Results 161 to 170 of about 1,106,758 (269)

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

Advanced 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, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance. [PDF]

Int J Cardiovasc Imaging
Oliveira C, Vilela M, Silva Marques J, Jorge C, Rodrigues T, Francisco AR, Oliveira RM, Silva B, Silva JL, Oliveira AL, Pinto FJ, Nobre Menezes M.   +11 more
europepmc   +1 more source

Two‐Way Shape Memory Polymer Composite Gripper for Adaptive Robotic Applications

Advanced Materials Technologies, EarlyView.
A two‐way shape memory polymer (SMP) composite is developed with intrinsic shape‐changing capability driven solely by temperature, eliminating external actuation loads. Embedding the SMP in a low‐stiffness elastomeric matrix enabled reversible transformations during heating and cooling cycles.
Aamna Hameed, Kamran Ahmed Khan
wiley   +1 more source

The principle of uncertainty in biology: Will machine learning/artificial intelligence lead to the end of mechanistic studies? [PDF]

PLoS Biol
de Lorenzo V.
europepmc   +1 more source

Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs. [PDF]

PLoS One, 2020
Zhu J, Shen B, Abbasi A, Hoshmand-Kochi M, Li H, Duong TQ.   +5 more
europepmc   +1 more source

Strategies for Enhancing Thermal Conductivity of PDMS in Electronic Applications

Advanced Materials Technologies, EarlyView.
This review explores effective strategies for enhancing heat dissipation in Polydimethylsiloxane (PDMS)‐based composites, focusing on particle optimization, 3D network design, and multifunctional integration. It offers key insights into cutting‐edge methods and simulations that are advancing thermal management in modern electronic devices.
Xiang Yan, Marisol Martin‐Gonzalez
wiley   +1 more source

Deep Learning Artificial Intelligence Predicts Homologous Recombination Deficiency and Platinum Response From Histologic Slides. [PDF]

J Clin Oncol
Bergstrom EN, Abbasi A, Díaz-Gay M, Galland L, Ladoire S, Lippman SM, Alexandrov LB.   +6 more
europepmc   +1 more source

Accelerating Discovery to Deployment: Argonne's Materials Engineering Research Facility (MERF) and Its Role in Scaling Materials Technologies for Water and Resource Solutions

Advanced Materials Technologies, EarlyView.
In this Perspective, we highlight the processing science and scale‐up capabilities of the Materials Engineering Research Facility (MERF) at the U.S. Department of Energy's Argonne National Laboratory, with an emphasis on practical solutions for sustainable water and critical resource recovery. We demonstrate how national laboratories bridge fundamental
Yuepeng Zhang, Bratin Sengupta, Xiaoao Shi, Haihui Pu, Jeffrey W. Elam, Gregory K. Krumdick, Jessica Durham Macholz, Allison Bennett Irion, Junhong Chen, Seth B. Darling   +9 more
wiley   +1 more source

Is Histopathology Deep Learning Artificial Intelligence the Future of Precision Oncology? [PDF]

J Clin Oncol
Wagner VM.
europepmc   +1 more source

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

Advanced 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, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source