Recent advances and applications to cultural heritage using ATR-FTIR spectroscopy and ATR-FTIR spectroscopic imaging

Enhancing cellulose acetate biodegradability in cigarette filters: an in-depth analysis of thermal alkaline pretreatment, microbial dynamics, and breakdown pathway prediction

BACKGROUND

The demand for bioplastics has increased exponentially as they have emerged as alternatives to petrochemical plastics. However, there is a substantial lack of knowledge regarding bioplastic degradation. This study developed a novel pretreatment method to improve the accessibility of a bioplastic substrate for biodegradation. In this study, cellulose acetate, a bioplastic found in the world's most littered waste, e.g. cigarette filters, was selected as a potential substrate. Before anaerobic digestion, three thermal alkaline pretreatments: TA 30 °C, TA 90 °C, and TA 121 °C, were used to evaluate their effects on the chemical alterations of cellulose acetate.

RESULT

The ester groups in cellulose acetate were significantly reduced by the TA 30 °C pretreatment, as seen by a decrease in C = O stretching vibrations and shortening of C - O stretches (1,270 ∼ 1,210 cm- 1), indicating effective removal of acetyl groups. This pretreatment significantly enhanced cellulose acetate biodegradability to a maximum of 91%, surpassing the previously reported cellulose acetate degradation. Methane production increased to 695.0 ± 4 mL/g of volatile solid after TA 30 °C pretreatment, indicating enhanced cellulose acetate accessibility to microorganisms, which resulted in superior biogas production compared to the control (306.0 ± 10 mL/g of volatile solid). Diverse microbes in the anaerobic digestion system included hydrolytic (AB240379_g, Acetomicrobium, FN436103_g, etc.), fermentative, and volatile fatty acids degrading bacteria (JF417922_g, AB274492_g, Coprothermobacter, etc.), with Methanobacterium and Methanothermobacter being the sole hydrogenotrophic methanogens in the anaerobic digestion system. Additionally, an attempt to predict the pathway for the effective degradation of cellulose acetate from the microbial community in different pretreatment conditions.

CONCLUSIONS

To the best of our knowledge, this is the first study to estimate the maximum cellulose acetate degradation rate, with a simple and cost-effective pretreatment procedure. This approach holds promise for mitigating the environmental impact of cellulose acetate of cigarette filters and presents a sustainable and economically viable waste management strategy.

Graphormer-IR: Graph Transformers Predict Experimental IR Spectra Using Highly Specialized Attention

Infrared (IR) spectroscopy is an important analytical tool in various chemical and forensic domains and a great deal of effort has gone into developing in silico methods for predicting experimental spectra. A key challenge in this regard is generating highly accurate spectra quickly to enable real-time feedback between computation and experiment. Here, we employ Graphormer, a graph neural network (GNN) transformer, to predict IR spectra using only simplified molecular-input line-entry system (SMILES) strings. Our data set includes 53,528 high-quality spectra, measured in five different experimental media (i.e., phases), for molecules containing the elements H, C, N, O, F, Si, S, P, Cl, Br, and I. When using only atomic numbers for node encodings, Graphormer-IR achieved a mean test spectral information similarity (SISμ) value of 0.8449 ± 0.0012 (n = 5), which surpasses that the current state-of-the-art model Chemprop-IR (SISμ = 0.8409 ± 0.0014, n = 5) with only 36% of the encoded information. Augmenting node embeddings with additional node-level descriptors in learned embeddings generated through a multilayer perceptron improves scores to SISμ = 0.8523 ± 0.0006, a total improvement of 19.7σ (t = 19). These improved scores show how Graphormer-IR excels in capturing long-range interactions like hydrogen bonding, anharmonic peak positions in experimental spectra, and stretching frequencies of uncommon functional groups. Scaling our architecture to 210 attention heads demonstrates specialist-like behavior for distinct IR frequencies that improves model performance. Our model utilizes novel architectures, including a global node for phase encoding, learned node feature embeddings, and a one-dimensional (1D) smoothing convolutional neural network (CNN). Graphormer-IR's innovations underscore its value over traditional message-passing neural networks (MPNNs) due to its expressive embeddings and ability to capture long-range intramolecular relationships.

