Mass Spectrometry, Surface Sampling and Dried Matrix Spots - Greener Chemistry and 3D Printing
- Photo: Concentrating on Chromatography: Mass Spectrometry, Surface Sampling and Dried Matrix Spots - Greener Chemistry and 3D Printing
- Video: Concentrating on Chromatography: Mass Spectrometry, Surface Sampling and Dried Matrix Spots - Greener Chemistry and 3D Printing
🎤Dan Reddy (PhD candidate in the Department of Chemistry at Queen's University and a recipient of the NSERC Vanier Canada Graduate Scholarship. He was recently named one of the top 35 early-career scientists globally in the 2025 CAS Future Leaders program.)
In this episode, we interview Daniel Reddy, 2025 CAS Future Leader and PhD candidate at Queen's University, about his groundbreaking research on automated mass spectrometry and dried matrix spots (DMS).
Dan's work combines computer vision, 3D printer automation, and laser micromachining to revolutionize sample preparation—reducing CO₂ emissions by 28-fold and organic solvent use by 21-fold compared to traditional methods.
What You'll Learn:
- How to give a mass spectrometer "sight" and "taste" using computer vision and the LMJ-SSP (Liquid Microjunction Surface Sampling Probe)
- The breakthrough technology behind Surface Energy Traps (SETs) for confining liquid droplets on paper substrates
- Why dried matrix spots eliminate the need for cold-chain shipping and enable analysis of blood, urine, and saliva samples via standard mail
- How DIY chemists are hacking 3D printers to build cost-effective autosamplers (replacing $10K+ systems)
- The role of green chemistry and systems thinking in modernizing analytical methods
- Why interdisciplinary collaboration (chemistry + computer science) is critical to innovation
Key Topics:
- Dried Matrix Spots (DMS) for automated sample prep
- Laser-micromachined Surface Energy Traps
- Direct surface sampling mass spectrometry
- Sustainability in analytical chemistry
- 3D printer customization for laboratory automation
- The importance of science communication and community outreach
Video Transcription
Introduction
Recent advances in analytical chemistry increasingly focus on simplifying workflows, improving sustainability, and enabling automation. In this context, the work of Dan Reddy centers on the concept of “bringing mass spectrometry to life” through the integration of automated sampling, computer vision, and dried matrix spot (DMS) methodologies.
The primary objective is to enable efficient and reproducible analysis of biological and liquid samples—such as blood, urine, saliva, or other solutions—by depositing them onto substrates, drying them, and extracting meaningful analytical information directly via mass spectrometry.
Conceptual Framework: Enabling “Sight” and “Taste” in Mass Spectrometry
A central innovation in this work is the conceptual transformation of mass spectrometry from a passive analytical tool into an active, semi-autonomous system.
- “Sight” is introduced through camera-based computer vision, allowing the system to identify predefined patterns on a substrate.
- “Taste” is implemented via a liquid microjunction surface sampling probe (LMJSSP), which enables direct extraction of analytes from surfaces.
The LMJSSP consists of two concentric capillaries forming a continuously flowing microdroplet. When brought into contact with the sample surface, this droplet facilitates localized extraction, effectively enabling direct surface analysis without traditional chromatographic separation.
Combined with an automated positioning system (adapted from 3D printer mechanics), the platform can autonomously locate sampling sites and perform reproducible measurements.
Dried Matrix Spots as an Analytical Platform
Principle and Advantages
Dried matrix spots involve depositing a small volume of liquid sample onto a substrate (commonly paper), followed by drying. This approach offers several advantages:
- Reduced need for cold-chain transport
- Simplified sample handling and storage
- Compatibility with remote or decentralized sampling
- Lower solvent consumption
These features contribute significantly to greener analytical workflows and improved logistical efficiency.
Sustainability Impact
The implementation of DMS-based workflows has demonstrated:
- Up to 28-fold reduction in CO₂ emissions
- Up to 21-fold reduction in organic solvent use
These improvements arise from eliminating cold-chain logistics and minimizing solvent-intensive preparation steps.
Surface Energy Traps (SCTs): Controlled Micro-Sampling Environments
Definition and Fabrication
Surface Energy Traps (SCTs) are microstructured regions on a substrate designed to confine liquid droplets within defined boundaries.
The fabrication process involves:
- Coating paper with a hydrophobic layer
- Using laser ablation to selectively remove the coating in defined patterns
- Creating hydrophilic circular regions (typically ~0.5 mm diameter)
These patterned regions act as micro-wells that confine droplets spatially and prevent lateral diffusion.
Analytical Benefits
SCTs address key limitations of traditional dried matrix spots:
- Improved spatial confinement of analytes
- Reduced diffusion variability
- Enhanced reproducibility
- Preconcentration effects due to controlled drying
Additionally, the SCT diameter is smaller than the sampling probe, enabling near-complete analyte collection during surface extraction.
Drying Dynamics and Analyte Distribution
Traditional dried matrix spots often suffer from the “coffee-ring effect”, where analytes redistribute unevenly during drying. This leads to variability depending on sampling location.
The SCT approach mitigates these effects by:
- Limiting diffusion area
- Maintaining analytes near the surface
- Producing more uniform analyte distribution
Preliminary investigations (e.g., via SEM imaging) indicate improved homogeneity, although further studies are needed to fully characterize drying kinetics and their influence on signal intensity.
Integration with Automated Sampling Systems
3D Printer-Based Positioning
A key engineering innovation is the repurposing of 3D printer hardware for automated sample positioning:
- Provides cost-effective XYZ motion control
- Enables programmable sampling routines
- Supports integration with analytical instrumentation
Custom software—developed in collaboration with computer engineers—allows users to define coordinates, dwell times, and sampling parameters.
Computer Vision Integration
The addition of computer vision enables:
- Pattern recognition (e.g., alignment markers near SCTs)
- Autonomous targeting of sampling locations
- Reduced operator intervention
This transforms the system into a semi-autonomous analytical platform.
Comparison with Conventional Workflows
Compared to traditional LC-MS or GC-MS workflows, the presented approach offers:
| Aspect | Conventional Methods | SCT + LMJSSP Approach |
|---|---|---|
| Sample prep | Multi-step, solvent-intensive | Minimal, direct surface sampling |
| Chromatography | Required | Potentially bypassed |
| Throughput | Moderate | High (automated) |
| Sustainability | Limited | Significantly improved |
While chromatographic methods remain essential for many applications, this approach provides a complementary pathway for rapid screening and targeted analyses.
Green Chemistry and Systems Thinking
A notable aspect of this work is the integration of systems thinking into analytical chemistry. Inspired by engagement with organizations such as the American Chemical Society and green chemistry initiatives, the research emphasizes:
- Environmental impact reduction
- Resource efficiency
- Lifecycle considerations
This perspective expands the role of analytical chemists beyond method performance to broader societal and environmental implications.
Future Outlook and Applications
The research is currently at an early stage but shows strong potential for:
- Decentralized diagnostics (e.g., remote blood sampling)
- Environmental monitoring
- High-throughput screening workflows
- Field-deployable analytical systems
Further advancements are expected in:
- Substrate engineering
- Automation robustness
- Integration with advanced MS platforms (e.g., triple quadrupole systems)
Conclusion
The integration of dried matrix spots, surface energy traps, and automated surface sampling represents a significant step toward more sustainable, efficient, and accessible analytical workflows.
By combining innovations in microfabrication, computer vision, and mass spectrometry, the work of Dan Reddy demonstrates how analytical chemistry can evolve toward smarter, greener, and more autonomous systems.
This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.
Concentrating on Chromatography Podcast
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