Results 101 to 110 of about 195,667 (268)

Bayesian inverse problems with Monte Carlo forward models

open access: yes, 2012
The full application of Bayesian inference to inverse problems requires exploration of a posterior distribution that typically does not possess a standard form. In this context, Markov chain Monte Carlo (MCMC) methods are often used.
Langmore, Ian   +2 more
core   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

open access: yesAdvanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz   +5 more
wiley   +1 more source

Isospectral sets and inverse problems for vector-valued Sturm-Liouville equations

open access: yes, 2011
In this paper, we investigate inverse spectral problems for vectorial Sturm–Liouville equations via the matrix-valued Gelfand–Levitan equation. With this approach, we prove some uniqueness theorems for the even problem, mixed data problem and interior ...
謝忠村; Shieh, Chung-tsun
core   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

open access: yesAdvanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue   +8 more
wiley   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

open access: yesAdvanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane   +4 more
wiley   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

open access: yesAdvanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu   +8 more
wiley   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding   +5 more
wiley   +1 more source

Next‐Generation Water Treatment With Molybdenum Disulfide: Dual‐Functionality in Pollutant Adsorption and Photocatalysis

open access: yesAdvanced Materials Technologies, EarlyView.
ABSTRACT Molybdenum disulfide (MoS2) has attracted attention as a promising material due to the growing demand for environmentally friendly, cost‐effective, and efficient water treatment techniques. With its physicochemical characteristics, this stratified bidimensional material allows it to be highly effective in adsorption and catalytic performance ...
Pariksha Bishnoi   +4 more
wiley   +1 more source

Stress‐Normalized Sensitivity as a Comparative Benchmark for Intrinsically Piezoresistive Nanocomposite Materials in Wearable Electronics

open access: yesAdvanced Materials Technologies, EarlyView.
A stress‐normalised sensitivity metric (S = G/Y) is introduced as a materials‐level benchmark for intrinsically piezoresistive nanocomposites. By decoupling electromechanical response (G) from stiffness (Y), the framework enables direct comparison across diverse systems and clarifies design trade‐offs for wearable sensors.
Conor S. Boland
wiley   +1 more source

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