A Simple Doublet Lens Design for Mid-Infrared Imaging

Wide-field mid-infrared (MIR) hyperspectral imaging offers a promising approach for studying heterogeneous chemical systems due to its ability to independently characterize the molecular properties of different regions of a sample. However, applications of wide-field MIR microscopy are limited to spatial resolutions no better than ∼1 μm. While methods exist to overcome the classical diffraction limit of ∼λ/2, chromatic aberration from transmissive imaging reduces the achievable resolution. Here we describe the design and implementation of a simple MIR achromatic lens combination that we believe will aid in the development of resolution-enhanced wide-field MIR hyperspectral optical and chemical absorption imaging. We also examine the use of this doublet lens to image through polystyrene microspheres, an emerging and simple means for enhancing spatial resolution.

Non-invasive analysis of reference glass and historical mosaic tesserae by means of reflectance infrared spectroscopy

Within vibrational spectroscopy techniques, Raman is much more employed than infrared spectroscopy for the study of glassy materials belonging to cultural heritage. This could be due to both a less straightforward interpretation of the spectra and a more difficult application of the technique with portable instrumentations. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) can be exploited in archaeometric investigations because portable and non-invasive. On the other hand, no systematic applications of this technique to historical glasses are found in the literature. This exploratory work reports the DRIFTS investigation of the Corning Archaeological Reference Glasses, widely used as references in the cultural heritage field, and of real case glass samples, with the aim of exploring the potential of this technique to gain information about their composition and alteration. The results, exploiting the association of portable X-ray Fluorescence (pXRF), and, where possible, of EDS microanalyses, are encouraging, setting the samples within a compositional range and highlighting spectral differences for the altered surfaces.

Analysis and comparison of machine learning methods for species identification utilizing ATR-FTIR spectroscopy

Accurate identification of insect species holds paramount significance in diverse fields as it facilitates a comprehensive understanding of their ecological habits, distribution range, and impact on both the environment and humans. While morphological characteristics have traditionally been employed for species identification, the utilization of empty pupariums for this purpose remains relatively limited. In this study, ATR-FTIR was employed to acquire spectral information from empty pupariums of five fly species, subjecting the data to spectral pre-processing to obtain average spectra for preliminary analysis. Subsequently, PCA and OPLS-DA were utilized for clustering and classification. Notably, two wavebands (3000-2800 cm-1 and 1800-1300 cm-1) were found to be significant in distinguishing A. grahami. Further, we established three machine learning models, including SVM, KNN, and RF, to analyze spectra from different waveband groups. The biological fingerprint region (1800-1300 cm-1) demonstrated a substantial advantage in identifying empty puparium species. Remarkably, the SVM model exhibited an impressive accuracy of 100 % in identifying all five fly species. This study represents the first instance of employing infrared spectroscopy and machine learning methods for identifying insect species using empty pupariums, providing a robust research foundation for future investigations in this area.

Laser-based analytical techniques in cultural heritage science - Tutorial review

This tutorial review combines the fundamentals of the design and operation of lasers with their usage in applications related to conservation and cultural heritage (CH) science - as components of analytical devices for the study of the chemical composition of materials. The development of laser instruments and their fundamental physical background, including a short explanation of their properties and parameters, are briefly summarised, and an overview of different laser-based analytical techniques is given. The analytical techniques covered in this tutorial are divided into three groups based on their technical aspects and properties: (1) vibrational spectroscopy, (2) elemental analysis, and (3) different molecular mass spectrometric techniques.

