Intelligent Recommendation Systems Powered by Consensus Neural Networks: The Ultimate Solution for Finding Suitable Chiral Chromatographic Systems? DOI Creative Commons
S. Sagrado,

Carlos Pardo-Cortina,

Laura Escuder‐Gilabert

et al.

Analytical Chemistry, Journal Year: 2024, Volume and Issue: 96(29), P. 12205 - 12212

Published: July 10, 2024

The selection of suitable combinations chiral stationary phases (CSPs) and mobile (MPs) for the enantioresolution compounds is a complex issue that often requires considerable experimental effort can lead to significant waste. Linking structure compound CSP/MP system its enantioseparation be an effective solution this problem. In study, we evaluate algorithmic tools purpose. Our proposed consensus model, which uses multiple optimized artificial neural networks (ANNs), shows potential as intelligent recommendation (IRS) ranking chromatographic systems with different molecular structures. To IRS in proof-of-concept stage, 56 structural descriptors structurally unrelated across 14 families are considered. Chromatographic under study comprise 7 cellulose amylose derivative CSPs acetonitrile or methanol aqueous MPs (14 all). ANNs using fit-for-purpose version chaotic network algorithm competitive learning (CCLNNA), novel approach not previously applied chemical domain. CCLNNA adapted define inner ANN complexity perform feature descriptors. A customized target function evaluates correctness recommending appropriate system. ANN-consensus model exhibits no advisory failures only attempt verify complete enantioresolution. This outstanding performance highlights effectively resolve

Language: Английский

Artificial intelligence-assisted electrochemical sensors for qualitative and semi-quantitative multiplexed analyses DOI Creative Commons
Rocco Cancelliere, Mario Molinara,

Antonio Licheri

et al.

Digital Discovery, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

AI-integrated electrochemical sensors boost peak resolution and sensitivity, enabling precise detection of electroactive species in complex matrices. This method enhances analytical capabilities, providing an analytically robust solution.

Language: Английский

Citations

2
Advancing tea detection with artificial intelligence: strategies, progress, and future prospects DOI

Qilin Xu,

Yifeng Zhou, Linlin Wu

et al.

Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: unknown, P. 104731 - 104731

Published: Sept. 1, 2024

Language: Английский

Citations

9
GLANCE: A Novel Graphical Tool for Simplifying Analytical Chemistry Method Evaluation DOI Creative Commons
Adrián Fuente-Ballesteros, Ana Jano, Ana M. Ares

et al.

Analytica—A Journal of Analytical Chemistry and Chemical Analysis, Journal Year: 2025, Volume and Issue: 6(1), P. 8 - 8

Published: March 1, 2025

GLANCE (Graphical Layout Tool for Analytical Chemistry Evaluation) is an innovative and adaptable free, editable template specifically designed to help researchers visually summarize their analytical chemistry methods in a structured clear manner. It provides accessible solution the challenge of presenting complex scientific data, offering significant advantage over traditional reporting methods, which often lack visual clarity. This crucial because no previous tool has been developed such comprehensive concise format, significantly enhancing process gathering key information, particularly review articles. The (bit.ly/409cwDd) composed twelve distinct attributes, each targeting critical aspects method development (novelty, analytes, sample preparation, reagents, instrumentation, validation, matrix effects recoveries, application real samples, metrics, main results, limitations, additional information). By filling out block with keywords or short phrases, authors can provide yet thorough overview method. Once completed, be easily downloaded included straightforward integration enhances both clarity accessibility publications, providing community quick snapshot principal features research.

Language: Английский

Citations

1
Violet Innovation Grade Index (VIGI): A New Survey-Based Metric for Evaluating Innovation in Analytical Methods DOI
Adrián Fuente-Ballesteros, Víctor Martínez-Martínez, Ana M. Ares

et al.

Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: March 26, 2025

The violet innovation grade index (VIGI) is a pioneering metric designed to evaluate the degree of in analytical methods. This study introduces VIGI tool (https://bit.ly/VIGItool) and demonstrates its application assessing innovative potential various techniques. integrates ten distinct criteria─sample preparation instrumentation, data processing software, white chemistry derivatives, regulatory compliance, materials reagents, miniaturization, automation, interdisciplinarity, sensitivity, approach─providing comprehensive evaluation that complements existing green, blue, red metrics. Each method assessed using survey-based approach, resulting star-shaped decagon pictogram visually represents score. was successfully applied five case studies, revealing insights into strengths weaknesses each terms innovation. Methods incorporating advanced materials, miniaturized devices, automation scored highly, reflecting their cutting-edge contributions chemistry. Conversely, methods lacking or interdisciplinary applications lower, highlighting areas for improvement. work underscores importance prioritizing metrics like development ensure remains at forefront scientific advancement through more effective sustainable practices.

