Results 91 to 100 of about 11,198,121 (288)

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

Advanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source

Interpretable Physics-informed Machine Learning Methods for Scientific Modeling and Data Analysis

, 2023
With the recent advancement of modern machine learning methods, there are now many exciting opportunities to use machine learning in scientific research, including for modeling and data analysis.
Lu, Peter Yucheng
core  

Machine Learning-Empowered Electromagnetic Wave Absorbing Materials: From Forward Prediction to Generative Inverse Design

Molecules
Electromagnetic wave absorbing materials are important for electromagnetic protection, radar stealth, wireless communication, and advanced electronic systems.
Tongbaihui Qi, Jintang Zhou
doaj   +1 more source

Physics-Informed Machine Learning On Polar Ice: A Survey

CoRR
The mass loss of the polar ice sheets contributes considerably to ongoing sea-level rise and changing ocean circulation, leading to coastal flooding and risking the homes and livelihoods of tens of millions of people globally. To address the complex problem of ice behavior, physical models and data-driven models have been proposed in the literature ...
Zesheng Liu, Younghyun Koo, Maryam Rahnemoonfar   +2 more
openaire   +3 more sources

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Achieving High ON State Current through Ferroelectric Polarization‐Dependent Interfacial Resistance Switching in Undoped Orthorhombic HfO2 Films

Advanced Functional Materials, EarlyView.
Ferroelectric tunnel junction devices based on epitaxial undoped ferroelectric HfO2 films demonstrate stable switching endurance of over 106 switching cycles, low write voltages of ±3 V, 16 measured resistance states, and neuromorphic capability.
Markus Hellenbrand, Nuno Estrócio, Ji S. Kim, Babak Bakhit, Marian C. Istrate, Corneliu Ghica, Tiago Rebelo, Nives Strkalj, Abin Varghese, Bernardo Almeida, Luís S. Marques, Bipin Rajendran, Judith L. MacManus‐Driscoll, José P. B. Silva   +13 more
wiley   +1 more source

Intuitive tests to validate machine learning models against physics and domain knowledge

Digital Engineering
The integration of machine learning (ML) faces a fundamental challenge because current explainability methods provide statistical attribution and lack systematic frameworks for validating explanations against physical laws, constitutive relationships ...
M.Z. Naser
doaj   +1 more source

Physics-Informed Machine Learning for Characterizing System Stability

AIAA SCITECH 2026 Forum
In the design and operation of complex dynamical systems, it is essential to ensure that all state trajectories of the dynamical system converge to a desired equilibrium within a guaranteed stability region. Yet, for many practical systems -- especially in aerospace -- this region cannot be determined a priori and is often challenging to compute.
Tomoki Koike, Elizabeth Qian
openaire   +2 more sources

Advances in Sustainable and Wearable Textile Based Soft Robotics

Advanced Functional Materials, EarlyView.
This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas, Marzia Dulal, Sophia K. Novoselov, Victoria K. Novoselov, Kostya S. Novoselov, Shaila Afroj, Nazmul Karim   +6 more
wiley   +1 more source

RNA regulation mechanisms study using physics-informed machine learning

Communications Physics
Understanding the dynamic regulation mechanisms of RNA is crucial for unlocking the secrets of biological processes and diseases. Existing computational methods primarily focus on static structures and give insufficient attention to RNA. Here, we develop
Haoquan Liu, Yanan Zhu, Jiaming Gao, Chen Zhuo, Chengwei Zeng, Yunjie Zhao   +5 more
doaj   +1 more source