Sex Determination of Human Nails Based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy in Forensic Context

This study reports on the successful use of a machine learning approach using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy for the classification and prediction of a donor's sex from the fingernails of 63 individuals. A significant advantage of ATR FT-IR is its ability to provide a specific spectral signature for different samples based on their biochemical composition. The infrared spectrum reveals unique vibrational features of a sample based on the different absorption frequencies of the individual functional groups. This technique is fast, simple, non-destructive, and requires only small quantities of measured material with minimal-to-no sample preparation. However, advanced multivariate techniques are needed to elucidate multiplex spectral information and the small differences caused by donor characteristics. We developed an analytical method using ATR FT-IR spectroscopy advanced with machine learning (ML) based on 63 donors' fingernails (37 males, 26 females). The PLS-DA and ANN models were established, and their generalization abilities were compared. Here, the PLS scores from the PLS-DA model were used for an artificial neural network (ANN) to create a classification model. The proposed ANN model showed a greater potential for predictions, and it was validated against an independent dataset, which resulted in 92% correctly classified spectra. The results of the study are quite impressive, with 100% accuracy achieved in correctly classifying donors as either male or female at the donor level. Here, we underscore the potential of ML algorithms to leverage the selectivity of ATR FT-IR spectroscopy and produce predictions along with information about the level of certainty in a scientifically defensible manner. This proof-of-concept study demonstrates the value of ATR FT-IR spectroscopy as a forensic tool to discriminate between male and female donors, which is significant for forensic applications.

Construction of an OCP-ATR-FTIR Spectroscopy Device to In Situ Monitor the Interfacial Reaction of Contaminants: Competitive Adsorption of Cr(VI) and Oxalate on Hematite

The comprehensive understanding of contaminant interfacial behavior strongly depends on the in situ characterization technique, which is still a great challenge. In this study, we constructed a device integrated with open-circuit potentialand attenuated total reflectance Fourier transform infrared (OCP-ATR-FTIR) spectroscopy to simultaneously monitor the electrochemical and infrared spectral information on the interfacial reaction for the process analysis, taking the competitive adsorption of hexavalent chromium (Cr(VI)) and oxalate on hematite nanocubes (HNC) as an example. The synchronous OCP and infrared results revealed that Cr(VI) interacted with HNC via bidentate binuclear inner-sphere coordination, accompanied by electron transfer from HNC to Cr(VI), while oxalate was adsorbed on HNC through bidentate mononuclear side-on inner-sphere coordination with electron transfer from HNC to oxalate, and also outer-sphere coordination with negative charge accumulation. When oxalate was added to HNC with preadsorbed Cr(VI), oxalate would occupy the inner-sphere adsorption sites and thus cause the detaching of preadsorbed Cr(VI) from HNC. This study provides a promising in situ characterization technique for real-time interfacial reaction monitoring and also sheds light on the competitive adsorption mechanism of oxalate and Cr(VI) on the mineral surface.

Recovery of phosphorus and other minerals from greenhouse wastewater generated during soilless tomato cultivation by means of alkalizing agents

The research was aimed at determining the possibility of recovering part of nutrients by precipitation from greenhouse wastewater (GW) from soilless tomato cultivation. Analyses included such elements as: P, S, N, Cl, Ca, Mg, K, Mo, Mn, Fe, Zn, Cu, and B. Three alkalizing agents were tested in a pH range of 6.5-12.0: Ca(OH)2, KOH, and NH4OH, which simultaneously enrich greenhouse wastewater in calcium, potassium, and nitrogen. It was determined what dose of the alkalizing agent should be used, how the composition of the treated GW will change, how much and what kind of sludge will be formed, what will be the stability and technical possibility of sediment separation, and whether the type of alkalizing agent affects the course of the process. Precipitation triggered by the alkalizing agents proved to be an effective method for the recovery of phosphorus, calcium, magnesium, manganese, and boron, while it turned out ineffective in the case of the other elements tested, including nitrogen and potassium. Phosphorus recovery depended mainly on GW pH and forms of phosphate ions corresponding to this pH, and not on the alkalizing agent type. The pH value adjustment to pH = 9 for KOH and NH4OH and to pH = 9.5 for Ca(OH)2 ensured <99 % phosphorus recovery, which corresponded to P concentration in GW below 1 mgP/L and to the applied Ca(OH)2, KOH, and NH4OH doses of 0.20 g/L, 0.28 g/L, and 0.08 g/L, respectively. The highest P contents in the sludge were determined at pH = 7 and reached 18.0 %, 16.8 %, and 16.3 % in the experimental series with Ca(OH)2, KOH, and NH4OH, respectively. The sludge volume index increase along with pH increase up to pH = 10.5 for KOH and to pH = 11 for Ca(OH)2 and NH4OH.

