Baby Food: Achieving Lower Detection Limits in Pursuit of “Closer to Zero”

The following articles are the most accessed digital object identifier (DOI) manuscripts for Spectroscopy and LCGC International during the month of August 2026. Ten articles are individually ranked here by DOI page views.

This interactive e-book celebrates National Forensic Science Week by highlighting the vital role of spectroscopy in modern criminal investigations and emphasizing how technological innovation is making forensic analysis faster, safer, and more reliable for courtroom testimony.

An upcoming talk at SciX 2026 Conference will describe a new multimodal platform using laser ablation inductively coupled plasma–mass spectrometry (LA-ICP-MS) elemental mapping that can detect nanoparticles and microplastics in biological tissue.

Top content published this week include a feature article on a new innovation called the Personalized Optical Digital Twin (PODT), a recap of the International Conference on Raman Spectroscopy (ICORS) 2026 show, and a Q&A on measuring nanoparticle formation in indoor air.

In the final part of our conversation with Brandon Boor of Purdue University, he explains the respiratory deposition model his team used to analyze indoor particle exposure.

In the second part of our interview with Brandon Boor of Purdue University, he discusses how his team controls experimental variables during cleaning experiments in order to obtain interpretable data.

An upcoming interview with Ji-Xin Cheng, a Theodore Moustakas Distinguished Professor in Photonics and Optoelectronics at Boston University, will highlight his ongoing work in coherent Raman scattering microscopy.

The bulky bench-top NIR spectrometer is quietly being dismantled and rebuilt as a wafer-scale photonic chip, a self-calibrating algorithm, and a sensor small enough to ride in a shirt pocket. What once demanded a grating, a moving mirror, and a climate-controlled lab now fits inside a handheld module, a bioreactor probe, or a drone payload, and it increasingly figures out what it is looking at on its own.