Infrared spectroscopy articles from across Nature Portfolio

Water at the surface of proteins is known to be critically important in maintaining their conformation and function, but the dynamics of the backbone hydration of peptides remains somewhat elusive. Here, the authors study the hydrogen-bonding structural dynamics of N-ethylpropionamide, a β-peptide model, in heavy water using nonlinear infrared spectroscopy and MD simulations.

Deep tissues can be imaged with high resolution and greater contrast by performing fluorescence imaging in the second near-infrared (NIR-II) window. This Primer summarizes how NIR-II fluorescence imaging can be used in animal models, exploring commonly used fluorophores and implementation approaches across a range of scientific and clinical applications.

A framework to break the inherent trade-off barrier between spectral resolution and operational bandwidth of integrated optical spectrometers is developed and demonstrated on thin-film lithium niobate without sacrificing the compact footprint.

Hole-doped polymer PEDOT:PSS shows high conductivity but the carrier transport mechanism is not yet clarified. Here, broadband optical conductivity spectra are derived using terahertz time-domain spectroscopy and far-infrared to-ultraviolet reflection spectroscopy, demonstrating band transport of hole carriers.

JWST collects vast amounts of information about exoplanets light years away from Earth. Back home, the measured optical constants of laboratory aerosols are critically input parameters in models to interpret the observational results.

We developed a high-content profiling method named vibrational painting (VIBRANT) for single-cell drug response measurements, combining vibrational imaging, multiplexed vibrational probes and machine learning. VIBRANT showed high performance in predicting drug mechanisms of action, discovering novel compounds and assessing drug combinations, demonstrating great promise for phenotypic drug discovery.

The accurate prediction of molecular spectra is essential for substance discovery and structure identification, but conventional quantum chemistry methods are computationally expensive. Now, DetaNet achieves the accuracy of quantum chemistry while improving the efficiency of prediction of organic molecular spectra.