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The 'Jumbo Shrimp' Problem in Microfluidics
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The 'Jumbo Shrimp' Problem in Microfluidics
a day ago
by
Will Wetzel
The Dirty Secret of 'Dirt Cheap' Lithium Sulfur Batteries
1:23
The Dirty Secret of 'Dirt Cheap' Lithium Sulfur Batteries
5 days ago
by
Will Wetzel
Identifying Cancer Cells by Metabolism
1:23
Identifying Cancer Cells by Metabolism
8 days ago
by
Will Wetzel
We Separate Cancer Cells By Physics, Not Antibodies
0:41
We Separate Cancer Cells By Physics, Not Antibodies
12 days ago
by
Will Wetzel
Universal Sensors Are Like Radios Without Tuning Knobs!
0:46
Universal Sensors Are Like Radios Without Tuning Knobs!
15 days ago
by
Will Wetzel
The Key to Selective Actinide Extraction
0:50
The Key to Selective Actinide Extraction
19 days ago
by
Will Wetzel
ML & Spectroscopy: The Future of Pathology
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ML & Spectroscopy: The Future of Pathology
22 days ago
by
Will Wetzel
Seeing The Raman Signal From 1-3 Molecules
0:52
Seeing The Raman Signal From 1-3 Molecules
25 days ago
by
Will Wetzel
Not Your Grandfather’s NMR
0:40
Not Your Grandfather’s NMR
a month ago
by
Caroline Hroncich
Controlling Selectivity via Molecular Structure
0:57
Controlling Selectivity via Molecular Structure
a month ago
by
Will Wetzel

A Beginner’s Guide to Spectroscopy in Energy Applications

An Overview for New Spectroscopists

A Beginner’s Guide to Spectroscopy in Energy Applications

Recent Research in Chemometrics and AI for Spectroscopy, Part I

Foundations, Definitions, and the Integration of AI in Chemometric Analysis

Recent Research in Chemometrics and AI for Spectroscopy, Part I

Testing a New Deep Learning Model for Petroleum Analysis

An Inside Look

Testing a New Deep Learning Model for Petroleum Analysis

Microplastics Widespread on Catalan Beaches, Study Finds

Read About This Study Here!

Microplastics Widespread on Catalan Beaches, Study Finds

Recent Research in Chemometrics and AI for Spectroscopy, Part II

Emerging Applications, Explainable AI, and Future Trends

Recent Research in Chemometrics and AI for Spectroscopy, Part II

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In this part of our ongoing review of the infrared spectra of carbonyl-containing functional groups, we will study the spectra of esters and carbonates. Esters are ubiquitous in our food and medicines, and polymeric carbonates form an important part of the materials around us. As always, concepts will be illustrated with reference spectra.

Spectroscopy is rapidly evolving, and professionals who build expertise in AI-driven analytics, automation, and high-demand sectors like pharma, biotech, and materials science will be best positioned to advance their careers despite industry-wide talent and budget challenges.

2025 was a turning point for vibrational spectroscopy © somchai20162516

In 2025, the vibrational-spectroscopy community saw a convergence of deep learning, advanced simulation, and portable instrumentation that materially changed how spectra are interpreted and applied. Breakthroughs in spectrum-to-structure models, machine learning (ML)-accelerated molecular dynamics, and field-deployable classic Raman, near-infrared (NIR), and surface-enhanced Raman spectroscopy (SERS) sensors pushed vibrational techniques from complex laboratory characterization toward automated structure elucidation, rapid analysis, and real-world sample sensing (1–6,9). This summary article highlights key 2025 contributions and their implications for the year of discovery.

A recent study provides a detailed introduction to uniform manifold approximation and projection (UMAP) for analyzing LA-ICP-TOF-MS data. By converting high-dimensional MSI data into two-dimensional spaces, UMAP facilitates automated visualization to identify spectral clusters. Spectroscopy spoke to the paper’s lead author, Katharina Kronenberg of the University of Graz, about her group’s work.