Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy

Demystifying the tropics: FTIR characterization of pantropical woods and their α-cellulose extracts for past atmospheric 14C reconstructions

To ensure unbiased tree-ring radiocarbon (14C) results, traditional pretreatments carefully isolate wood cellulose from extractives using organic solvents, among other chemicals. The addition of solvents is laborious, time-consuming, and can increase the risk of carbon contamination. Tropical woods show a high diversity in wood-anatomical and extractive composition, but the necessity of organic-solvent extraction for the 14C dating of these diverse woods remains untested. We applied a chemical treatment that excludes the solvent step on the wood of 8 tropical tree species sampled in South-America and Africa, with different wood-anatomical and extractive properties. We analyzed the success of the extractive removal along with several steps of the α-cellulose extraction procedure using Fourier Transform Infrared (FTIR) spectroscopy and further confirmed the quality of 14C measurements after extraction. The α-cellulose extracts obtained here showed FTIR-spectra free of signals from various extractives and the 14C results on these samples showed reliable results. The chemical method evaluated reduces the technical complexity required to prepare α-cellulose samples for 14C dating, and therefore can bolster global atmospheric 14C applications, especially in the tropics.

FT-IR and HPLC analysis of silver fir (Abies alba Mill.) bark compounds from different geographical provenances

Fourier Transform Infrared Spectroscopy (FT-IR) and High-Performance Liquid Chromatography (HPLC) could be applied to study the provenance of wood, specifically the differentiation of wood resources, as well as the identification of chemical compounds that are connected to the changes that occur in wood as a result of drying treatments. To test this hypothesis, the bark of silver fir (Abies alba Mill.) from trees belonging to seven different geographical provenances was studied, using samples dried at three different temperatures (60, 80, and 100 °C). FT-IR spectroscopy revealed different band assignments in the mid-infrared region depending on fir provenances, whereas the vibrational bands of the biomass functional groups tended to shift to lower wavenumbers. Significant differences were identified between the chemical compounds in the bark depending on the provenances. The largest proportion of the total phenolics was represented by the epicatechin gallate, epicatechin, catechin, and procyanidin dimer B1. Exploratory data analysis was performed using principal component analysis (PCA), hierarchical clustering, and Pearson correlations. This allowed a comparative evaluation of the samples and interpret the findings according to the geographical provenances, respectively ecological conditions in the areas of origin, but also the influence of the drying temperatures of the samples on chemical compounds. The precipitation in the areas of origin decreased total phenolics in silver fir bark samples, and total phenolics differed not only due to the geographic provenance, but also due to drying temperature.

Classification of Amazonian fast-growing tree species and wood chemical determination by FTIR and multivariate analysis (PLS-DA, PLS)

Fast-growing trees like Capirona, Bolaina, and Pashaco have the potential to reduce forest degradation because of their ecological features, the economic importance in the Amazon Forest, and an industry based on wood-polymer composites. Therefore, a practical method to discriminate specie (to avoid illegal logging) and determine chemical composition (tree breeding programs) is needed. This study aimed to validate a model for the classification of wood species and a universal model for the rapid determination of cellulose, hemicellulose, and lignin using FTIR spectroscopy coupled with chemometrics. Our results showed that PLS-DA models for the classification of wood species (0.84 ≤ R² ≤ 0.91, 0.12 ≤ RMSEP ≤ 0.20, accuracy, specificity, and sensibility between 95.2 and 100%) were satisfied with the full spectra and the differentiation among these species based on IR peaks related to cellulose, lignin, and hemicellulose. Besides, the full spectra helped build a three-species universal PLS model to quantify the principal wood chemical components. Lignin (RPD = 2.27, [Formula: see text] = 0.84) and hemicellulose (RPD = 2.46, [Formula: see text] = 0.83) models showed a good prediction, while cellulose model (RPD = 3.43, [Formula: see text] = 0.91) classified as efficient. This study showed that FTIR-ATR, together with chemometrics, is a reliable method to discriminate wood species and to determine the wood chemical composition in juvenile trees of Pashaco, Capirona, and Bolaina.

