The Evolution of the Intrinsic Flexural Strength of Jute Strands after a Progressive Delignification Process and Their Contribution to the Flexural Strength of PLA-Based Biocomposites

Biocomposites from poly-(lactic acid) (PLA) and jute strands were prepared, and their flexural strength was analyzed. Jute strands were submitted to a progressive delignification process and the resulting morphology, composition, and crystallinity index were evaluated. Then, PLA biocomposites comprising 30 wt% of jute strands were produced and characterized under flexural conditions. The delignification processes decreased the lignin content and progressively increased the cellulose content. All this resulted in an enhancement of the composite flexural strength. A modified rule of mixtures, and the relation between tensile and flexural properties were used to determine the intrinsic flexural strength (of the jute strands) and their correlation with their physic-chemical characteristics. Equations correlating the intrinsic flexural strength with the crystallinity index, the cellulose content, and the microfibril angle were proposed. These equations show the impact of these properties over the intrinsic properties of the fibers and can help researchers to select appropriate fibers to obtain accurate properties for the composites. Jute strands show their value as reinforcement by increasing the flexural strength of the matrix by 70% and being less expensive and more environmentally friendly than mineral reinforcements. Together with the profitability and the environmental advantages, the mechanical results suggest that these PLA biocomposites are suitable for specific products of different market sectors.

Portable near-infrared and Raman spectroscopic devices as complementary tools for instantaneous quality control of turmeric powder

INTRODUCTION

Process analytical technology (PAT) guidance is implemented in the quality assurance of phytocompounds to achieve the Industry 4.0 concept. Near-infrared (NIR) and Raman spectroscopies are feasible for rapid, reliable quantitative analysis through transparent packaging without removing the samples from their original containers. These instruments can serve PAT guidance.

OBJECTIVE

This study aimed to develop online portable NIR and Raman spectroscopic methods for quantifying total curcuminoids in turmeric samples through a plastic bag. The method mimicked an in-line measurement mode in PAT compared with placing samples into a glass vessel (at-line mode).

MATERIALS AND METHODS

Sixty-three curcuminoid standard-spiked samples were prepared. Then, 15 samples were randomly selected as fixed validation samples, and 40 of the 48 remaining samples were chosen as calibration set. The results obtained from the partial least square regression (PLSR) models constructed by using the spectra acquired from NIR and Raman were compared with the reference values from high-performance liquid chromatography (HPLC).

RESULTS

The optimum PLSR model of at-line Raman was achieved with three latent variables and a root mean square error of prediction (RMSEP) of 0.46. Meanwhile, the PLSR model of at-line NIR with one latent variable offered an RMSEP of 0.43. For the in-line mode, PLSR models created from Raman and NIR spectra had one latent variable with RMSEP of 0.49 and 0.42, respectively. The R² values for prediction were 0.88-0.92.

CONCLUSION

The models established from the spectra from portable NIR and Raman spectroscopic devices with the appropriate spectral pretreatments allowed the determination of total curcuminoid contents through plastic bag.

Research on the Strengthening Advantages on Using Cellulose Nanofibers as Polyvinyl Alcohol Reinforcement

The present work aims to combine the unique properties of cellulose nanofibers (CNF) with polyvinyl alcohol (PVA) to obtain high-performance nanocomposites. CNF were obtained by means of TEMPO-mediated ((2,2,6,6-Tetramethylpiperidin-1-yl)oxyl) oxidation, incorporated into the PVA matrix by means of compounding in a single-screw co-rotating internal mixer and then processed by means of injection molding. It was found that CNF were able to improve the tensile strength of PVA in 85% when 4.50 wt % of CNF were added. In addition, the incorporation of a 2.25 wt % of CNF enhanced the tensile strength to the same level that when 40 wt % of microsized fibers (stone groundwood pulp, SGW) were incorporated, which indicated that CNF possessed significantly higher intrinsic mechanical properties than microsized fibers. SGW was selected as reference for microsized fibers due to their extended use in wood plastic composites. Finally, a micromechanical analysis was performed, obtaining coupling factors near to 0.2, indicating good interphase between CNF and PVA. Overall, it was found that the use of CNF is clearly advantageous to the use of common cellulosic fibers if superior mechanical properties are desired, but there are still some limitations that are related to processing that restrict the reinforcement content at low contents.

Calibration sets selection strategy for the construction of robust PLS models for prediction of biodiesel/diesel blends physico-chemical properties using NIR spectroscopy

Even when the feasibility of using near infrared (NIR) spectroscopy combined with partial least squares (PLS) regression for prediction of physico-chemical properties of biodiesel/diesel blends has been widely demonstrated, inclusion in the calibration sets of the whole variability of diesel samples from diverse production origins still remains as an important challenge when constructing the models. This work presents a useful strategy for the systematic selection of calibration sets of samples of biodiesel/diesel blends from diverse origins, based on a binary code, principal components analysis (PCA) and the Kennard-Stones algorithm. Results show that using this methodology the models can keep their robustness over time. PLS calculations have been done using a specialized chemometric software as well as the software of the NIR instrument installed in plant, and both produced RMSEP under reproducibility values of the reference methods. The models have been proved for on-line simultaneous determination of seven properties: density, cetane index, fatty acid methyl esters (FAME) content, cloud point, boiling point at 95% of recovery, flash point and sulphur.

Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I+II+III supernatant in human albumin separation

Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I+II+III (FI+II+III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (R_p²), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501g/L, 0.465g/L and 5.57 for TP, and 0.969, 0.530g/L, 0.341g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI+II+III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS.

Ion mobility spectrometry evaluation of cocaine occupational exposure in forensic laboratories

An approach, based on ion mobility spectrometry (IMS) has been developed for the control of cocaine in air of the breathing zone of operators, in laboratory surfaces and in nasal mucus of employees to evaluate cocaine exposure in a forensic laboratory. The analytical methodology has been validated in terms of accuracy, precision and limits of detection and results obtained were statistically comparable with those obtained by liquid chromatography. Cocaine concentration in laboratory air increases from 100 ± 35 ng m(-3) of a normal day to 10,000 ng m(-3) during the manipulation of cocaine seizures. The occupational exposure limit (OEL) for cocaine has not been established which difficult the evaluation of the health effects of continuous exposition to very small doses of cocaine. Cocaine was also found in almost all the analyzed sample surfaces and also was found in nasal mucus of the police officers that were present during the manipulation of cocaine seizures without using a face mask. In summary, cocaine concentrations could present a health hazard to the employees and therefore warrants remediation and some modifications of the manipulation operations have been proposed.

Noninvasive double confirmation of cocaine abuse

A double confirmation procedure, based on the combined application of Ion Mobility Spectrometry (IMS) and Infrared Spectroscopy (IR), has been developed for the noninvasive unambiguous identification of cocaine consume. The use of nasal mucus as a biological specimen for cocaine abuse confirmation has been proposed as an alternative to the use of blood and urine due to its noninvasive character and the presence of the parent compound instead of its metabolites. Sampling conditions, interferences caused by cutting agents and other substances, and limits of identification (LOI) and confirmation (LOC) have been deeply evaluated. The procedure combines the high sensitivity of the IMS to identify positive samples with the high selectivity of the IR procedure to confirm positive results. Thus, the proposed two tier method has been applied to the detection and identification of cocaine in the nasal mucus of different individuals, consumers, and nonconsumers, providing results comparable with those obtained by a reference procedure.

Determination of drug, excipients and coating distribution in pharmaceutical tablets using NIR-CI

The growing interest of the pharmaceutical industry in Near Infrared-Chemical Imaging (NIR-CI) is a result of its high usefulness for quality control analyses of drugs throughout their production process (particularly of its non-destructive nature and expeditious data acquisition). In this work, the concentration and distribution of the major and minor components of pharmaceutical tablets are determined and the spatial distribution from the internal and external sides has been obtained. In addition, the same NIR-CI allowed the coating thickness and its surface distribution to be quantified. Images were processed to extract the target data and calibration models constructed using the Partial Least Squares (PLS) algorithms. The concentrations of Active Pharmaceutical Ingredient (API) and excipients obtained for uncoated cores were essentially identical to the nominal values of the pharmaceutical formulation. But the predictive ability of the calibration models applied to the coated tablets decreased as the coating thickness increased.

Determination of trace impurities in cosmetic intermediates by ion mobility spectrometry

The cosmetic and pharmaceutical industries are continuously demanding fast, efficient, cost-effective analytical methods to monitor production processes and assure end-product quality. The presence of residual reagents or impurities formed during a synthetic process can have an adverse impact on product quality, assurance of which requires using increasingly sensitive analytical methods to facilitate the detection and/or determination of toxic compounds with potentially hazardous effects on consumer's health. In this work, we assessed the potential of ion mobility spectrometry (IMS) for the detection and quantitation of dimethylaminopropylamine (DMAPA) residues in stearamidopropyldimethylamine (SAPDA) production samples. The influence of instrumental variables including solvent, solution drying time, injected volume and volatilization temperature was examined. The ensuing analytical method takes less than 1 min per analysis and uses only a few microlitres of sample. The calibration curve was linear over the DMAPA concentration range 0.030-0.500 μg mL(-1). The proposed method was validated for use in control processes. The complex plasmagram for amidoamines allows the origin of cosmetic oils to be easily, expeditiously identified. Based on the results, IMS holds great promise for the qualitative and quantitative determination of the studied amide and various others in cosmetic products.

API determination by NIR spectroscopy across pharmaceutical production process

The purpose of this research was to demonstrate the ability of reflectance near-infrared (NIR) spectroscopy for quantitative analysis of an active ingredient in different production steps of a solid formulation. The drug is quantified at two different steps of a pharmaceutical process: after granulation and after tablet coating. Calibration samples were prepared by mixing pure drug, excipients, and batch samples (75-120 mg/g active ingredient) using a simple methodology that can be easily carried out in a laboratory. Partial least squares calibration models were calculated in second-derivative mode using the wavelength range 1,134-1,798 nm. The error of prediction for granulated samples was 1.01% and 1.63% for tablets. The results prove that NIR spectroscopy is a good alternative to other, more time-consuming means of analysis for pharmaceutical process monitoring.