Nano Boron Oxide and Zinc Oxide Doped Lignin Containing Cellulose Nanocrystals Improve the Thermal, Mechanical and Flammability Properties of High-Density Poly(ethylene).

The widely used high-density polyethylene (HDPE) polymer has inadequate mechanical and thermal properties for structural applications. To overcome this challenge, nano zinc oxide (ZnO) and nano boron oxide (B2O3) doped lignin-containing cellulose nanocrystals (L-CNC) were blended in the polymer matrix. The working hypothesis is that lignin will prevent CNC aggregation, and metal oxides will reduce the flammability of polymers by modifying their degradation pathways. This research prepared and incorporated safe, effective, and eco-friendly hybrid systems of nano ZnO/L-CNC and nano B2O3/L-CNC into the HDPE matrix to improve their physio-mechanical and fire-retardant properties. The composites were characterized using Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray analysis, thermo-gravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, horizontal burning test, and microcalorimetry test. The results demonstrated a substantial increase in mechanical properties and a reduction in flammability. The scanning electron microscope (SEM) images showed some agglomeration and irregular distribution of the inorganic oxides.

Evaluation of OptRx™ active optical sensor to monitor soybean response to nitrogen inputs.

BACKGROUND: Active optical crop sensors have been gaining importance to determine in-season nitrogen (N) fertilization requirements for on-the-go variable rate applications. Although most of these active in-field crop sensors have been evaluated in maize (Zea mays L.) and wheat (Triticum aestivum L. emend. Thell.), these sensors have not been evaluated in soybean [Glycine max (L.) Merr.] production systems in North Dakota, USA. Recent research from both South Dakota and North Dakota, USA indicate that in-season N application in soybean can increase soybean yield under certain conditions. RESULTS: The study revealed that OptRx™ sensor reading did not show any significant differences from early to midway through the growing season. The NDRE (normalized difference red edge) index data collected towards the end of the growing season showed significantly higher values for some of the N treatments as compared to others in both years. The NDRE values were strongly correlated to grain yield for both years under tiled (r = 0.923) and non-tiled (r = 0.901) drainage conditions. Certain soybean varieties displayed significantly higher NDRE values over both years. The three varieties tested across years, under both tiled and non-tiled conditions, showed a significant linear relationship between late August NDRE values and yield (R2  = 0.85 for tiled and R2  = 0.81 for non-tiled). CONCLUSION: In this research, the study results show that the OptRx™ sensor has the potential to work for soybean as well, though later in the crop growing season. Further investigation is needed to confirm the use of OptRx™ sensor for variable rate in-season N applications in soybeans. © 2019 Society of Chemical Industry.

Functionalized Cellulose Nanocrystals: A Potential Fire Retardant for Polymer Composites.

The flammability of synthetic thermoplastic polymers has been recognized as an increasingly important safety problem. The goal of this study was to evaluate a green and safe fire-retardant system comprising of cellulose nanocrystals (CNC) and zinc oxide nanoparticles (ZnO). CNCs coated with nano ZnO were incorporated in the high-density polyethylene polymer (HDPE) matrix at different concentrations. Fire testing results of different formulations of HDPE containing 0.4 to 1.0% zinc oxide coated CNC exhibited a substantial decrease in the average mass loss, peak heat release rate and total smoke release. The time to ignition exhibited a positive correlation with CNC-ZnO concentration. Modest improvement in the flexural strength and moduli of composites was noticed validating no adverse effects of CNC-ZnO complex. The transmission electron microscopy further confirmed dispersion of nanoparticles as well as the presence of some nanoparticle aggregates in the matrix. The uniform dispersion of CNC-ZnO complex is expected to further improve fire and mechanical properties of polymer.

Deterioration in the Physico-Mechanical and Thermal Properties of Biopolymers Due to Reprocessing.

Biopolymers are an emerging class of materials being widely pursued due to their ability to degrade in short periods of time. Understanding and evaluating the recyclability of biopolymers is paramount for their sustainable and efficient use in a cost-effective manner. Recycling has proven to be an important solution, to control environmental and waste management issues. This paper presents the first recycling assessment of Solanyl, Bioflex, polylactic acid (PLA) and PHBV using a melt extrusion process. All biopolymers were subjected to five reprocessing cycles. The thermal and mechanical properties of the biopolymers were investigated by GPC, TGA, DSC, mechanical test, and DMA. The molecular weights of Bioflex and Solanyl showed no susceptible effect of the recycling process, however, a significant reduction was observed in the molecular weight of PLA and PHBV. The inherent thermo-mechanical degradation in PHBV and PLA resulted in 20% and 7% reduction in storage modulus, respectively while minimal reduction was observed in the storage modulus of Bioflex and Solanyl. As expected from the Florry-Fox equation, recycled PLA with a high reduction in molecular weight (78%) experienced 9% reduction in glass transition temperature. Bioflex and Solanyl showed 5% and 2% reduction in molecular weight and experienced only 2% reduction in glass transition temperature. These findings highlight the recyclability potential of Bioflex and Solanyl over PLA and PHBV.

Influence of Hybridizing Flax and Hemp-Agave Fibers with Glass Fiber as Reinforcement in a Polyurethane Composite.

In this study, six combinations of flax, hemp, and glass fiber were investigated for a hybrid reinforcement system in a polyurethane (PU) composite. The natural fibers were combined with glass fibers in a PU composite in order to achieve a better mechanical reinforcement in the composite material. The effect of fiber hybridization in PU composites was evaluated through physical and mechanical properties such as water absorption (WA), specific gravity (SG), coefficient of linear thermal expansion (CLTE), flexural and compression properties, and hardness. The mechanical properties of hybridized samples showed mixed trends compared to the unhybridized samples, but hybridization with glass fiber reduced water absorption by 37% and 43% for flax and hemp-agave PU composites respectively.

Removal of surface reflection from above-water visible-near infrared spectroscopic measurements.

Water quality estimation in fresh and marine water systems with in situ above-water spectroscopy requires measurement of the volume reflectance (rhov) of water bodies. However, the above-water radiometric measurements include surface reflection (Lr) as a significant component along with volume reflection. The Lr carries no information on water quality, and hence it is considered as a major source of error in in situ above-water spectroscopy. Currently, there are no methods to directly measure Lr. The common method to estimate Lr assumes a constant water surface reflectance (rhos) of 2%, and then subtracts the Lr thus calculated from the above-water radiance measurements to obtain the volume reflection (Lv). The problem with this method is that the amount of rhos varies with environmental conditions. Therefore, a methodology was developed in this study for direct measurement of water volume reflectance above water at nadir view geometry. Other objectives of this study were to analyze the contribution of Lr to the total water reflectance under various environmental conditions in a controlled setup and to develop an artificial neural network (ANN) model to estimate rhos from environmental conditions. The results showed that Lr contributed 20-54% of total upwelling radiance from water at nadir. The rhos was highly variable with environmental conditions. Using sun altitude, wind speed, diffuse lighting, and wavelength as inputs, the ANN model was able to accurately simulate rhos, with a low root mean square error of 0.003. A sensitivity analysis with the ANN model indicated that sun altitude and diffuse light had the highest influence on rhos, contributing to over 82% of predictability of the ANN model. Therefore, the ANN modeling framework can be an accurate tool for estimating surface reflectance in applications that require volume reflectance of water.