The sequence of changes observed during degradation process of paper by the use of UV/VIS and FTIR spectrometry with application of the PCA and 2D correlation method for forensic purposes

One-class modelling applied to ATR-FTIR spectroscopy for determining document forgeries related to paper aging

One of the great challenges of document analysis is determining document forgeries. The present work proposes a non-destructive approach to discriminate natural and artificially aged papers using infrared spectroscopy and soft independent modeling by class analogy (SIMCA) algorithms. This is of particular interest in cases of document falsifications made by artificial aging, for this study, SIMCA, and Data-Driven SIMCA (DD-SIMCA) classification models were built using naturally aged paper samples, taken from three time periods: 1st period from 1998 to 2003; 2nd period from 2004 to 2009; and 3rd period from 2010 to 2015. Artificially aged samples (exposed to high temperature or UV radiation) were used as test sets. Promising results in detecting document falsifications related to aging were obtained. Samples artificially aged at high temperature were correctly discriminated from the authentic samples (naturally aged) with 100% accuracy. In contrast, the samples under the photodegradation process showed a lower classification performance, with results above 90%.

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.

Sustainable multifunctional zinc oxide quantum dots-aided double-layers security paper sheets

Fluorescence is well-known nowadays as one of the most efficient anti-counterfeiting techniques. Zinc oxide quantum dots (ZnOQds) are exceptionally fluorescence when exposed to ultraviolet (UV) light, which makes them a candidate for anti-counterfeiting printing. The resulting anti-counterfeiting papers are sustainable and resistance against organic dyes. In this work, ZnOQds were prepared via a green method and characterized under UV-visible spectroscopy, along with microscopic observations by transmission electron microscopy (TEM) and crystallography by X-ray diffraction (XRD). Formation of ZnOQds nanocrystals with an average partials size of 7.3 nm was approved. Additionally, double-layers sheets were prepared at two loading concentrations of ZnOQds, namely 0.5 and 1 (wt./v) and underwent characterization using a topographical surface study via field emission scanning electron microscopy (FE-SEM). Hybrid sheets were mechanically more stable compared to single-layer paper and likewise polymer film. Moreover, aging simulation approved a high stability for hybrid sheets. Particularly, the photoluminescence emission affirmed anti-aging character of hybrid paper for more than 25 years. The hybrid sheets also showed a broad range of antimicrobial activity.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS): Part III. Versatile applications

In this review, the comprehensive summary of two-dimensional correlation spectroscopy (2D-COS) for the last two years is covered. The remarkable applications of 2D-COS in diverse fields using many types of probes and perturbations for the last two years are highlighted. IR spectroscopy is still the most popular probe in 2D-COS during the last two years. Applications in fluorescence and Raman spectroscopy are also very popularly used. In the external perturbations applied in 2D-COS, variations in concentration, pH, and relative compositions are dramatically increased during the last two years. Temperature is still the most used effect, but it is slightly decreased compared to two years ago. 2D-COS has been applied to diverse systems, such as environments, natural products, polymers, food, proteins and peptides, solutions, mixtures, nano materials, pharmaceuticals, and others. Especially, biological and environmental applications have significantly emerged. This survey review paper shows that 2D-COS is an actively evolving and expanding field.

Lignin and Xylan as Interface Engineering Additives for Improved Environmental Durability of Sustainable Cellulose Nanopapers

Cellulose materials and products are frequently affected by environmental factors such as light, temperature, and humidity. Simulated UV irradiation, heat, and moisture exposure were comprehensively used to characterize changes in cellulose nanopaper (NP) tensile properties. For the preparation of NP, high-purity cellulose from old, unused filter paper waste was used. Lignin and xylan were used as sustainable green interface engineering modifiers for NP due to their structural compatibility, low price, nontoxic nature, and abundance as a by-product of biomass processing, as well as their ability to protect cellulose fibers from UV irradiation. Nanofibrillated cellulose (NFC) suspension was obtained by microfluidizing cellulose suspension, and NP was produced by casting films from water suspensions. The use of filler from 1 to 30 wt% significantly altered NP properties. All nanopapers were tested for their sensitivity to water humidity, which reduced mechanical properties from 10 to 40% depending on the saturation level. Xylan addition showed a significant increase in the specific elastic modulus and specific strength by 1.4- and 2.8-fold, respectively. Xylan-containing NPs had remarkable resistance to UV irradiation, retaining 50 to 90% of their initial properties. Lignin-modified NPs resulted in a decreased mechanical performance due to the particle structure of the filler and the agglomeration process, but it was compensated by good property retention and enhanced elongation. The UV oxidation process of the NP interface was studied with UV-Vis and FTIR spectroscopy, which showed that the degradation of lignin and xylan preserves a cellulose fiber structure. Scanning electron microscopy images revealed the structural formation of the interface and supplemented understanding of UV aging impact on the surface and penetration depth in the cross-section. The ability to overcome premature aging in environmental factors can significantly benefit the wide adaption of NP in food packaging and functional applications.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Non-destructive analysis the dating of paper based on convolutional neural network

A non-destructive method based on Fourier Transformed Infrared Spectroscopy (FT-IR) was proposed to estimate the date of paper from different years in this article. For the paper samples, dated from 1940 to 1980, naturally aged and conserved in library. Partial least squares-discriminate analysis (PLS-DA), Logistic regression and convolutional neural network (CNN), were employed to evaluate the date of paper, with the accuracy 60.74%, 95.31% and 98.77%, respectively. Based on the characteristics of CNN model and with the help of network localization, active variables could be recognized in the whole spectrum. Although the localization of active variables showed a discriminative pattern, the selected spectral regions were similar. Most important variables focused on the 1700-1400 cm^-1, were corresponding to cellulose crystallinity, which was consisted with the ageing processing. The present work gave the potential of FT-IR combined with chemometric techniques could estimate the dating of unknown paper. Meanwhile, the analysis of active variables obtained further indicated the worthy of CNN model for document dating.

Adsorption Strategy for Removal of Harmful Cyanobacterial Species Microcystis aeruginosa Using Chitosan Fiber

Microcystis aeruginosa is one of the predominant species responsible for cyanobacterial-harmful algal blooms (Cyano-HABs) in water bodies. Cyano-HABs pose a growing number of serious threats to the environment and public health. Therefore, the demand for developing safe and eco-friendly solutions to control Cyano-HABs is increasing. In the present study, the adsorptive strategy using chitosan was applied to remove M. aeruginosa cells from aqueous phases. Using a simple immobilization process, chitosan could be fabricated as a fiber sorbent (chitosan fiber, CF). By application of CF, almost 89% of cyanobacterial cells were eliminated, as compared to those in the control group. Field emission scanning electron microscopy proved that the M. aeruginosa cells were mainly attached to the surface of the sorbent, which was correlated well with the measurement of the surface area of the fiber. We tested the hypothesis that massive applications of the fabricated CF to control Cyano-HABs might cause environmental damage. However, the manufactured CF displayed negligible toxicity. Moreover, we observed that the release of cyanotoxins and microcystins (MCs), during the removal process using CF, could be efficiently prevented by a firm attachment of the M. aeruginosa cells without cell lysis. Our results suggest the possibility of controlling Cyano-HABs using a fabricated CF as a non-toxic and eco-friendly agent for scaled-up applications.