AIMC Topic: Ions

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Deep learning-based fast denoising of Monte Carlo dose calculation in carbon ion radiotherapy.

Medical physics Sep 1, 2023
BACKGROUND: Plan verification is one of the important steps of quality assurance (QA) in carbon ion radiotherapy. Conventional methods of plan verification are based on phantom measurement, which is labor-intensive and time-consuming. Although the pl...
Carbon Ions Algorithms Deep Learning Monte Carlo Method Heavy Ion Radiotherapy Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans
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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,...
Ions Metalloproteins Binding Sites Zinc Deep Learning Metals
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An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation.

Journal of chemical information and modeling Jan 11, 2023
Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchm...
Computer Simulation Ions Artificial Intelligence
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Dip-coating electromechanically active polymer actuators with SIBS from midblock-selective solvents to achieve full encapsulation for biomedical applications.

Scientific reports Dec 14, 2022
Soft and compliant ionic electromechanically active polymer actuators (IEAPs) are a promising class of smart materials for biomedical and soft robotics applications. These materials change their shape in response to external stimuli like the electric...
Solvents Smart Materials Ions Styrenes Robotics Polymers
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AlphaFill: enriching AlphaFold models with ligands and cofactors.

Nature methods Nov 24, 2022
Artificial intelligence-based protein structure prediction approaches have had a transformative effect on biomolecular sciences. The predicted protein models in the AlphaFold protein structure database, however, all lack coordinates for small molecul...
Ligands Protein Conformation Proteins Ions Zinc Artificial Intelligence
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An open-source deep learning model for predicting effluent concentration in capacitive deionization.

The Science of the total environment Oct 1, 2022
To effectively evaluate the performance of capacitive deionization (CDI), an electrochemical ion separation technology, it is necessary to accurately estimate the number of ions removed (effluent concentration) according to energy consumption. Herein...
Electrodes Ions Water Purification Electricity Deep Learning
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Transfer learning based generalized framework for state of health estimation of Li-ion cells.

Scientific reports Aug 1, 2022
Estimating the state of health (SOH) of batteries powering electronic devices in real-time while in use is a necessity. The applicability of most of the existing methods is limited to the datasets that are used to train the models. In this work, we p...
Neural Networks, Computer Machine Learning Lithium Ions Electric Power Supplies
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Predicting the oxidation states of Mn ions in the oxygen-evolving complex of photosystem II using supervised and unsupervised machine learning.

Photosynthesis research Jul 27, 2022
Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL) sources enabled the imaging of the catalytic intermediates of the oxygen evolution reaction of Photosystem II (PSII). However, due to the incoherent transition of the S-states...
Photosystem II Protein Complex Ions Electron Spin Resonance Spectroscopy Oxygen Unsupervised Machine Learning Water Oxidation-Reduction
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Accurate Prediction of y Ions in Beam-Type Collision-Induced Dissociation Using Deep Learning.

Analytical chemistry May 24, 2022
Peptide fragmentation spectra contain critical information for the identification of peptides by mass spectrometry. In this study, we developed an algorithm that more accurately predicts the high-intensity peaks among the peptide spectra. The trainin...
Proteomics Tandem Mass Spectrometry Peptides Deep Learning Ions
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Remaining Useful Life Prediction of Lithium-Ion Batteries Using Neural Networks with Adaptive Bayesian Learning.

Sensors (Basel, Switzerland) May 17, 2022
With smart electronic devices delving deeper into our everyday lives, predictive maintenance solutions are gaining more traction in the electronic manufacturing industry. It is imperative for the manufacturers to identify potential failures and predi...
Bayes Theorem Electric Power Supplies Neural Networks, Computer Algorithms Ions Lithium
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