New formula of the green synthesised Au@Ag core@shell nanoparticles using propolis extract presented high antibacterial and anticancer activity

Antimicrobial alternatives such as nanoparticles are critically required to tackle bacterial infections, especially with the emerging threat of antibiotic resistance. Therefore, this study aimed to biosynthesize Au-Ag nanoparticles using propolis as a natural reducing agent and investigate their antibacterial activity against antibiotic-resistant Staphylococcus sciuri (S. sciuri), Pseudomonas aeruginosa (P. aeruginosa), and Salmonella enterica Typhimurium (S. enterica), besides demonstrating their anticancer activity in cancer cell lines. The biosynthesized Au@AgNPs were characterized using UV-Vis spectrophotometer, Transmission Electron Microscopy (TEM), Zeta potential, Dynamic Light Scattering (DLS), Fourier Transformation Infrared (FTIR), and Scanning Electron Microscopy (SEM). Moreover, the detection of antibacterial activity was assessed through disc diffusion, the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC), time-killing curve, and detection of cell membrane integrity via SEM. As a result, the UV-Vis spectrum revealed the formation of Au@AgNPs in a single peak between 533 and 555 nm. Furthermore, FTIR analysis confirmed nanoparticles' green synthesis due to the presence of carbon functional groups. The formulated Au@AgNPs showed antibacterial activity against both Gram-positive and Gram-negative bacteria. The MIC and the MBC of P. aeruginosa and S. sciuri were 31.25 µg/mL. However, nanoparticles were more effective on S. enterica with MIC of 7.5 µg/mL and MBC of 15.6 µg/mL. Furthermore, the time-killing curve of the three model bacteria with the treatment was effective at 50 µg/mL. Besides, SEM of the tested bacteria indicated unintegrated bacterial cell membranes and damage caused by Au@AgNPs. Regarding the anticancer activity, the results indicated that the biosynthesized Au@AgNPs have a cytotoxic effect on HEPG2 cell lines. In conclusion, this research revealed that the green synthesized Au@AgNPs could be effective antibacterial agents against S. sciuri, P. aeruginosa, and S. enterica and anticancer agents against HEPG2.

Non-Destructive Evaluation of the Cutting Surface of Hardwood Finger Joints

In this study, the surface parameters wettability, roughness, and adhesive penetration, which are important for wood bonding, were investigated and evaluated utilizing non-destructive methods after different mechanical processing. For this purpose, beech and birch finger joints were prepared with different cutting combinations (three cutters with different sharpness levels and two feed rates) in an industrial process. Effects and interactions on the surface parameters resulting from the different cutting combinations were evaluated using three Full Factorial Designs. The various cutting parameters had a predominantly significant influence on the surface parameters. The effects and identified interactions highlight the complexity of the cutting surface and the importance of wood bonding. In this respect, a new finding is that with sharper cutters, higher contact angles of the adhesives occur. The methods (contact angle measurement, laser scanning microscopy, and brightfield microscopy) used were well suited to make effects visible and quantifiable, which can be of interest for the quality control of the wood processing industry. The results can help to better understand and evaluate the design of wood surfaces via machining and the bonding of hardwoods. Possibly the results can contribute to further standardizing the production of load-bearing hardwood finger joints and making them more efficient.

Determination of hemicellulose, cellulose, holocellulose and lignin content using FTIR in Calycophyllum spruceanum (Benth.) K. Schum. and Guazuma crinita Lam

Capirona (Calycophyllum spruceanum (Benth.) K. Schum.) and Bolaina (Guazuma crinita Lam.) are fast-growing Amazonian trees with increasing demand in timber industry. Therefore, it is necessary to determine the content of cellulose, hemicellulose, holocellulose and lignin in juvenile trees to accelerate forest breeding programs. The aim of this study was to identify chemical differences between apical and basal stem of Capirona and Bolaina to develop models for estimating the chemical composition using Fourier transform infrared (FTIR) spectra. FTIR-ATR spectra were obtained from 150 samples for each species that were 1.8 year-old. The results showed significant differences between the apical and basal stem for each species in terms of cellulose, hemicellulose, holocellulose and lignin content. This variability was useful to build partial least squares (PLS) models from the FTIR spectra and they were evaluated by root mean squared error of predictions (RMSEP) and ratio of performance to deviation (RPD). Lignin content was efficiently predicted in Capirona (RMSEP = 0.48, RPD > 2) and Bolaina (RMSEP = 0.81, RPD > 2). In Capirona, the predictive power of cellulose, hemicellulose and holocellulose models (0.68 < RMSEP < 2.06, 1.60 < RPD < 1.96) were high enough to predict wood chemical composition. In Bolaina, model for cellulose attained an excellent predictive power (RMSEP = 1.82, RPD = 6.14) while models for hemicellulose and holocellulose attained a good predictive power (RPD > 2.0). This study showed that FTIR-ATR together with PLS is a reliable method to determine the wood chemical composition in juvenile trees of Capirona and Bolaina.

