Results 11 to 20 of about 1,235 (237)
This work presents a programmable atomic engineering strategy for 2D materials using Å‐scale nanoreactors formed by bilayer graphene (BLG) intercalation. A new class of alkali‐iron‐chloride compounds, along with lateral heterostructures composed of monolayer alkali halides and iron chlorides, is revealed.
Haiming Sun +6 more
wiley +1 more source
Interface‐Engineered Binary Framework Composites: Advancing Porous Materials for Precision Medicine
Binary framework composites integrate two complementary porous architectures into a unified platform, enabling multifunctional design, enhanced structural tunability, and improved physicochemical performance. By combining high surface area, ordered porosity, interfacial synergy, and versatile functionalization, these hybrid materials offer new ...
Navid Rabiee +3 more
wiley +1 more source
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Sustainable Productivity Growth in Agriculture: The Role of Shifts in R&D Investments and Technology
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 +4 more
wiley +1 more source
Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang +6 more
wiley +1 more source
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
From Compliance to Circularity: A Design‐Led Approach to Recyclable Packaging
ABSTRACT The transition to recyclable packaging is a strategic priority for the Fast‐Moving Consumer Goods (FMCG) sector, aligning with the EU Packaging and Packaging Waste Regulation (PPWR). Adapting to regulatory uncertainty and integrating evolving recyclability criteria require not only technical innovation but also organisational transformation ...
Tessa Bronsky +2 more
wiley +1 more source
Climate Change Risks and Customer Concentration: Evidence From US‐Listed Firms
ABSTRACT While prior studies have investigated climate risks in supply chains, customer ESG pressures, and shared climate exposure, this paper is, to the best of our knowledge, the first to provide direct empirical evidence on the relationship between climate change risks and firms' customer concentration.
Thi Thuy Trang Nguyen +2 more
wiley +1 more source
ABSTRACT The transition to a circular economy (CE) in the textile and clothing (TC) industry is frequently attributed to sustainability‐oriented innovation (SOI), yet empirical understanding of the systemic conditions under which SOI enables CE remains underdeveloped.
Krishnendu Saha +3 more
wiley +1 more source
ABSTRACT Although artificial intelligence (AI) is increasingly being touted to assist organizations, AI integration for sustainability efforts has been limited AND sporadic and tends to follow an ad hoc strategy. The existing literature therein focuses on the technological capabilities of AI, overlooking how organizations make sense of and ...
Amanda Balasooriya, Darshana Sedera
wiley +1 more source

