AIMC Topic: Metals
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Soft Robots with Plant-Inspired Gravitropism Based on Fluidic Liquid Metal.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 6, 2024
Plants can autonomously adjust their growth direction based on the gravitropic response to maximize energy acquisition, despite lacking nerves and muscles. Endowing soft robots with gravitropism may facilitate the development of self-regulating syste...
Artificial intelligence-based prediction model for the elemental occurrence form of tailings and mine wastes.
Environmental research
Feb 2, 2024
With the advent of the second industrial revolution, mining and metallurgical processes generate large volumes of tailings and mine wastes (TMW), which worsens global environmental pollution. Studying the occurrence of metal and metalloid elements in...
Fungal bioleaching of metals from WPCBs of mobile phones employing mixed Aspergillus spp.: Optimization and predictive modelling by RSM and AI models.
Journal of environmental management
Nov 15, 2023
In the present study, optimization and prediction models for fungal bioleaching for effective metal extraction from waste printed circuit boards (WPCBs) of mobile phones were developed employing central composite design (CCD) of response surface meth...
Preclinical validation of a novel deep learning-based metal artifact correction algorithm for orthopedic CT imaging.
Journal of applied clinical medical physics
Oct 3, 2023
PURPOSE: To validate a novel deep learning-based metal artifact correction (MAC) algorithm for CT, namely, AI-MAC, in preclinical setting with comparison to conventional MAC and virtual monochromatic imaging (VMI) technique.
Machine Learning-Based Prediction of Activation Energies for Chemical Reactions on Metal Surfaces.
Journal of chemical information and modeling
Sep 18, 2023
In computational surface catalysis, the calculation of activation energies of chemical reactions is expensive, which, in many cases, limits our ability to understand complex reaction networks. Here, we present a universal, machine learning-based appr...
Deep learning-based ultrasound transducer induced CT metal artifact reduction using generative adversarial networks for ultrasound-guided cardiac radioablation.
Physical and engineering sciences in medicine
Aug 7, 2023
In US-guided cardiac radioablation, a possible workflow includes simultaneous US and planning CT acquisitions, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a metal artifa...
Liquid Metal Fibers with a Knitted Structure for Wearable Electronics.
Biosensors
Jul 7, 2023
Flexible conductive fibers have shown tremendous potential in diverse fields, including health monitoring, intelligent robotics, and human-machine interaction. Nevertheless, most conventional flexible conductive materials face challenges in meeting t...
Liquid Metal Flexible EMG Gel Electrodes for Gesture Recognition.
Biosensors
Jun 29, 2023
Gesture recognition has been playing an increasingly important role in the field of intelligent control and human-computer interaction. Gesture recognition technology based on electromyography (EMG) with high accuracy has been widely applied. However...
Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins.
Nature communications
May 11, 2023
Metal ions are essential cofactors for many proteins and play a crucial role in many applications such as enzyme design or design of protein-protein interactions because they are biologically abundant, tether to the protein using strong interactions,...
Deep learning reconstruction with single-energy metal artifact reduction in pelvic computed tomography for patients with metal hip prostheses.
Japanese journal of radiology
Mar 2, 2023
PURPOSE: The aim of this study was to assess the impact of the deep learning reconstruction (DLR) with single-energy metal artifact reduction (SEMAR) (DLR-S) technique in pelvic helical computed tomography (CT) images for patients with metal hip pros...
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