•Cellulose nanocrystals (CNs) with different polymorphs (I and II) were obtained.•CNs with different sizes and shapes (cilindrical and circular) were obtained.•CNs composed of cellulose II had lower ...DP values than CNs composed of cellulose I.•CNs extracted using H2SO4 were less thermally stable than those extracted using HCl.•The type of polymorph and acid employed affected the thermal degradation kinetics.
Cellulose nanocrystals (CNs) were extracted from different sources by acid hydrolysis using H2SO4 and HCl. The thermal decomposition of resulting CNs was studied by thermogravimetric analysis (TGA). The kinetic parameters were determined using the Flynn–Wall–Ozawa (FWO) and Kissinger methods. CNs were also characterized by X-ray diffraction (XRD), Atomic Force Microscopy (AFM), elemental analysis (EA), Zeta Potential (ZP) and degree of polymerization (DP). The results of the XRD analysis showed different profiles, making it possible to differentiate cellulose I from cellulose II. The results obtained by the FWO method showed that cellulose II CNs had an increased activation energy (Ea) with conversion (α), while in CNs of cellulose I the Ea remained constant or decreased slightly. This difference between Ea values for the thermal decomposition of CNs was mainly attributed to different crystalline arrangements of cellulose I and cellulose II, and to the type of acid employed.
•Biodiesel from sunflower oil was successfully purified with natural adsorbents.•Starch from different sources and cellulose fibers were used as adsorbents.•Dry washing has removed more impurities ...than the wet washing.•Was reduced the acidity index, alkalinity, free glycerine and turbidity of biodiesel.
This work describes a study of the purification of biodiesel produced from sunflower oil by dry cold washing using natural adsorbents as cellulose and starch from different sources (corn, potato, cassava and rice), and the comparison with dry cold washing with a commercial adsorbent Select 450® and with the conventional wet washing with hot water. The purification by dry washing was carried out by varying the amount of adsorbents in 1%, 2%, 5% and 10% (w/v) at 25°C for 10min. For the purification by wet washing, the biodiesel was successively washed with acidified water and pure water at 85°C until neutralisation. The efficiency of the processes for the removal of biodiesel impurities was evaluated by determining the acidity index, combined alkalinity, free glycerine and turbidity of the biodiesel. All adsorbents studied presented good efficiency in the removal of the impurities and showed similar behaviour independent of the kind or amount of adsorbent employed. The use of natural adsorbents for the purification of biodiesel have been shown to be a promissory process to be applied as an industrial stage of the purification of biodiesel during their production.
The work presented here aims to study and compare the performance of a polyvinylidene fluoride (PVDF) electrospun membrane, unmodified cellulose nanofiber (CNF) based PVDF membrane, and Meldrum’s ...acid (2,2-dimethyl-1,3-dioxane-4,6-dione) modified CNF-based PVDF membranes against the Fe2O3 nanoparticle filtration and crystal violet (CV) dye adsorption. Herein, we introduced a facile method to produce a unique green adsorbent material from cellulose nanofibers (CNFs) via a nonsolvent assisted procedure using Meldrum’s acid as an esterification agent to enhance the adsorption toward positively charged crystal violet dyes. Most of the surface modifications of cellulose nanofibers have been done using toxic organic solvents like pyridine, dimethyl acetate, (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO), etc. So far, this is the first report on the surface modification of cellulose nanofibers via a nonsolvent assisted procedure. Both CNF-based PVDF membranes were prepared by successive coating of modified and unmodified CNFs on to the surface of a PVDF electrospun membrane. All the demonstrated membranes showed high filtration capacity against the Fe2O3 nanoparticles. With the 10 mg/L of crystal violet (CV) aqueous solution, CV adsorption of PVDF electrospun membrane, and unmodified CNF-based PVDF membrane was around 1.368 and 2.948 mg/g of the membrane respectively, whereas it was 3.984 mg/g of the membrane by Meldrum’s acid CNF-based PVDF membrane. The demonstrated Meldrum’s acid modified CNF-based PVDF membrane was proven to be the efficient media that can concurrently eliminate the Fe2O3 nanoparticles and CV dyes from the water. The investigation into the surface chemistries of cellulose nanofibers beyond the adoption of toxic solvents can enhance the economic usefulness of the process and also yield a new ecofriendly adsorbent material that is agreeable to adsorbing various toxic pollutants.