Realizing Improved Sodium-Ion Storage by Introducing Carbonyl Groups and Closed Micropores into a Biomass-Derived Hard Carbon Anode

Micropores and defects, like oxygen-containing groups, as active sites for sodium-ion storage in hard carbon have attracted considerable attention; nevertheless, most oxygen doping or oxidizing processes inevitably introduce undesired oxygen groups into a carbon framework, leading to deteriorated initial Coulombic efficiency (ICE). Here, precise carbonyl groups and closed micropores are together introduced into biomass-derived hard carbon to enhance the Na-ion storage performance. The hard carbon delivers a large reversible capacity of 354.6 mA h g^-1 at 30 mA g^-1, a high ICE (88.7%), as well as ultra-long cycling stability (277 mA h g^-1 at 0.3 A g^-1 over 1000 cycles; 243 mA h g^-1 at 1 A g^-1 over 5000 cycles). The rate capability and cycling stability of hard carbon in carbonate- and diglyme-based electrolytes are contrasted to demonstrate the superiority of diglyme. Cyclic voltammetry at varied scans and galvanostatic intermittent titration techniques are carried out to clarify the disparity between the two different electrolyte systems. Furthermore, the as-prepared hard carbon is utilized as the anode for sodium-ion full cells exhibiting an energy density of 166.2 W h kg^-1 at 0.2 C and a long-cycle life (47.9% retention over 200 cycles at 1 C).

Characterization of nano-to-micron sized respirable coal dust: Particle surface alteration and the health impact

Chemical and physical properties of coal dust particles significantly influence the inhalation of respirable coal dust by miners, causing several lung diseases such as coal workers' pneumoconiosis (CWP) and silicosis. Multiple experimental techniques, including proximate/ultimate analyses, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), laser diffraction, and low-pressure CO₂ and N₂ adsorption, were used to investigate the chemical and physical properties of micron-/nano-coal particles comprehensively. Compared to the micron-scale coal dust, the nano-coal dust (prepared by cryogenic ballmill) shows the increase of carbon content and aromaticity and a decrease of oxygen content along with the reduction of oxygen-containing functional groups. Pore volume and surface area estimated by low-pressure CO₂ and N₂ adsorption have more than five-time increase for the nano-coal dust. The reduction of oxygen functional groups suggests the dropped wetting behavior of coal nanoparticles. The significantly increased pore volume and surface area in coal nanoparticles could be caused by the enhanced pore interconnectivity on the particle surface and the alteration of coal macromolecules. Weaker wettability and the highly enhanced surface area suggest potentially more significant toxicity of nano-coal dust inhaled by coal miners.

The Biofungicide Activity of Some Plant Essential Oils for the Cleaner Production of Model Linen Fibers Similar to Those Used in Ancient Egyptian Mummification

