Machine Learning-Driven, Sensor-Integrated Microfluidic Device for Monitoring and Control of Supersaturation for Automated Screening of Crystalline Materials-Reference-Cited by-同舟云学术

Machine Learning-Driven, Sensor-Integrated Microfluidic Device for Monitoring and Control of Supersaturation for Automated Screening of Crystalline Materials

Published:2022-01-20 Issue:3 Volume:7 Page:797-805
ISSN:2379-3694
Container-title:ACS Sensors
language:en
Short-container-title:ACS Sens.

Author:

Coliaie Paria¹^ORCID,Prajapati Aditya¹,Ali Rabia¹,Korde Akshay²^ORCID,Kelkar Manish S.²,Nere Nandkishor K.¹²^ORCID,Singh Meenesh R.¹^ORCID

Affiliation:

1. Department of Chemical Engineering, University of Illinois Chicago, Chicago, Illinois 60607, United States

2. Center of Excellence for Isolation & Separation Technologies (CoExIST), Process R&D, AbbVie Inc., North Chicago, Illinois 60064, United States

Publisher

American Chemical Society (ACS)

Subject

Fluid Flow and Transfer Processes,Process Chemistry and Technology,Instrumentation,Bioengineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acssensors.1c02358

Reference34 articles.

1. Real-time monitoring of crystallization from solution by using an interdigitated array electrode sensor

2. Innovative High-Throughput SAXS Methodologies Based on Photonic Lab-on-a-Chip Sensors: Application to Macromolecular Studies

3. Application of Laser-Backscattering Instruments for In Situ Monitoring of Crystallization Processes - A Review

4. Drug supersaturation during formulation digestion, including real-time analytical approaches

5. Polymorphic Concentration Control for Crystallization Using Raman and Attenuated Total Reflectance Ultraviolet Visible Spectroscopy

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Over a decade of progress: Crystallization in microfluidic systems;Chemical Engineering Journal;2024-09

2. Highly robust, self-adhesive, self-healing, pH-responsive, cytocompatible and degradable collagen/PVA/tannin-based conductive hydrogel sensor for motion-monitoring;Polymer;2024-08

3. Research on differential pulse voltammetry detection method for low concentration glucose based on machine learning model;International Journal of Electrochemical Science;2024-02

4. Addressing Uncertainty on Machine Learning Models for Long-Period Fiber Grating Signal Conditioning Using Monte Carlo Method;IEEE Transactions on Instrumentation and Measurement;2024

5. Machine learning combined with electrochemical sensor for rapid detection of Sudan Red I in food;Journal of Food Measurement and Characterization;2023-09-28