Results 31 to 40 of about 3,207 (262)

Atom–Cluster Synergy in Scalable Fe–Ru Dual‐Site Architectures Accelerates Alkaline Hydrogen Evolution

Advanced Materials, EarlyView.
A mechanochemically synthesized dual‐site electrocatalyst (RuNC@Fe1NC) accelerates alkaline hydrogen evolution via atomic‐level spatial decoupling. Oxophilic Fe single atoms effectively dissociate water, while adjacent Ru nanoclusters rapidly recombine hydrogen.
Jae‐Hoon Baek, Seong Hyeon Kweon, Sun Gwan Cha, Se Jung Lee, Jinwoo Baek, Dong Hyeok Kwon, Hojeong Lee, Youngkook Kwon, Sang Kyu Kwak, Jong‐Beom Baek   +9 more
wiley   +1 more source

Fabric first: is it still the right approach?

Buildings & Cities, 2023
‘Fabric first’ describes an approach to improving the thermal performance of residential buildings by prioritising the improvement of fabric. It has historically been widely advocated.
Nick Eyre, Tina Fawcett, Marina Topouzi, Gavin Killip, Tadj Oreszczyn, Kay Jenkinson, Jan Rosenow   +6 more
doaj   +1 more source

Advanced Manufacturing of Composite‐Based Systems for Energy Applications

Advanced Materials Technologies, EarlyView.
Advanced manufacturing enables the integration of polymers, ceramics, metal oxides, and composites into architected microstructures with tailored transport pathways. By coupling material selection, manufacturing strategy, and structural design, multifunctional energy systems can simultaneously improve electrochemical performance, thermal management ...
Sri Vaishnavi Thummalapalli, Dhanush Patil, Libin Yang, M. Taylor Sobczak, Anshul Kulkarni, Xiao Sun, Arunachalam Ramanathan, Tiantian Li, Ramaraja P. Ramasamy, Jason J. Locklin, Yanyu Chen, Xianqiao Wang, Arunachala Mada Kannan, Kenan Song   +13 more
wiley   +1 more source

From Pores to Pavement: Advanced Modeling of Aluminosilicates for Scalable Carbon Capture in Concrete

Advanced Science, EarlyView.
This study presents a transferable modeling framework for carbon capture using aluminosilicates, integrating Universal Isotherm Modeling with experimental data. It reveals how ultramicropores, alumina content, and amine functionalization influence CO2 adsorption energetics.
Pooja Anil Kumar Nair, Jéssica de O. N. Ribeiro, Murilo Daniel de Mello Innocentini, Kevin Paine, Juliana Calabria‐Holley   +4 more
wiley   +1 more source

Cleaner the better: Macro-economic assessment of ambitious decarbonisation pathways across Indian states

Renewable and Sustainable Energy Transition, 2022
In first of its kind, this study evaluates socio -economic impacts of two ambitious decarbonisation pathways for India (i) aligned with India's Nationally Determined Commitments (NDC) negotiated through Paris agreement in 2015 and (ii) more ambitious NDC
Surabhi Joshi, Kakali Mukhopadhyay
doaj   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Low carbon futures: assessing the status of decarbonisation efforts at universities within a 2050 perspective

Energy, Sustainability and Society, 2023
Background The implementation of sustainability at universities means that they can also play a key role in the transition to a low carbon economy, and in assisting global efforts towards decarbonisation. Yet, not all of them have so far fully engaged in
Walter Leal Filho, Diogo Guedes Vidal, Maria Alzira Pimenta Dinis, Wim Lambrechts, Claudio R. P. Vasconcelos, Petra Molthan-Hill, Ismaila Rimi Abubakar, Rachel M. Dunk, Amanda Lange Salvia, Ayyoob Sharifi   +9 more
doaj   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Optimal decarbonisation pathway for mining truck fleets

Journal of Automation and Intelligence
The fossil fuel powered mining truck fleets can contribute up to 80% of total emissions in open pit mines. This study investigates the optimal decarbonisation pathway for mining truck fleets.
Gang Yu, Xianming Ye, Yuxiang Ye, Hongxu Huang, Xiaohua Xia   +4 more
doaj   +1 more source