AIMC Topic: Alloys

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An end-to-end computer vision methodology for quantitative metallography.

Scientific reports Mar 21, 2022
Metallography is crucial for a proper assessment of material properties. It mainly involves investigating the spatial distribution of grains and the occurrence and characteristics of inclusions or precipitates. This work presents a holistic few-shot ...
Artificial Intelligence Computers Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Alloys
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Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 1, 2022
At present, alloys have broad application prospects in heterogeneous catalysis, due to their various catalytic active sites produced by their vast element combinations and complex geometric structures. However, it is the diverse variables of alloys t...
Machine Learning Catalysis Alloys
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Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection.

ACS applied materials & interfaces Jan 26, 2022
We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from the 3-day period of the existing tests to 15 min. Machine learning and robotized bioanalytical platforms require the principles such as hydrogel-bas...
Bacillus coagulans Hydrogels Density Functional Theory Machine Learning Alloys Streptococcus thermophilus Electrochemical Techniques Gallium Indium
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Machine Learning Accelerated, High Throughput, Multi-Objective Optimization of Multiprincipal Element Alloys.

Small (Weinheim an der Bergstrasse, Germany) Sep 15, 2021
Multiprincipal element alloys (MPEAs) have gained surging interest due to their exceptional properties unprecedented in traditional alloys. However, identifying an MPEA with desired properties from a huge compositional space via a cost-effective desi...
Algorithms Molecular Dynamics Simulation Stress, Mechanical Machine Learning Alloys
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Alloying conducting channels for reliable neuromorphic computing.

Nature nanotechnology Jun 8, 2020
A memristor has been proposed as an artificial synapse for emerging neuromorphic computing applications. To train a neural network in memristor arrays, changes in weight values in the form of device conductance should be distinct and uniform. An elec...
Alloys Thermodynamics Electrodes Silicon Electric Conductivity Neural Networks, Computer Kinetics
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Toward Predicting Intermetallics Surface Properties with High-Throughput DFT and Convolutional Neural Networks.

Journal of chemical information and modeling Nov 5, 2019
The surface energy of inorganic crystals is important in understanding experimentally relevant surface properties and designing materials for many applications. Predictive methods and data sets exist for surface energies of monometallic crystals. How...
Crystallization Alloys Thermodynamics Titanium Surface Properties Gold Models, Chemical Neural Networks, Computer Density Functional Theory Models, Molecular Computer Simulation
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A bioinspired optoelectronically engineered artificial neurorobotics device with sensorimotor functionalities.

Nature communications Aug 27, 2019
Development of the next generation of bio- and nano-electronics is inseparably connected to the innovative concept of emulation and reproduction of biological sensorimotor systems and artificial neurobotics. Here, we report for the first time princip...
Robotics Electrical Synapses Neurons Electrochemical Techniques Bioengineering Metals, Heavy Optogenetics Alloys Inhibitory Postsynaptic Potentials Muscles
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Prediction of formation force during single-point incremental sheet metal forming using artificial intelligence techniques.

PloS one Aug 22, 2019
Single-point incremental forming (SPIF) is a technology that allows incremental manufacturing of complex parts from a flat sheet using simple tools; further, this technology is flexible and economical. Measuring the forming force using this technolog...
Fuzzy Logic Materials Testing Alloys Humans Computer-Aided Design Manufacturing Industry Aluminum Neural Networks, Computer
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Machine Learning Prediction of H Adsorption Energies on Ag Alloys.

Journal of chemical information and modeling Apr 2, 2019
Adsorption energies on surfaces are excellent descriptors of their chemical properties, including their catalytic performance. High-throughput adsorption energy predictions can therefore help accelerate first-principles catalyst design. To this end, ...
Thermodynamics Machine Learning Adsorption Models, Molecular Hydrogen Silver Alloys Molecular Conformation
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Shape memory alloy reinforced 5 mm ultra-thin rigid link surgical instrument with force-feedback.

Journal of medical engineering & technology Jan 4, 2019
We report the development of a rigid link surgical instrument for surgical robotics. The device is only 5 mm in diameter and equipped with a shape memory alloy for better gripping, which avoids the use of mechanical gears. This ultra-thin instrument ...
Equipment Design Hand Strength Alloys Surgical Instruments Feedback Robotics Biomechanical Phenomena
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