In this work, the essential oils (EOs) from Eriocephalus africanus leaf, Vitex agnus-castus leaf and fruit, Cymbopogon citratus leaf, and Rosmarinus officinalis leaf were used as antifungal agents against isolated Aspergillus flavus, Cladosporium cladosporioides, and Penicillium chrysogenum from an ancient Egyptian child’s mummy. The isolated fungi were used to colonize the samples of linen fibers. The best oil was used as a novel natural product for the cleaner production of model linen fibers similar to those used in ancient Egyptian mummification. Standard and original linen fibers were compared with the infected Linen samples using Fourier transform infrared (FTIR) and X-ray diffraction (XRD) analyses. The FTIR revealed the changes in the molecular structure of the cellulose, hemicellulose, and lignin of the infected linen fibers. The cellulose crystallinity indices decreased to 64.61%, 52.69%, and 54.63% in the linen inoculated with A. flavus, C. cladosporioides, and P. chrysogenum compared to the control sample (72.08%), thereby affecting the chemical properties of the cellulose. The mycelia inhibition percentages of the three fungi reached 100% after the leaf EO from V. agnus-castus was applied, followed by C. citratus. The V. agnus-castus leaf EO applied at contraptions of 250, 500, 50, 1000, and 2000 µL/mL showed 100% inhibition for A. flavus and P. chrysogenum and reached 100% against C. cladosporioides at concentrations of 500, 750, 1000, and 2000 µL/mL. C. citratus leaf essential oil applied at concentrations of 500, 750, 1000, and 2000 µL/mL showed 100% inhibition to the growth of A. flavus and C. cladosporioides and reached 100% inhibition against the growth of P. chrysogenum at concentrations of 750, 1000 and 2000 µL/mL. This inhibition could be related to the main compounds of caryophyllene (23.13%), eucalyptol (20.59%), sabinene (β-thujene) (12.2%), γ-elemene (9%), and β-farnesene (6.14%) identified in V. agnus-castus leaf EO or due to the main compounds of β-citral (43.63%) and geranial (41.51%), as identified in the leaf EO of C. citratus by GC/MS. The morphological changes in the hyphae of the fungi were observed via SEM examination, where V. agnus-castus leaf EO, the best active oil, showed potent inhibition to fungi grown on the model linen fiber. In this way, the morphology and the structure of the hyphae were effectively changed. Our findings prove that the designed model linen fiber treated with V. agnus-castus leaf EO is able to preserve wrapping fibres and represents a novel natural alternative for effective fungicidal treatment.

Assessing utility of handheld laser induced breakdown spectroscopy as a means of Dalbergia speciation

Many species of Dalbergia are prized hardwoods, generally referred to as 'Rosewood,' and used in high-end products due to their distinctive hue and scent. Despite more than 58 species of Dalbergia being listed as endangered in Appendix 1 of The Convention on International Trade in Endangered Species of Fauna and Flora (CITES), the illegal logging and trade of this timber is ongoing. In this work, a handheld laser induced breakdown spectrometer (LIBS) was used to analyze seven Dalbergia species and two other exotic hardwood species to evaluate the ability of handheld LIBS for rapid classification of Dalbergia in the field. The KNN model of the classification presented 80% to 90% sensitivity for discriminating between Dalbergia species in the training set. PLS-DA models were based on a binary decision tree structure. Cumulatively, the PLS-DA decision tree model showed greater than 97% sensitivity and 99% selectivity for prediction of Dalbergia species included in the training set. The data presented in the following study are promising for the use of handheld LIBS devices and both KNN and PLS-DA models for applications in customs screenings at the port of entry of hard woods, among others.

Differentiation between pine woods according to species and growing location using FTIR-ATR

Attenuated total reflectance-Fourier transform infrared (FTIR-ATR) spectroscopy was applied to 120 samples of heartwood rings from eight individual pine trees from different locations in Spain. Pinus sylvestris cores were collected at the Artikutza natural park (Ps-ART). Pinus nigra cores were collected in Sierra de Cazorla (Pn-LIN) and in La Sagra Mountain (Pn-LSA). Three discriminant analysis tests were performed using all bands (DF_T), lignin bands only (DF_L) and polysaccharides bands only (DF_P), to explore the ability of FTIR-ATR to separate between species and growing location. The DF_L model enabled a good separation between pine species, whereas the DF_P model enabled differentiation for both species and growing location. The DF_T model enabled virtually perfect separation, based on two functions involving twelve FTIR bands. Discrimination between species was related to bands at 860 and 1655 cm^-1, which were more intense in P. sylvestris samples, and bands at 1425 and 1635 cm^-1, more intense in P. nigra samples. These vibrations were related to differences in lignin structure and polysaccharide linear chains. Discrimination between growing locations was mainly related to polysaccharide absorptions: at 900, 1085 and 1335 cm^-1 more representative of Pn-LIN samples, and at 1105 and 1315 cm^-1 mostly associated to Pn-LSA samples. These absorptions are related to β-glycosidic linkages (900 cm^-1), cellulose and hemicellulose (C-O bonds, 1085 and 1105 cm^-1) and content in amorphous/crystalline cellulose (1315 and 1335 cm^-1). These results show that FTIR-ATR in combination with multivariate statistics can be a useful tool for species identification and provenancing for pine wood samples of unknown origin.

Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression

Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R² > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material.