An array of highly conductive, lightweight and flexible cellulose nanopapers as effective attenuators of electromagnetic radiations within 8.2–12.4 GHz (X band) were formulated via in situ ...polymerization of pyrrole monomers on to cellulose nanofibers (CNFs). It is quite obvious that the free hydroxyl groups on the surface of CNFs facilitate the formation of intense intermolecular hydrogen bonding with PPy which is envisaged for its excellent electromagnetic shielding performance with an average shielding effectiveness of ca. –22 dB (>99% attenuation) at 8.2 GHz for a paper having 1 mm thickness. The fabricated papers displayed a predominant absorption mechanism (ca. 89%) rather than reflection (ca. 11%) for efficiently attenuating electromagnetic radiations, which has a considerable importance in the modern telecommunication sector. Thus, the designed PPy/CNF papers would replace the conventional metal‐based shields and pave way for the development of green microwave attenuators functioning via a strong absorption mechanism. The PPy/CNF nanopapers exhibited a DC conductivity of 0.21 S/cm, a prime requisite for the development of highly efficient electromagnetic shields. Undoubtedly, such nanopapers can be employed in wide range of applications such as electrodes for supercapacitors and other freestanding flexible paper‐based devices.
A series of flexible, lightweight, and highly conductive cellulose nanopapers were fabricated through in situ polymerization of aniline monomer on to cellulose nanofibers with a rationale for ...attenuating electromagnetic radiations within 8.2–12.4 GHz (X band). The demonstrated paper exhibits good conductivity due to the formation of a continuous coating of polyaniline (PANI) over the cellulose nanofibers (CNF) during in situ polymerization, which is evident from scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction analysis. The free hydroxyl groups on the surface of nanocellulose fibers promptly form intermolecular hydrogen bonding with PANI, which plays a vital role in shielding electromagnetic radiations and makes the cellulose nanopapers even more robust. These composite nanopapers exhibited an average shielding effectiveness of ca. −23 dB (>99% attenuation) at 8.2 GHz with 1 mm paper thickness. The fabricated papers exhibited an effective attenuation of electromagnetic waves by a predominant absorption mechanism (ca. 87%) rather than reflection (ca. 13%), which is highly desirable for the present-day telecommunication sector. Unlike metal-based shields, these demonstrated PANI/CNF papers have given a new platform for designing green microwave attenuators via an absorption mechanism. The prime novelty of the present study is that these robust PANI/CNF nanopapers have the ability to attenuate incoming microwave radiations to an extent that is 360% higher than the shielding effectiveness value reported in the previous literature. This makes them suitable for use in commercial electronic gadgets. This demonstrated work also opens up new avenues for using cellulose nanofibers as an effective substrate for fabricating conductive flexible papers using polyaniline. The direct current conductivity value of PANI/CNF nanopaper was 0.314 S/cm, which is one of the key requisites for the fabrication of efficient electromagnetic shields. Nevertheless, such nanopapers also open up an arena of applications such as electrodes for supercapacitors, separators for Li–S, Li–polymer batteries, and other freestanding flexible paper-based devices.
The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality ...and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force Warner-Bratzler shear force (WBSF), marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R2C), and prediction (R2P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R2P = 0.40) and b* color (RMSEP = 1.21, R2P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R2P = 0.16) and a* (RMSEP = 1.42, R2P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.
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•NIRS can be used in soybean breeding programs to discriminate superior genotypes.•NIRS can be used in breeding programs to predict the oil content of intact grains.•GA-LDA resulted ...in a high discrimination accuracy (88.89% - prediction set).•PLSR oil prediction models presented low RMSEP (0.96%) and adequate R2 (0.66).
