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Articles

A research team has utilized the Allan variance technique to analyze the performance characteristics of compact Fourier transform infrared (FT-IR) spectrometers. The study provides insights into the noise sources and instabilities of these handheld instruments, offering guidance for improving their accuracy and stability in real-time material detection and quantification applications.

Analysis Reveals Performance Characteristics of Compact Fourier Transform Infrared Spectrometers

In this interview, James Chapman discusses his current and future research efforts, and how combining spectroscopy with machine learning tools can change how bacterial research is conducted.

New Analytical Tools for Biomedical Applications Using Machine Learning and Spectroscopy

Howard Mark serves on the Editorial Advisory Board of 

 and runs a consulting service, Mark Electronics that provides assistance, training, and consultation in near-IR spectroscopy as well as custom hardware and software design and development.

A sample library of selected references discussing the application of artificial intelligence (AI) in analytical chemistry and molecular spectroscopy is presented.

Artificial Intelligence in Analytical Spectroscopy, Part II: Examples in Spectroscopy

A new publication explores the concept of secondary model-based examination of model-free analysis results in chemical data, revealing hidden insights. His research highlights the significance of integrating quantitative model-based evaluations to enhance data interpretation and extract valuable information.

Exploring Secondary Model-Based Examination of Model-Free Analysis Results: Unveiling Hidden Insights in Chemical Data

Researcher team questions the effectiveness of core consistency as a diagnostic tool in fluorescence analysis of complex samples. A new study suggests the need for alternative methods to accurately determine model complexity in such analyses.

New Study Challenges Diagnostic Tool for Fluorescence Analysis of Complex Samples

We interviewed an AI program (ChatGPT) for Spectroscopy asking questions about AI and its role in various applications for vibrational and atomic spectroscopy, including data analysis. 

An Interview with AI About Its Potential Role in Vibrational and Atomic Spectroscopy

The relationship between leaf nitrogen content (LNC) and hyperspectral remote sensing imagery (HYP) was determined to construct an estimation model of the LNC of drip-irrigated sugar beets, to enable real-time monitoring of sugar beet growth and nitrogen management in arid areas.

Study on Estimating Total Nitrogen Content in Sugar Beet Leaves Under Drip Irrigation Based on Vis-NIR Hyperspectral Data and Chlorophyll Content

In combination with attenuated total reflectance (ATR), Fourier transform infrared (FT-IR) spectroscopy can be used to classify different moss species.

Efficient Discrimination of Some Moss Species by Fourier Transform Infrared Spectroscopy and Chemometrics

Are you intrigued by artificial intelligence, but unsure what it really means for analytical chemistry? Read on.

Artificial Intelligence in Analytical Spectroscopy, Part I: Basic Concepts and Discussion

The past decision to use binary representation in computer architectures affects the results of chemometric-based outputs, especially if different data values are used.

Data Analytics, Statistics, Chemometrics, and Artificial Intelligence