AIMC Topic: Ions

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Rapid prototyping of ion-selective electrodes using a low-cost 3D printed internet-of-things (IoT) controlled robot.

Talanta
We report automated fabrication of solid-contact sodium-selective (Na-ISEs) and potassium-selective electrodes (K-ISEs) using a 3D printed liquid handling robot controlled with Internet of Things (IoT) technology. The printing system is affordable an...

High-Throughput Measurement and Machine Learning-Based Prediction of Collision Cross Sections for Drugs and Drug Metabolites.

Journal of the American Society for Mass Spectrometry
Drug metabolite identification is a bottleneck of drug metabolism studies due to the need for time-consuming chromatographic separation and structural confirmation. Ion mobility-mass spectrometry (IM-MS), on the other hand, separates analytes on a ra...

Portable Deep Learning-Driven Ion-Sensitive Field-Effect Transistor Scheme for Measurement of Carbaryl Pesticide.

Sensors (Basel, Switzerland)
This research proposes a multiple-input deep learning-driven ion-sensitive field-effect transistor (ISFET) scheme to predict the concentrations of carbaryl pesticide. In the study, the carbaryl concentrations are varied between 1 × 10-1 × 10 M, and t...

MFPS_CNN: Multi-filter Pattern Scanning from Position-specific Scoring Matrix with Convolutional Neural Network for Efficient Prediction of Ion Transporters.

Molecular informatics
In cellular transportation mechanisms, the movement of ions across the cell membrane and its proper control are important for cells, especially for life processes. Ion transporters/pumps and ion channel proteins work as border guards controlling the ...

Transferable Neural Network Potential Energy Surfaces for Closed-Shell Organic Molecules: Extension to Ions.

Journal of chemical theory and computation
Transferable high dimensional neural network potentials (HDNNPs) have shown great promise as an avenue to increase the accuracy and domain of applicability of existing atomistic force fields for organic systems relevant to life science. We have previ...

Rapid detection of ionic contents in water through sensor fusion and convolutional neural network.

Chemosphere
Salt contents in soil or groundwater are one of the primary indicators to evaluate contamination levels. Electrical conductivity (EC) or salinity information from the conventional laboratory analysis is typically inefficient in delineating contaminat...

Sodium adduct formation with graph-based machine learning can aid structural elucidation in non-targeted LC/ESI/HRMS.

Analytica chimica acta
Non-targeted screening with LC/ESI/HRMS aims to identify the structure of the detected compounds using their retention time, exact mass, and fragmentation pattern. Challenges remain in differentiating between isomeric compounds. One untapped possibil...

Deep learning models for image and data processes of intracellular calcium ions.

Cellular signalling
Intracellular calcium ion (Ca) in cytoplasm as an intracellular second messenger is involved in almost all important cellular activities of organisms. Generally its concentration ([Ca]) is tested by live imaging followed image and data processes, in ...

Semi-Automated Determination of Heavy Metals in Autopsy Tissue Using Robot-Assisted Sample Preparation and ICP-MS.

Molecules (Basel, Switzerland)
The endoprosthetic care of hip and knee joints introduces multiple materials into the human body. Metal containing implant surfaces release degradation products such as particulate wear and corrosion debris, metal-protein complexes, free metallic ion...

Neural Network Analysis of Electron Microscopy Video Data Reveals the Temperature-Driven Microphase Dynamics in the Ions/Water System.

Small (Weinheim an der Bergstrasse, Germany)
Real-time field-emission scanning electron microscopy (FE-SEM) measurements and neural network analysis were successfully merged to observe the temperature-induced behavior of soft liquid microdomains in mixtures of different ionic liquids with water...