In soybean (Glycine max L.) breeding programs, segregation is normally observed, and it is not possible to have replicates of individuals because each genotype is a unique copy. Therefore, near-infrared spectroscopy (NIRS) was used as a non-destructive tool to classify soybeans by genotypes and to predict oil content. A total of 260 soybean genotypes were divided into five classes, which were composed of 32, 52, 82, 46, and 49 samples of the BV, BVV, EB, JAB, and L class, respectively. NIR spectra were obtained using oven-dried samples (80 g) in a reflectance mode. A successive projection algorithm and genetic algorithm with linear discriminant analysis discriminated genotypes of the low (L class) from the high (EB class) for oil content (88.89% accuracy). The partial least square regression models for oil content were considered good (root mean square error of prediction of 0.96%). Therefore, NIRS can be used as a non-destructive tool in soybean breeding programs, but further investigation is necessary to improve the robustness of the models. It is important to note that to use the models, it is necessary to collect NIR spectra from dry soybean samples.
One of the most important quality traits in popcorn breeding programs is the popping expansion (PE) capacity of the kernel, which is the ratio of the volume of the popcorn to the weight of the ...kernel. In this study, we evaluated whether near infrared spectroscopy (NIR spectroscopy) could be used as a tool in popcorn breeding programs to routinely predict and/or discriminate popcorn genotypes on the basis of their PE. Three generations (F1, F2, and F2:3) were developed in three planting seasons by manual cross-pollination and self-pollination. A total of 376 ears from the F2:3 generation were selected, shelled, and subjected to phenotypic analysis. Genetic variability was observed in the F2 and F2:3 generations, and their average PE value was 31.5 ± 6.7 mL g−1. PE prediction models using partial least square (PLS) regression were developed, and the root mean square error of calibration (RMSEC) was 6.08 mL g−1, while the coefficient of determination (RC2) was 0.26. The model developed by principal component analysis with quadratic discriminant analysis (PCA-QDA) was the best for discriminating the kernels with low PE (≤30 mL g−1) from those with high PE (>30 mL g−1) with an accuracy of 78%, sensitivity of 81.2%, and specificity of 72.2%. Although NIR spectroscopy appears to be a promising non-destructive method for assessing the PE of intact popcorn kernels for narrow breeding populations, greater variability and larger sample sizes would help improve the robustness of the predictive and classificatory models.
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•PLS regression using raw spectra could be used to predict PE in intact popcorn kernels.•PCA-QDA is better model to classify PE.•NIR spectroscopy is a new option to select popcorn genotype in a breeding program.
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•Nanosorbents with high magnetization were synthesized for Pb (II) removal.•Nanosorbents were capped with thin layers of modified biopolymers.•Thin layers of biopolymers were ...sufficient to improve Pb (II) removal.•Cheap raw materials were utilized for nanoparticle functionalization.•Nanosorbents can be recovered magnetically for reuse in Pb (II) removal.
In this study we report findings on the elaboration of magnetic nanosorbents based on manganese ferrite nanoparticles (MNPs) capped with carboxymethylated biopolymers (starch or cellulose) for water remediation purposes. The functionalization was optimized through the analysis of pH-dependent speciation profiles of MNPs/biopolymers, and samples were characterized using X ray powder diffraction, atomic force microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, nitrogen adsorption–desorption surface analysis and magnetization measurements. Nanosorbents have all been shown to remove Pb (II) efficiently from aqueous solution (∼100%, after 30 min of contact) in spite of the presence of very tiny layers of biopolymers (the maximal amount of organic layer adsorbed on the MNP surface was only about 4.0% in mass and biopolymer coating thickness was estimated < 1 nm). This low biopolymer content was sufficient to increase the affinity of nanosorbents for Pb (II), preserving high magnetization of material (∼65 emu/g). Equilibrium adsorption isotherms for Pb (II) adsorption on biopolymer-modified MNPs indicated that more heterogeneous surfaces were formed after capping MNPs with biopolymers, corroborating the hypothesis that upon surface functionalization, affinity for Pb (II) adsorption by the magnetic adsorbents was enhanced. Adsorption was more effective at pH = 5.5, and the contact time required to reach equilibrium was relatively short (∼30 min), following a pseudo-second-order model, with adsorption capacities of (34 to 46 mg g−1), calculated from Sips model. Regeneration studies revealed that the nanosorbents can be recovered for reuse, indicating their use as a powerful tool for Pb (II) removal from contaminated water.
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