Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Privacy-aware community infrastructureResearch graph
References from Chemical proximity governs open-world infrared identification of microplastics using dual-evidence calibration. Local targets link to admitted publications; unresolved targets remain external evidence.
Validation of ATR FT-IR to identify polymers of plastic marine debris, including those ingested by marine organisms
10.1016/j.marpolbul.2017.12.061 · 2018 · External reference
FTIR-plastics: a Fourier transform infrared spectroscopy dataset for the six most prevalent industrial plastic polymers
10.1016/j.dib.2024.110612 · 2024 · External reference
μATR-FTIR spectral libraries of plastic particles (FLOPP and FLOPP-e) for the analysis of microplastics
10.1021/acs.analchem.1c02549 · 2021 · External reference
Lost at sea: where is all the plastic?
10.1126/science.1094559 · 2004 · External reference
Chemical analysis of microplastics and Nanoplastics: challenges, advanced methods, and perspectives
10.1021/acs.chemrev.1c00178 · 2021 · External reference
Microplastics in the marine environment: a review of the methods used for identification and quantification
10.1021/es2031505 · 2012 · External reference
Critical review of processing and classification techniques for images and spectra in microplastic research
10.1177/0003702820929064 · 2020 · External reference
The identification of microplastics based on vibrational spectroscopy data – a critical review of data analysis routines
10.1016/j.trac.2022.116535 · 2022 · External reference
Development of a new hyperspectral imaging technology with autoencoder-assisted generative adversarial network for predicting the content of polyunsaturated fatty acids in red meat
10.1016/j.compag.2024.108842 · 2024 · External reference
Synergizing meat science and AI: Enhancing long-chain saturated fatty acids prediction
10.1016/j.compag.2024.108931 · 2024 · External reference
Synergizing meat science and AI: Enhancing long-chain saturated fatty acids prediction
10.1016/j.compag.2024.108931 · 2024 · External reference
Machine learning outperforms humans in microplastic characterization and reveals human labelling errors in FTIR data
10.1016/j.jhazmat.2024.136989 · 2025 · External reference
Reference database design for the automated analysis of microplastic samples based on Fourier transform infrared (FTIR) spectroscopy
10.1007/s00216-018-1156-x · 2018 · External reference
Automated characterization and identification of microplastics through spectroscopy and chemical imaging in combination with chemometric: latest developments and future prospects
10.1016/j.trac.2023.116956 · 2023 · External reference
Quantum cascade laser imaging (LDIR) and machine learning for the identification of environmentally exposed microplastics and polymers
10.1016/j.envres.2022.113569 · 2022 · External reference
Investigation of new analysis methods for simultaneous and rapid identification of five different microplastics using ATR-FTIR spectroscopy and chemometrics
10.1016/j.envpol.2024.125043 · 2024 · External reference
Hybrid deep learning framework for environmental microplastic classification: integrating CNN-based spectral feature extraction and transformer models
10.1016/j.envpol.2025.126989 · 2025 · External reference
A new Chemometric approach for automatic identification of microplastics from environmental compartments based on FT-IR spectroscopy
10.1021/acs.analchem.7b02472 · 2017 · External reference
Robust automatic identification of microplastics in environmental samples using FTIR microscopy
10.1021/acs.analchem.9b01095 · 2019 · External reference
Moving toward automated μFTIR spectra matching for microplastic identification: addressing false identifications and improving accuracy
10.1186/s43591-024-00106-5 · 2024 · External reference
Increasing the accessibility for characterizing microplastics: introducing new application-based and spectral libraries of plastic particles (SLoPP and SLoPP-E)
10.1021/acs.analchem.9b03626 · 2020 · External reference
Microplastic spectral classification needs an open source community: open Specy to the rescue!
10.1021/acs.analchem.1c00123 · 2021 · External reference
Open Specy 1.0: automated (hyper)spectroscopy for microplastics
10.1021/acs.analchem.5c00962 · 2025 · External reference
Raman spectra for plastics identification (RaSPI) and Raman maps for plastics identification (RaMPI) datasets
10.1038/s41597-026-07103-8 · 2026 · External reference
Comparison of Raman and Fourier transform infrared spectroscopy for the quantification of microplastics in the aquatic environment
10.1021/acs.est.8b03438 · 2018 · External reference
A Raman spectral reference library of potential anthropogenic and biological ocean polymers
10.1038/s41597-022-01883-5 · 2022 · External reference
Unresolved reference
2025 · External reference
Customizable machine-learning models for rapid microplastic identification using Raman microscopy
10.1021/acs.analchem.2c02451 · 2022 · External reference
Integrating C–H information to improve machine learning classification models for microplastic identification from Raman spectra
10.1021/acs.analchem.4c05197 · 2025 · External reference
A modular convolutional neural network framework for Raman spectra-based identification of environmental microplastics
10.1016/j.watres.2026.126308 · 2026 · External reference
FTIR and Raman imaging for microplastics analysis: state of the art, challenges and prospects
10.1016/j.trac.2019.115629 · 2019 · External reference
Enhanced prediction of total purine content in hyperspectral images of diverse livestock meat samples using optimization algorithm
10.1016/j.foodres.2025.116000 · 2025 · External reference
Machine learning for polycyclic aromatic hydrocarbons analysis in roasted lamb: New insights from spectral and chemical data
10.1016/j.foodchem.2025.145727 · 2025 · External reference
Recent advances in open set recognition: a survey
10.1109/tpami.2020.2981604 · 2021 · External reference
10.1561/2200000101 · 2023 · Admitted local publication
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
10.1038/s41467-022-34945-8 · 2022 · External reference
On calibration of modern neural networks
2017 · External reference
Enhancing confidence in microplastic spectral identification via conformal prediction
10.1021/acs.est.4c05167 · 2024 · External reference
Unveiling uncertainty in microplastic quantification: artificial intelligence integrated Raman analysis
10.1016/j.jhazmat.2026.141763 · 2026 · External reference
A local pre-processing method for near-infrared spectra, combined with spectral segmentation and standard normal variate transformation
10.1016/j.aca.2016.01.010 · 2016 · External reference
Smoothing and differentiation of data by simplified least squares procedures
10.1021/ac60214a047 · 1964 · External reference
Unresolved reference
2005 · External reference
Deep learning for reconstructing low-quality FTIR and Raman spectraa case study in microplastic analyses
10.1021/acs.analchem.1c02618 · 2021 · External reference
A Raman spectral database of naturally aged plastics: a proof-of-concept study for waste plastic sorting
10.1002/jrs.6484 · 2023 · External reference
Development of a multi-spectroscopy method coupling μ-FTIR and μ-Raman analysis for one-stop detection of microplastics in environmental and biological samples
10.1016/j.scitotenv.2024.170396 · 2024 · External reference
Identification and quantification of tire wear particles by employing different cross-validation techniques: FTIR-ATR Micro-FTIR, Pyr-GC/MS, and SEM
10.1016/j.envpol.2023.121511 · 2023 · External reference
Does microplastic analysis method affect our understanding of microplastics in the environment?
10.1016/j.scitotenv.2023.166513 · 2023 · External reference
Microplastic identification and quantification from organic rich sediments: a validated laboratory protocol
10.1016/j.envpol.2020.114298 · 2020 · External reference
