AIMC Topic: Lithium

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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 Ions Electric Power Supplies Algorithms Lithium Neural Networks, Computer
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Optimized design of battery pole control system based on dual-chip architecture.

PloS one May 11, 2022
At present, the global demand for lithium batteries is still in a high growth state, and the traditional lithium battery pole mill control system is still dominated by ARM (Artificial Intelligence Enhanced Computing), DSP (Digital Signal Processing),...
Artificial Intelligence Lithium Signal Processing, Computer-Assisted Software Algorithms
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State of Charge Estimation of Battery Based on Neural Networks and Adaptive Strategies with Correntropy.

Sensors (Basel, Switzerland) Feb 4, 2022
Nowadays, electric vehicles have gained great popularity due to their performance and efficiency. Investment in the development of this new technology is justified by increased consciousness of the environmental impacts caused by combustion vehicles ...
Algorithms Lithium Electric Power Supplies Electricity Neural Networks, Computer
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Quantitative analysis of lithium in brine by laser-induced breakdown spectroscopy based on convolutional neural network.

Analytica chimica acta Jun 26, 2021
In this study, a simple and effective method for accurate determination of lithium in brine samples was developed by the combination of laser induced breakdown spectroscopy (LIBS) and convolutional neural network (CNN). Our results clearly demonstrat...
Neural Networks, Computer Lasers Salts Lithium Spectrum Analysis
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Unsupervised word embeddings capture latent knowledge from materials science literature.

Nature Jul 3, 2019
The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the ma...
Reproducibility of Results Lithium Natural Language Processing Iron Unsupervised Machine Learning Research Temperature Research Report Magnetics Semantics Knowledge Terminology as Topic Electric Conductivity Materials Science Electrodes Data Mining
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Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies.

Journal of chemical information and modeling Jun 27, 2018
Machine learning (ML) algorithms are gaining importance in the processing of chemical information and modeling of chemical reactivity problems. In this work, we have developed a perturbation-theory and machine learning (PTML) model combining perturba...
Lithium Cyclization Neural Networks, Computer Structure-Activity Relationship Organometallic Compounds Machine Learning Molecular Structure High-Throughput Screening Assays Thermodynamics Models, Chemical Linear Models Algorithms Isoquinolines Databases, Chemical
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Antifungal activities against toxigenic Fusarium specie and deoxynivalenol adsorption capacity of ion-exchanged zeolites.

Journal of environmental science and health. Part. B, Pesticides, food contaminants, and agricultural wastes Dec 29, 2017
Zeolites are often used as adsorbents materials and their loaded cations can be exchanged with metal ions in order to add antimicrobial properties. The aim of this study was to use the 4A zeolite and its derived ion-exchanged forms with Zn, Li, Cu an...
Drug Evaluation, Preclinical Adsorption Zeolites Trichothecenes Lithium Fusarium Fungicides, Industrial Metals
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A lithium-ion batteries SOH estimation method based on extracting new features during the constant voltage charging stage and improving BPNN.

PloS one Jan 1, 2025
Existing state of health (SOH) estimation methods for lithium-ion batteries predominantly extract health features (HF) from constant current (CC) and constant voltage (CV) charging phases. Nevertheless, CC charging phase feature extraction is suscept...
Algorithms Humans Lithium Neural Networks, Computer Electric Power Supplies
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Biomorphic structural batteries for robotics.

Science robotics Aug 19, 2020
Batteries with conformal shape and multiple functionalities could provide new degrees of freedom in the design of robotic devices. For example, the ability to provide both load bearing and energy storage can increase the payload and extend the operat...
Electric Power Supplies Fractals Nanofibers Electric Conductivity Equipment Design Polymers Microscopy, Electron, Scanning Biomimetic Materials Biomimetics Robotics Electrochemical Techniques Zinc Lithium Humans
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