AIMC Topic: Oxides

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Prediction of Tl(I) adsorption onto metal oxides and identification of critical factors using a machine learning-based model.

Environmental research
Thallium is a highly toxic element, which is widely found all over the world. Adsorption is one of the most common techniques for thallium removal. Traditional adsorption studies face several limitations, such as a limited ability to predict adsorpti...

Machine Learning-Assisted Discovery of Bimetallic Oxides for Highly Efficient Catalytic Ozonation.

Environmental science & technology
Catalytic ozonation stands out as an effective process in the advanced treatment of industrial wastewater, where heterogeneous catalysts play a pivotal role. Here, by screening 1603 bimetallic oxides via machine learning (ML), a pioneering ZnCuO was ...

Facilitating ab initio configurational sampling of multicomponent solids using an on-lattice neural network model and active learning.

The Journal of chemical physics
We propose a scheme for ab initio configurational sampling in multicomponent crystalline solids using Behler-Parinello type neural network potentials (NNPs) in an unconventional way: the NNPs are trained to predict the energies of relaxed structures ...

RRAM-based synapse devices for neuromorphic systems.

Faraday discussions
Hardware artificial neural network (ANN) systems with high density synapse array devices can perform massive parallel computing for pattern recognition with low power consumption. To implement a neuromorphic system with on-chip training capability, w...

Effect of conductance linearity and multi-level cell characteristics of TaO-based synapse device on pattern recognition accuracy of neuromorphic system.

Nanotechnology
To improve the classification accuracy of an image data set (CIFAR-10) by using analog input voltage, synapse devices with excellent conductance linearity (CL) and multi-level cell (MLC) characteristics are required. We analyze the CL and MLC charact...

Synthesis of MnFeO and MnO magnetic nano-composites with enhanced properties for adsorption of Cr(VI): artificial neural network modeling.

Water science and technology : a journal of the International Association on Water Pollution Research
This study reports adsorptive removal of Cr(VI) by magnetic manganese ferrite and manganese oxide nano-particles (MnF-MO-NPs) composite from aqueous media. The X-ray diffraction pattern of MnF-MO-NPs revealed a polycrystalline nature with nanoscale c...

Multi-responsive actuators based on a graphene oxide composite: intelligent robot and bioinspired applications.

Nanoscale
Carbon-based electrothermal or photothermal actuators have attracted intense attention recently. They can directly convert electrical or light energy into thermal energy and exhibit obvious deformations. However, if the actuation mechanism is only li...

[A machine learning model using gut microbiome data for predicting changes of trimethylamine-N-oxide in healthy volunteers after choline consumption].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To establish a machine learning model based on gut microbiota for predicting the level of trimethylamine N-oxide (TMAO) metabolism in vivo after choline intake to provide guidance of individualized precision diet and evidence for screening...

Training and operation of an integrated neuromorphic network based on metal-oxide memristors.

Nature
Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 10(14) synapses, makes the hardware implementation of neuromorphic networks with a comparable number of ...