Imagen de Portada

Machine Learning-Assisted Thermoelectric Cooling for On-Demand Multi-Hotspot Thermal Management

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Luo, Jiajian, Lee, Jaeho
Formato:	Preprint
Publicado:	2024
Materias:	Applied Physics Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Machine Learning Enhanced Laser Spectroscopy for Multi-Species Gas Detection in Complex and Harsh Environments
por: Sy, Mohamed
Publicado: (2026)

High Thermoelectric Cooling Performance of Junction Thermoelectric Transistors
por: Tang, Chen, et al.
Publicado: (2025)

Material-Agnostic Zero-Shot Thermal Inference for Metal Additive Manufacturing via a Parametric PINN Framework
por: Lee, Hyeonsu, et al.
Publicado: (2026)

Machine Learning-Guided Design of Non-Reciprocal and Asymmetric Elastic Chiral Metamaterials
por: Yuan, Lingxiao, et al.
Publicado: (2024)

Machine Learning Based Prediction of Proton Conductivity in Metal-Organic Frameworks
por: Han, Seunghee, et al.
Publicado: (2024)

A Certifiable Machine Learning-Based Pipeline to Predict Fatigue Life of Aircraft Structures
por: Ladrón, Ángel, et al.
Publicado: (2025)

Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures
por: Bond, R. Bailey, et al.
Publicado: (2024)

Defining Energy Indicators for Impact Identification on Aerospace Composites: A Physics-Informed Machine Learning Perspective
por: Marinho, Natália Ribeiro, et al.
Publicado: (2025)

Uncertainty Reasoning with Photonic Bayesian Machines
por: Brückerhoff-Plückelmann, F., et al.
Publicado: (2025)

Experimental Machine Learning with Classical and Quantum Data via NMR Quantum Kernels
por: Sabarad, Vivek, et al.
Publicado: (2024)

Bubble2Heat: Optical to Thermal Inference in Pool Boiling Using Physics-encoded Generative AI
por: Fu, Qianxi, et al.
Publicado: (2025)

Machine Learning and Kalman Filtering for Nanomechanical Mass Spectrometry
por: Erdogan, Mete, et al.
Publicado: (2023)

Weighted Bayesian Conformal Prediction
por: Lou, Xiayin, et al.
Publicado: (2026)

Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches
por: Filippozzi, Davide, et al.
Publicado: (2025)

Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design
por: Zhang, Zhen, et al.
Publicado: (2025)

Machine Learning-Assisted 3D Printing of Thermoelectric Materials of Ultrahigh Performances at Room Temperature
por: Song, Kaidong, et al.
Publicado: (2024)

Design of Cavity Backed Slotted Antenna using Machine Learning Regression Model
por: Sutrakar, Vijay Kumar, et al.
Publicado: (2025)

Flexible Thermoelectric Active Cooling Garment to Combat Extreme Heat
por: Feng, Tianshi, et al.
Publicado: (2024)

Machine Learning Co-pilot for Screening of Organic Molecular Additives for Perovskite Solar Cells
por: Pu, Yang, et al.
Publicado: (2024)

Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals
por: Trapp, Maximilian, et al.
Publicado: (2024)

Metal Oxide-based Gas Sensor Array for the VOCs Analysis in Complex Mixtures using Machine Learning
por: Singh, Shivam, et al.
Publicado: (2023)

Machine Learning Resistant Amorphous Silicon Physically Unclonable Functions (PUFs)
por: Kilic, Velat, et al.
Publicado: (2024)

Estimation of Fish Catch Using Sentinel-2, 3 and XGBoost-Kernel-Based Kernel Ridge Regression
por: Mohammed, Kanu, et al.
Publicado: (2026)

Multi-Task Deep Learning for Surface Metrology
por: Kucharski, D., et al.
Publicado: (2025)

Optimal Data Generation in Multi-Dimensional Parameter Spaces, using Bayesian Optimization
por: Mahani, M. R., et al.
Publicado: (2023)

A Multi-Resolution Benchmark Framework for Spatial Reasoning Assessment in Neural Networks
por: Imbriani, Manuela, et al.
Publicado: (2025)

A Supervised Machine Learning Framework for Multipactor Breakdown Prediction in High-Power Radio Frequency Devices and Accelerator Components: A Case Study in Planar Geometry
por: Iqbal, Asif, et al.
Publicado: (2025)

Real-time Multi-instrument Autonomous Discovery of Novel Phase-change Memory Materials
por: Lee, Chih-Yu, et al.
Publicado: (2026)

Reinforcement Learning for Photonic Component Design
por: Witt, Donald, et al.
Publicado: (2023)

Automotive Crash Dynamics Modeling Accelerated with Machine Learning
por: Nabian, Mohammad Amin, et al.
Publicado: (2025)

Acoustic Structure Inverse Design and Optimization Using Deep Learning
por: Sun, Xuecong, et al.
Publicado: (2021)

TunnElQNN: A Hybrid Quantum-classical Neural Network for Efficient Learning
por: Abbas, A. H.
Publicado: (2025)

Machine Learning-based Regional Cooling Demand Prediction with Optimised Dataset Partitioning
por: Zhang, Meng, et al.
Publicado: (2025)

Machine learning and atomic layer deposition: predicting saturation times from reactor growth profiles using artificial neural networks
por: Yanguas-Gil, Angel, et al.
Publicado: (2022)

CHLU: The Causal Hamiltonian Learning Unit as a Symplectic Primitive for Deep Learning
por: Jawahar, Pratik, et al.
Publicado: (2026)

Training all-mechanical neural networks for task learning through in situ backpropagation
por: Li, Shuaifeng, et al.
Publicado: (2024)

Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning
por: Bastawrous, Mary V., et al.
Publicado: (2024)

Constructing artificial life and materials scientists with accelerated AI using Deep AndersoNN
por: Dajani, Saleem Abdul Fattah Ahmed Al, et al.
Publicado: (2024)

A rapid approach to urban traffic noise mapping with a generative adversarial network
por: Yang, Xinhao, et al.
Publicado: (2024)

Training of Physical Neural Networks
por: Momeni, Ali, et al.
Publicado: (2024)