Results 141 to 150 of about 4,945 (184)

Low‐Dimensional Materials and Van Der Waals Heterostructures for Energy Application: A Comprehensive Review

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Low‐dimensional materials (0D, 1D, and 2D) exhibit unique electronic and physicochemical properties, enabling advanced nanoelectronic and optoelectronic devices. Mixed‐dimensional heterostructures combine these materials to enhance functionality.
Qaisar Alam, Sajjad Ali, Pir Muhammad Ismail, ABM Sharif Hossain   +3 more
wiley   +1 more source

Thermodynamic and Kinetic Analysis of Molecular Conformational Dynamics in a Riemannian Framework. [PDF]

J Phys Chem A
Fakharzadeh A, Goolsby C, Tajkhorshid E, Moradi M.   +3 more
europepmc   +1 more source

Earthquake and Tsunami NaTech Risk Assessment for Oil Storage Facilities

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Interaction of natural and technological hazards (NaTech) events, such as tsunamis and earthquakes, can affect industrial facilities such as those featuring anchored atmospheric storage tanks. Consequences of natural events on this kind of installation may include the release of hazardous substances, which in turn can lead to industrial ...
Georgios Baltzopoulos, Pasquale Cito, Federica Ricci, Manuela Volpe, Jacopo Selva, Valerio Cozzani, Iunio Iervolino   +6 more
wiley   +1 more source

Mutual information-based hierarchical NBV decision for active semantic visual SLAM under dynamic environments. [PDF]

Sci Rep
Yang Z, Sang AWY, Muthugala MAVJ, Elara MR.   +3 more
europepmc   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Multiobjective Optimization of Hydrogen‐Assisted Calophyllum inophyllum Biodiesel Operation in a Compression Ignition Engine

Energy Science &Engineering, EarlyView.
Tri‐fuel diesel–Calophyllum inophyllum biodiesel–hydrogen operation was tested over 96 points in a diesel engine. Eight performance and emission metrics feed a preference‐agnostic Bootstrapped Empirical Multiobjective Ranking and Selection methodology, revealing load‐blend‐hydrogen windows that increase efficiency, restrain smoke, and expose NOx trade ...
C. Naga Kumar, Nageswara Rao Dayadi, J. M. Babu, Srinivasa Reddy Yarram, Ravikiran Chintalapudi, Bridjesh Pappula   +5 more
wiley   +1 more source

Stochastic Geometric-Based Modeling for Partial Offloading Task Computing in Edge-AI Systems. [PDF]

Sensors (Basel)
Saeedi H, Nouruzi A.
europepmc   +1 more source

Feasibility of Wind‐Powered Green Hydrogen Production via a Hybrid Graph Neural Network‐Transformer Forecasting Model

Energy Science &Engineering, EarlyView.
ABSTRACT Accurate long‐term wind speed forecasting is pivotal for the strategic planning of renewable energy infrastructure, particularly for assessing the techno‐economic feasibility of wind‐powered green hydrogen facilities. However, capturing the complex spatiotemporal dependencies in climate data remains a significant challenge. This study proposes
Iman Baghaei, Mojtaba Mirhosseini, Alireza Zahedi   +2 more
wiley   +1 more source

Neural SHAKE: geometric constraints in neural differential equations. [PDF]

J Cheminform
Diamond JS, Lill MA.
europepmc   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source