Language: Английский

Citations

1
A practical approach to quantitative analytical surface-enhanced Raman spectroscopy DOI Creative Commons

Yikai Xu,

Wafaa Aljuhani, Yingrui Zhang

et al.

Chemical Society Reviews, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

The high sensitivity, molecular specificity and speed of analysis make SERS an attractive analytical technique. This review draws out the underlying principles for provides practical tips tricks quantitation.

Language: Английский

Citations

7
Biosynthesis of biomolecules from saffron as an industrial crop and their regulation, with emphasis on the chemistry, extraction methods, identification techniques, and potential applications in human health and food: A critical comprehensive review DOI
Vishal Gupta, Gayatri Jamwal, G. Rai

et al.

Biocatalysis and Agricultural Biotechnology, Journal Year: 2024, Volume and Issue: 59, P. 103260 - 103260

Published: May 29, 2024

Language: Английский

Citations

5
Integrating AI in Food Contaminant Analysis: Enhancing Quality and Environmental Protection DOI Creative Commons
Kuppusamy Sathishkumar, Meivelu Moovendhan‬‬‬‬‬‬‬‬,

Loganathan Praburaman

et al.

Journal of Hazardous Materials Advances, Journal Year: 2024, Volume and Issue: unknown, P. 100509 - 100509

Published: Oct. 1, 2024

Language: Английский

Citations

4
Molecular Docking Observations on Enantiomeric Retention Trends and Considerations for Stationary Phase Selection DOI
Anca‐Elena Dascălu, Alina Ghinet, Éric Boulanger

et al.

Published: Jan. 1, 2025

This study explores molecular docking as a predictive tool for enantiomeric separations in supercritical fluid chromatography, focusing on the binding mechanisms of chiral stationary phases. Polysaccharide-based CSPs, widely used separations, rely complex recognition involving hydrogen bonding, π-π interactions, and, case chlorinated halogen bonding. Using AutoDock Vina, simulations were conducted to predict retention and elution behaviors enantiomers by modeling their interactions with CSPs. These predictions systematically compared experimental results assess docking's reliability capturing key descriptors. The further characterized absolute configurations semi-preparatively isolated through X-ray crystallography optical rotation measurements, confirming stereochemistry validating purity. By bridging computational workflows, this work provides deeper insights into polysaccharide CSPs demonstrates potential streamline chromatographic method development, reducing reliance trial-and-error analytical processes.

Language: Английский

Citations

0
Selection of the best options in developing a high-performance liquid chromatography analytical method DOI
Serban C. Moldoveanu, Victor David

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 511 - 552

Published: Jan. 1, 2025

Language: Английский

Citations

0
Federated Learning Applications in Fingerprint and Finger Vein Recognition DOI Creative Commons
Yongchao Wang

ITM Web of Conferences, Journal Year: 2025, Volume and Issue: 70, P. 01023 - 01023

Published: Jan. 1, 2025

Fingerprints and finger veins are widely used in security identification many fields due to their uniqueness identifiability. However, privacy issues often criticized. This article summarizes several approaches that combine federated learning with fingerprint vein recognition solve issues. One of the frameworks for recognition, Federated Learning-Fingerprint Recognition, uses sparse representation techniques such as Discrete Cosine Transform data preprocessing. The framework also references ResNet18 model reservoir sampling so each client can participate training fairly. As Learning-based Finger Vein authentication allows clients share weights island problem divide into shared personalized parts ensure privacy. paper points out its challenges, poor interpretability applicability, provides optimization solutions. For example, issue be solved by implementing an expert system. system robust knowledge base inference engine track behavior derive reasonable explanations. Transfer eliminate applicability issue. It transfers gained from concentrated data. In summary, this comprehensively reviews methods vein, respectively, discusses shortcomings prospects.

Language: Английский

Citations

0