Advances in ATR-FTIR Spectroscopic Imaging for the Analysis of Tablet Dissolution and Drug Release

One of the major challenges in the development of effective pharmaceutical formulations for oral administration is the poor solubility of active pharmaceutical ingredients. For this reason, the dissolution process and drug release from solid oral dosage forms, such as tablets, is usually thoroughly studied in order to understand the dissolution behaviour under various conditions and optimize the formulation accordingly. Standard dissolution tests used in the pharmaceutical industry provide information on the amount of drug released over time; however, these do not allow for a detailed analysis of the underlying chemical and physical mechanisms of tablet dissolution. FTIR spectroscopic imaging, by contrast, does offer the ability to study these processes with high spatial and chemical specificity. As such, the method allows us to see the chemical and physical processes which occur inside the tablet as it dissolves. In this review, the power of ATR-FTIR spectroscopic imaging is demonstrated by presenting a number of successful applications of this chemical imaging technique to dissolution and drug release studies for a range of different pharmaceutical formulations and study conditions. Understanding these processes is essential for the development of effective oral dosage forms and optimization of pharmaceutical formulations.

Spectralprint techniques coupled with chemometric tools for vinegar classifications

Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (¹H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet-visible (UV-vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV-vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar.

Cu/CuO-Doped ZnO Nanocomposites via Solution Combustion Synthesis for Catalytic 4-Nitrophenol Reduction

The synthesis of optoelectrically enhanced nanomaterials should be continuously improved by employing time- and energy-saving techniques. The porous zinc oxide (ZnO) and copper-doped ZnO nanocomposites (NCs) were synthesized by the time- and energy-efficient solution combustion synthesis (SCS) approach. In this SCS approach, once the precursor-surfactant complex ignition point is reached, the reaction starts and ends within a short time without the need for any external energy. The TGA-DTA analysis confirmed that 500 °C was the point at which stable metal oxide was obtained. The doping and heterojunction strategy improved the optoelectric properties of the NCs more than the individual constituents, which then enhanced the materials' charge transfer and optical absorption capabilities. The porosity, nanoscale crystallite size (15-50 nm), and formation of Cu/CuO-ZnO NCs materials were confirmed from the XRD, SEM, and TEM/HRTEM analyses. The obtained d-spacing values of 0.275 and 0.234 nm confirm the formation of ZnO and CuO crystals, respectively. The decrease in photoluminescence intensity for the doped NCs corroborates a reduction in electron-hole recombination. On the Mott-Schottky analysis, the positive slope for ZnO confirms the n-type character, while the negative and positive slopes of the NCs confirm the p- and n-type characters, respectively. A diffusion-controlled type of charge transfer process on the electrode surface was confirmed from the cyclic voltammetric analysis. Thus, the overall analysis shows the applicability of the less expensive and more efficient SCS for several applications, such as catalysis and sensors. To confirm this, an organic catalytic reduction reaction of 4-nitrophenol to 4-aminophenol was tested. Within three and a half minutes, the catalytic reduction result showed the great potential of NCs over ZnO NPs. Thus, the energy- and time-saving SCS approach has a great future outlook as an industrial pollutant catalytic reduction application.

Synchrotron X-ray diffraction computed tomography to non-destructively study inorganic treatments for stone conservation

The characterization of consolidating products formed by conservation treatments within Cultural Heritage (CH) materials is a burning issue and an analytical challenge, as non-destructive approaches, phase analysis, and volume distribution analysis are simultaneously required. This paper proposes the use of synchrotron X-ray diffraction computed tomography (XRDCT) to non-destructively study diammonium hydrogen phosphate (DAP) consolidating treatments for stone conservation. The mineralogical composition and localization of crystalline phases formed in a complex mixture have been explored and spatially resolved. The coexistence of hydroxyapatite and octacalcium phosphate has been finally demonstrated. The image analysis highlights the 3D distribution of calcium phosphates, their arrangement in a binding network down to the voxel scale, and their consolidating action. Above all, this study demonstrates the feasibility and high potential of XRDCT to investigate the interactions of conservation treatments with CH stone materials, and opens new analytical perspectives for XRDCT in conservation science and materials science.

