wiley +1 more source

