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View article: Physics-informed neural networks with hard-encoded angle-dependent boundary conditions for phonon Boltzmann transport equation
Physics-informed neural networks with hard-encoded angle-dependent boundary conditions for phonon Boltzmann transport equation Open
View article: Higher-order factorization machine for accurate surrogate modeling in material design
Higher-order factorization machine for accurate surrogate modeling in material design Open
View article: Computation and machine learning for materials: Past, present, and future perspectives
Computation and machine learning for materials: Past, present, and future perspectives Open
Computational methods and machine learning (ML) are reshaping materials science by accelerating their discovery, design, and optimization. Traditional approaches such as density functional theory and molecular dynamics have been instrument…
View article: Self-Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers
Self-Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers Open
To overcome the inherent inefficiencies of traditional trial-and-error materials discovery, the scientific community is increasingly developing autonomous laboratories that integrate data-driven decision-making into closed-loop experimenta…
View article: HybridNDiff-UQ: Uncertainty Quantification for Hybrid Neural Differentiable Modeling
HybridNDiff-UQ: Uncertainty Quantification for Hybrid Neural Differentiable Modeling Open
View article: Solar Interfacial Evaporation Toward Multifunctional Water‐Energy Nexus Systems
Solar Interfacial Evaporation Toward Multifunctional Water‐Energy Nexus Systems Open
The scarcity of freshwater resources has escalated into a pressing global challenge. Solar interfacial evaporation (SIE) has gained significant attention because of the abundance and environmental sustainability of solar energy. While SIE …
View article: Quantum annealing for combinatorial optimization: a benchmarking study
Quantum annealing for combinatorial optimization: a benchmarking study Open
View article: JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations Open
This paper introduces JAX-BTE, a GPU-accelerated, differentiable solver for the phonon Boltzmann Transport Equation (BTE) based on differentiable programming. JAX-BTE enables accurate, efficient and differentiable multiscale thermal modeli…
View article: Inverse binary optimization of convolutional neural network in active learning efficiently designs nanophotonic structures
Inverse binary optimization of convolutional neural network in active learning efficiently designs nanophotonic structures Open
View article: Inverse Binary Optimization of Convolutional Neural Network in Active Learning Efficiently Designs Nanophotonic Structures
Inverse Binary Optimization of Convolutional Neural Network in Active Learning Efficiently Designs Nanophotonic Structures Open
Binary optimization using active learning schemes has gained attention for automating the discovery of optimal designs in nanophotonic structures and material configurations. Recently, active learning has utilized factorization machines (F…
View article: Quantum annealing-assisted lattice optimization
Quantum annealing-assisted lattice optimization Open
View article: Quest2DataAgent: Automating End-to-End Scientific Data Collection
Quest2DataAgent: Automating End-to-End Scientific Data Collection Open
View article: Active learning-guided exploration of thermally conductive polymers under strain
Active learning-guided exploration of thermally conductive polymers under strain Open
Active learning guided screening in combination with molecular dynamics simulation accelerate the discovery of high TC strained polymers and enhance the model performance in small data scenarios.
