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Related Concept Videos

Sample Preparation for Analysis: Overview01:21

Sample Preparation for Analysis: Overview

196
Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
Bulk or large solid samples are typically reduced in size using grinding, crushing, or milling techniques to increase the...
196
Sample Preparation for Analysis: Advanced Techniques01:08

Sample Preparation for Analysis: Advanced Techniques

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Accurate analysis of complex samples often requires advanced preparation techniques to achieve reliable and reproducible results. Samples containing inorganic or organic materials can be challenging to dissolve or decompose effectively. Standard sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion.
Acid digestion with strong acids is commonly used to dissolve inorganic materials that are insoluble (do not dissolve) in water. This method can be useful for...
304

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Updated: Jun 12, 2025

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
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Concept of flexible no-code automation for complex sample preparation procedures.

Kjell Kochale1, Dino Boerakker2, Thorsten Teutenberg2

  • 1Institut für Umwelt & Energie, Technik & Analytik e. V. (IUTA), Bliersheimer Str. 58-60, Duisburg 47229, Germany; Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstr. 5, Essen 45141, Germany.

Journal of Chromatography. A
|September 17, 2024
PubMed
Summary
This summary is machine-generated.

No-code automation addresses laboratory labor shortages by enabling staff to automate complex assays like HPTLC without programming skills, enhancing productivity and safety.

Keywords:
AChE-assayAutomationCollaborative robotHigh performance thin layer chromatographyNo-code automation

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Area of Science:

  • Laboratory Automation
  • Robotics in Science
  • Analytical Chemistry

Background:

  • Declining enrollments in Science, Technology, Engineering, and Mathematics (STEM) fields are creating labor shortages in scientific research.
  • Traditional laboratory automation often requires specialized programming expertise, limiting accessibility for many researchers.
  • There is a growing need for adaptable and user-friendly automation solutions to maintain research productivity and safety.

Purpose of the Study:

  • To introduce no-code automation as a viable strategy to address STEM labor deficits in laboratory settings.
  • To demonstrate the automation of a High-Performance Thin-Layer Chromatography (HPTLC) assay using a no-code software platform.
  • To enhance laboratory personnel's capability to configure and modify automated workflows without advanced programming knowledge.

Main Methods:

  • Development and deployment of a user-friendly, no-code software platform for assay automation.
  • Integration of a collaborative robot (cobot) and programmable logic controller (PLC) for automated laboratory tasks.
  • Utilization of open-source hardware for automated sample handling, incubation, spraying, detection, and storage stations.
  • Implementation of innovative design solutions and adaptive programming to manage challenges like handling fragile HPTLC plates.

Main Results:

  • Successful automation of a complex HPTLC assay using the no-code platform.
  • Empowerment of laboratory personnel to independently configure and adapt automated workflows.
  • Demonstrated seamless integration of various automated stations, including specialized handling for delicate HPTLC plates.
  • Overcoming practical challenges in laboratory automation through creative engineering and flexible programming.

Conclusions:

  • No-code automation presents a feasible and efficient solution to mitigate skilled labor shortages in scientific laboratories.
  • This approach enhances operational efficiency, safety, and accessibility of advanced laboratory techniques.
  • The study validates the potential of no-code automation to revolutionize laboratory practices and workforce development in STEM fields.