Recent literature suggests that the fields of machine learning (ML) and high-throughput
experimentation (HTE) have separately received considerable attention from chemists and …

Improved methods of analysis, ie, faster, more discriminatory, more sensitive, less costly,
etc., are needed for all abused substances. Additionally, standard analytical data are …

Due to the diversity and fast evolution of new psychoactive substances (NPS), both public
health and safety are threatened around the world. Attenuated total reflection-Fourier …

In recent years, fentanyl and its analogs have been increasingly abused, leading to tragic
outcomes. One way to tackle this problem is to rapidly detect fentanyl analog compounds …

Artificial intelligence (AI) represents a potential moonshot in the drug use field in terms of
primary prevention—that is, preventing drug use initiation—and in reducing morbidities …

The added value of supervised Machine Learning (ML) methods to determine the Absolute
Configuration (AC) of compounds from their Vibrational Circular Dichroism (VCD) spectra …

Multiple analytical techniques for the screening of fentanyl‐related compounds exist. High
discriminatory methods such as GC–MS and LC–MS are expensive, time‐consuming, and …

Spectroscopic techniques such as infrared spectroscopy and Raman spectroscopy are used
for a long time in the context of the analysis of illicit drugs, and their use is increasing due to …

Abstract Machine learning methods were combined with differential absorption spectroscopy
measurements in the vacuum-ultraviolet region (5.167–9.920 eV) in order to develop …

Ion mobility spectrometry (IMS) is the method of choice to detect trace amounts of explosives
in most airports and border crossing settings. For most explosives, the IMS detection limits …