View article: Numerical Study on Pressure Oscillations in a Solid Rocket Motor with Backward Step Configuration Under Two-Phase Flow Interactions
Numerical Study on Pressure Oscillations in a Solid Rocket Motor with Backward Step Configuration Under Two-Phase Flow Interactions Open
The pressure oscillation caused by vortex–acoustic coupling is one of the main gain factors that results in the combustion instability of motors. Focusing on a solid rocket motor with a backward step configuration that can generate a corne…
View article: Nanotwinned thermoelectric materials
Nanotwinned thermoelectric materials Open
View article: Transcend the boundaries: Machine learning for designing polymeric membrane materials for gas separation
Transcend the boundaries: Machine learning for designing polymeric membrane materials for gas separation Open
Polymeric membranes have become essential for energy-efficient gas separations such as natural gas sweetening, hydrogen separation, and carbon dioxide capture. Polymeric membranes face challenges like permeability-selectivity tradeoffs, pl…
View article: Quantum-inspired genetic algorithm for designing planar multilayer photonic structure
Quantum-inspired genetic algorithm for designing planar multilayer photonic structure Open
View article: Author Correction: Designing electrolytes with high solubility of sulfides/disulfides for high-energy-density and low-cost K-Na/S batteries
Author Correction: Designing electrolytes with high solubility of sulfides/disulfides for high-energy-density and low-cost K-Na/S batteries Open
View article: Experimental observation of ballistic to diffusive transition in AlN thin films
Experimental observation of ballistic to diffusive transition in AlN thin films Open
Bulk AlN possesses high thermal conductivity due to long phonon mean-free-paths, high group velocity, and long lifetimes. However, the thermal transport scenario becomes very different in a thin AlN film due to phonon-defect and phonon-bou…
View article: Designing electrolytes with high solubility of sulfides/disulfides for high-energy-density and low-cost K-Na/S batteries
Designing electrolytes with high solubility of sulfides/disulfides for high-energy-density and low-cost K-Na/S batteries Open
View article: QALO: Quantum Annealing-assisted Lattice Optimization
QALO: Quantum Annealing-assisted Lattice Optimization Open
High Entropy Alloys (HEAs) have drawn great interest due to their exceptional properties compared to conventional materials. The configuration of HEA system is considered a key to their superior properties, but exhausting all possible conf…
View article: A review on machine learning-guided design of energy materials
A review on machine learning-guided design of energy materials Open
The development and design of energy materials are essential for improving the efficiency, sustainability, and durability of energy systems to address climate change issues. However, optimizing and developing energy materials can be challe…
View article: Distributed Quantum Approximate Optimization Algorithm on a Quantum-Centric Supercomputing Architecture
Distributed Quantum Approximate Optimization Algorithm on a Quantum-Centric Supercomputing Architecture Open
Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dime…
View article: Superior polymeric gas separation membrane designed by explainable graph machine learning
Superior polymeric gas separation membrane designed by explainable graph machine learning Open
Gas separation using polymer membranes promises to dramatically drive down the energy, carbon, and water intensity of traditional thermally driven separation, but developing the membrane materials is challenging. Here, we demonstrate a gra…
View article: Probabilistic physics-integrated neural differentiable modeling for isothermal chemical vapor infiltration process
Probabilistic physics-integrated neural differentiable modeling for isothermal chemical vapor infiltration process Open
Chemical vapor infiltration (CVI) is a widely adopted manufacturing technique used in producing carbon-carbon and carbon-silicon carbide composites. These materials are especially valued in the aerospace and automotive industries for their…
View article: Quantum annealing-aided design of an ultrathin-metamaterial optical diode
Quantum annealing-aided design of an ultrathin-metamaterial optical diode Open
View article: Quantum-Inspired Genetic Algorithm for Designing Planar Multilayer Photonic Structure
Quantum-Inspired Genetic Algorithm for Designing Planar Multilayer Photonic Structure Open
Quantum algorithms are emerging tools in the design of functional materials due to their powerful solution space search capability. How to balance the high price of quantum computing resources and the growing computing needs has become an …
View article: Unlocking enhanced thermal conductivity in polymer blends through active learning
Unlocking enhanced thermal conductivity in polymer blends through active learning Open
Polymers play an integral role in various applications, from everyday use to advanced technologies. In the era of machine learning (ML), polymer informatics has become a vital field for efficiently designing and developing polymeric materi…
View article: Superior Polymeric Gas Separation Membrane Designed by Explainable Graph Machine Learning
Superior Polymeric Gas Separation Membrane Designed by Explainable Graph Machine Learning Open
Gas separation using polymer membranes promises to dramatically drive down the energy, carbon, and water intensity of traditional thermally driven separation, but developing the membrane materials is challenging. Here, we demonstrate a nov…
View article: Quantum Annealing-aided Design of an Ultrathin-Metamaterial Optical Diode
Quantum Annealing-aided Design of an Ultrathin-Metamaterial Optical Diode Open
Thin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural m…