Results 191 to 200 of about 75,327 (306)

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

Advances in Solid‐Phase Processing Techniques: Innovations, Applications, and Future Perspectives

open access: yesAdvanced Materials Technologies, EarlyView.
Based on practical manufacturing challenges, this review examines advanced solid‐phase processing techniques that overcome the inherent limitations of conventional melting‐based and traditional solid‐phase manufacturing, enabling the production of higher‐performance components at reduced cost through process innovation and improved supply‐chain ...
Tianhao Wang
wiley   +1 more source

Multimodal AI fusion for infrastructure resilience: real-time urban analytics framework aligned with SDG-9. [PDF]

open access: yesFront Artif Intell
Kalyan Chakravarthi NS   +5 more
europepmc   +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

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