Results 201 to 210 of about 96,436 (259)

Quantum computation of the electronic structure of some prototype solids. [PDF]

Sci Rep
Khandelwal N, Verma N, Jamdagni P, Kumar A.   +3 more
europepmc   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Multicolor Emission in Perovskite Nanostructures via Quantum Confinement Engineering for High-Speed Optical Wireless Communication. [PDF]

ACS Nano
Zhu X, Niu W, Wang L, Hu X, Zhou R, Wang JX, Li X, Ng TK, Alshareef HN, Bakr OM, Ooi BS, Mohammed OF.   +11 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Unifying Decoherence and Phase Evolution in Mixed Quantum-Classical Dynamics through Exact Factorization. [PDF]

J Phys Chem Lett
Ha JK, Kim SH, Min SK.
europepmc   +1 more source

Evaluating Three Foundation Potentials for Predicting Selected Properties of the Co–Ni–Ru Alloy System

Advanced Intelligent Discovery, EarlyView.
Distributions of intrinsic stacking fault energies (ISFE) among different slip planes in the face‐centered cubic Co2Ni2Ru alloy, predicted by three foundation potentials (DPA, Orb, and SevenNet) and density functional theory (DFT) calculations. This study evaluates the efficacy of three foundation potentials (FPs)—SevenNet, DPA, and Orb—in predicting ...
Subah Mubassira, Thu Nguyen, Anvesh Nathani, Shoutian Sun, Ming Hu, Yanqing Su, Bin Wang, Iman Ghamarian, Shuozhi Xu   +8 more
wiley   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Subjective nature of path information in quantum mechanics. [PDF]

Nat Commun
Jiang X, Hochrainer A, Kysela J, Erhard M, Gu X, Yu Y, Zeilinger A.   +6 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Thermal-State Continuous-Variable Quantum Key Distribution Under the Effects of Gravity. [PDF]

Entropy (Basel)
Zhang L, Huang J, Zhou J.
europepmc   +1 more source