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DAP consolidation of a porous stone matrix is non-destructively studied by SR XRDCT

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The mineralogical composition/3D distribution of phases are simultaneously explored

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The 3D consolidating shell of newly formed CaPs phases is showed for the first time

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XRDCT provides new analytical tools and new applications in conservation science

Hydrating Capabilities of the Biopolymers Produced by the Marine Thermophilic Bacillus horneckiae SBP3 as Evaluated by ATR-FTIR Spectroscopy

The surfactin-like lipopeptide (BS-SBP3) and the exopolysaccharide (EPS-SBP3) produced by the polyextremophilic Bacillus horneckiae SBP3 (DSM 103063) have been recently described as valuable biopolymers useful in biotechnological applications. To investigate the hydrating capabilities of BS-SBP3 and EPS-SBP3, here we evaluated (i) their wetting properties, measuring the contact angle; (ii) their moisture uptake abilities using the gravimetric method; and (iii) their hydrating states (from 0 to 160% w/w of water content) using ATR-FTIR spectroscopy. BS-SBP3 reduced the water contact angle on a hydrophobic surface from 81.7° to 51.3°, whereas the contact angle in the presence of EPS-SBP3 was 72.9°, indicating that BS-SBP3 improved the wettability of the hydrophobic surface. In the moisture uptake tests, EPS-SBP3 absorbed more water than BS-SBP3, increasing its weight from 10 mg to 30.1 mg after 36 h of 100% humidity exposure. Spectral distance and cross-correlation analyses were used to evaluate the molecular changes of the two biopolymers during the hydration process. As the water concentration increased, BS-SBP3 spectra changed in intensity in the two contributions of the OH-stretching band named "closed" and "open" (3247 and 3336 cm^-1, respectively). Differently, the spectra of EPS-SBP3 exhibited a broader peak (3257 cm^-1), which shifted at higher water concentrations. As evaluated by the spectral distance and the wavelet cross-correlation analysis, the OH-stretching bands of the BS-SBP3 and EPS-SBP3 changed as a function of water content, with two different sigmoidal trends having the inflection points at 80% and 48%, respectively, indicating peculiar water-properties of each biopolymer. As wetting agents, these biopolymers might replace industrially manufactured additives in agriculture and the food and cosmetic industries.

Biodeterioration Assessment of a Unique Old Pharaonic Kingdom Wooden Statue Using Advanced Diagnostic Techniques

A recently discovered Egyptian wooden statue of King Djedefre was studied together with some surrounding burial soil samples for assessing the statue biodeterioration. The wooden morphological characterisation identified the hardwood Acacia nilotica as the wood type. X-ray diffraction, micro-FT-IR spectroscopy, and scanning electron microscopy with an X-ray spectrometer were used to evaluate the wood deterioration degree and the soil contribution in wood biodeterioration. Microbiological analyses (fluorescent in situ hybridisation and polymerase chain reaction) were also performed to detect the microbial attack on the statue. The prolonged interaction of the statue with the burial environment caused a strong wood decay due to biotic (fungi and bacteria) and abiotic factors (e.g., humidity fluctuations of the burial environment), which caused the severe cracking and collapsing of the wood structures. The analyses of the burial soil mineral composition were relevant for obtaining an overall picture of the statue deterioration. The results are useful for planning the right conservation procedures for this very particular and important wooden statue. Furthermore, analysis of the woody cell wall will help in the selection of appropriate consolidation and recovery treatments. Because the statue is a unique single piece of wood, and the morphological observations indicated that it is a bald woman in a sitting position, this statue will provide new and interesting knowledge of Egyptian culture.

Nanoscale chemical characterization of a post-consumer recycled polyolefin blend using tapping mode AFM-IR

Tapping mode AFM-IR reveals the presence of contaminants, PP inclusions within the PE phase, and EPR rubber at the interphase between PP and PE in a real-world polyolefin recyclate.