Instrumental Methods

Instrumental methods encompass a broad array of analytical techniques that employ physical measurement systems—such as spectrometers, chromatographs, microscopes and electrochemical sensors—to probe the composition, structure and dynamics of chemical and biological samples. Spectroscopic approaches measure interactions between matter and electromagnetic radiation to identify molecular or elemental signatures, while chromatographic methods separate mixture components by differential affinity to stationary and mobile phases. Imaging modalities, from quantitative phase microscopy to Raman and coherent‐nonlinear techniques, visualise sample morphology and chemistry at high spatial resolution. Electrochemical and thermal instruments quantify redox activity and phase transitions, respectively, enabling kinetic and thermodynamic analyses. Advances in detector technology, microfluidics and artificial‐intelligence‐driven data processing have accelerated throughput, improved sensitivity to trace analytes and fostered portable, field‐deployable platforms. Together, these developments underpin applications from drug discovery and materials characterisation to environmental monitoring and precision diagnostics, delivering multidimensional insights with minimal sample quantities and often in real time.

Research from Nature Portfolio

A compact lens‐free holographic imaging device combined with deep‐learning algorithms has been shown to automate viral plaque assays without staining. By capturing gigapixel phase maps across standard multiwell plates and using a neural network trained on physics‐consistent loss functions, the system quantifies infected areas within hours, matching the dynamic range of conventional assays while preserving sample integrity.

A self‐supervised reconstruction framework has been introduced that enforces physical consistency between recorded holograms and object wave propagation. This approach, trained without labelled data, generalises across diverse holographic setups to recover both amplitude and phase images, demonstrating resilience to variations in recording distance, illumination wavelength and sensor parameters.

In cartilage research, layer‐resolved Raman spectroscopy integrated with coherent anti‐Stokes Raman scattering, second‐harmonic generation and two‐photon fluorescence imaging has discriminated healthy from osteoarthritic tissue with over 95 % accuracy. Multivariate analysis of spectral markers such as proline, hydroxyproline and sulphated glycosaminoglycans reveals depth‐dependent biochemical and structural alterations, offering a minimally invasive diagnostic tool for early osteoarthritis detection.

Research from all publishers

A high‐performance thin‐layer chromatography (HPTLC) platform interfaced with flexible, gold‐nanoparticle–infused cotton fabrics has enabled on‐site surface‐enhanced Raman spectroscopy (SERS) screening of the fungicide thiram in fruit juices. After chromatographic separation and elution, a handheld Raman spectrometer detects characteristic peaks at parts-per-million levels, achieving recoveries above 75 % in pear, apple and mango samples and demonstrating a facile point‐of‐care testing workflow.

Non-destructive SERS screening using copy paper loaded with silver nanoparticles has been applied to detect sulphite residues on shrimp surfaces. Moisture retained in the paper serves as a confined electrolyte for an electrochemical sensor, while characteristic Raman bands at 620 and 927 cm⁻¹ report sulphite levels down to sub-milligram-per-kilogram concentrations, suitable for routine monitoring in food processing.

Signal‐processing strategies combining complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet‐threshold filtering have been devised to enhance the extraction of fault‐related features from low signal-to-noise electrostatic emissions in aero-engine monitoring. This self-adaptive denoising framework outperforms traditional wavelet or empirical model decomposition methods in isolating wear-particle signatures under varying noise conditions.

Instrumental Methods publication trend

The graph below shows the total number of articles in instrumental methods across all publications each year (not limited to Nature Index journals).

Technical terms

Surface-enhanced Raman spectroscopy (SERS): A vibrational technique whereby analyte molecules adsorbed on nanostructured metallic surfaces produce greatly amplified Raman signals.

Lens-free holography: An imaging modality capturing diffraction patterns on a sensor without conventional optics, reconstructing phase and amplitude distributions computationally.

Self-supervised learning: A machine-learning paradigm that trains models using intrinsic data consistency constraints rather than external labels.

High-performance thin-layer chromatography (HPTLC): An advanced planar separation method using finely coated plates and controlled elution to resolve complex mixtures rapidly.

Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN): A signal decomposition algorithm that mitigates mode mixing by adding controlled noise ensembles to extract intrinsic oscillatory modes.

Wavelet threshold method: A denoising approach applying thresholding to wavelet-transformed signal coefficients to suppress noise while preserving salient features.

References

1. Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning. Nature Biomedical Engineering (2023).
2. Self-supervised learning of hologram reconstruction using physics consistency. Nature Machine Intelligence (2023).
3. Harnessing Raman spectroscopy and multimodal imaging of cartilage for osteoarthritis diagnosis. Scientific Reports (2024).
4. HPTLC + SRES screening of pesticide for point-of-care application as shown with thiram in juice. Food Chemistry X (2023).
5. Non-Destructive Screening of Sodium Metabisulfite Residue on Shrimp by SERS with Copy Paper Loaded with AgNP. Biosensors (2023).
6. Electrostatic Signal Self-Adaptive Denoising Method Combined with CEEMDAN and Wavelet Threshold. Aerospace (2024).