Sulfur-based polymers are unique renewable materials that are receiving a growing attention. The utilization of elemental sulfur with a variety of monomers in their preparation in the absence of solvents using the inverse vulcanization are granting them green nature and unique properties. Several characterization techniques have been used to evaluate the properties of sulfur-based polymers. However, the complex structure and lack of solubility undermine the applicability of some standard characterization techniques in the usual manners. This article reviews the characterization methods used for the evaluation of various properties of sulfur-based polymers such as chemical, morphological, structural, thermal, rheological and mechanical properties, all of which vary depending on the type of comonomer involved in the reaction and heat treatment conditions. The successful applications of different characterization techniques including Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, nuclear magnetic resonance (NMR), scanning electron microscopy/X-ray energy dispersion (SEM-EDX), X-ray diffraction (XRD), mechanical tester, rheometer, thermal gravimetric analyzer (TGA) and differential scanning calorimetry (DSC) are discussed. The challenges to the evaluation of the properties of sulfur-based polymers and the innovative applications of the conventional techniques to overcome them are also deliberated.

In the oil and gas construction industry, the adoption of superhydrophobic coatings is still in the early adoption phase. Due to the lack of research and the importance of hydrophobic coatings in the oil and gas construction business, this study examined the success determinants of superhydrophobic coatings in Malaysia. This quantitative study included a pilot survey to assess questionnaire validity and Exploratory Factor Analysis (EFA) to reduce success variables discovered through a literature review. A structural equation modeling (SEM) approach was used to develop a model involving success factors of superhydrophobic coatings in the oil and gas construction industry of Malaysia. Four constructs in total were found in SEM, namely, performance success, sustainability construct, oil spill management, and safety and economic success. In total, five items were excluded from the model because their loading factors were less than 0.6. All Cronbach Alpha reliability constants were greater than 0.7, the composite reliability indicators were greater than 0.8, and the AVE was greater than 0.6 for all of the constructs, confirming acceptable reliability and validity statistics. Both convergent and discriminant validity confirmed the relationships between all constructs and the latent variable. The observed path coefficients between the constructs and the latent variable were 0.476 for performance success, 0.461 for sustainability success, 0.322 for oil spill management, and 0.242 for safety and economic success. The significance value for all of the constructs was less than 0.05, confirming the strong relationship between the constructs and the critical success of superhydrophobic coatings in the oil and gas industry.

To improve crop nutrient uptake efficacy (NUE) and better manage fertilization, slow-release fertilizers (SRFs) are developed by either coating the urea granules or making a composite. Several materials have already been developed, nevertheless, scalability of those materials is still a challenge due to their inherit drawbacks (such as hydrophilicity, crystallinity, non-biodegradability, etc.). Herein, we utilized a biodegradable, green and sustainable copolymer produced from industrial waste (sulfur-petroleum industry waste and myrcene-citrus industry waste) to coat the urea using a facile coating method to develop novel SRFs and achieve better agronomic and environmental advantages. The copolymer was first synthesized using a facile, solvent-free one-pot method called inverse vulcanization followed by Fourier transform infrared spectroscopy (FTIR) analysis to confirm the successful reaction between myrcene and sulfur subsequently coating the copolymer on urea granule. The morphology and coating thickness of coated fertilizers were analysed using scanning electron microscopy (SEM), followed by a nitrogen release test in distilled water and a soil burial test to confirm the biodegradability. The nitrogen release test revealed that the SRF with the maximum coating thickness of 1733 μm releases only 16% of its total nitrogen after 4 days of incubation compared to the pristine urea which releases all its nutrient within 1 day. The soil burial test confirms the biodegradability of the copolymer, as after 50 days of incubation in soil the copolymer loses almost 18.25% of its total weight indicating that the copolymer is degrading.

Global enhancement of crop yield is achieved using chemical fertilizers; however, agro-economy is affected due to poor nutrient uptake efficacy (NUE), which also causes environmental pollution. Encapsulating urea granules with hydrophobic material can be one solution. Additionally, the inverse vulcanized copolymer obtained from vegetable oils are a new class of green sulfur-enriched polymer with good biodegradation and better sulfur oxidation potential, but they possess unreacted sulfur, which leads to void generations. In this study, inverse vulcanization reaction conditions to minimize the amount of unreacted sulfur through response surface methodology (RSM) is optimized. The copolymer obtained was then characterized using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). FTIR confirmed the formation of the copolymer, TGA demonstrated that copolymer is thermally stable up to 200 °C temperature, and DSC revealed the sulfur conversion of 82.2% (predicted conversion of 82.37%), which shows the goodness of the model developed to predict the sulfur conversion. To further maximize the sulfur conversion, 5 wt% diisopropenyl benzene (DIB) as a crosslinker is added during synthesis to produce terpolymer. The urea granule is then coated using terpolymer, and the nutrient release longevity of the coated urea is tested in distilled water, which revealed that only 65% of its total nutrient is released after 40 days of incubation. The soil burial of the terpolymer demonstrated its biodegradability, as 26% weight loss happens in 52 days of incubation. Thus, inverse vulcanized terpolymer as a coating material for urea demonstrated far better nutrient release longevity compared with other biopolymers with improved biodegradation; moreover, these copolymers also have potential to improve sulfur oxidation.

Adulteration of meat products is a delicate issue for people around the globe. The mixing of lard in meat causes a significant problem for end users who are sensitive to halal meat consumption. Due to the highly similar lipid profiles of meat species, the identification of adulteration becomes more difficult. Therefore, a comprehensive spectral detailing of meat species is required, which can boost the adulteration detection process. The experiment was conducted by distributing samples labeled as “Pure (80 samples)” and “Adulterated (90 samples)”. Lard was mixed with the ratio of 10–50% v/v with beef, lamb, and chicken samples to obtain adulterated samples. Functional groups were discovered for pure pork, and two regions of difference (RoD) at wavenumbers 1700–1800 cm⁻¹ and 2800–3000 cm⁻¹ were identified using absorbance values from the FTIR spectrum for all samples. The principal component analysis (PCA) described the studied adulteration using three principal components with an explained variance of 97.31%. The multiclass support vector machine (M-SVM) was trained to identify the sample class values as pure and adulterated clusters. The acquired overall classification accuracy for a cluster of pure samples was 81.25%, whereas when the adulteration ratio was above 10%, 71.21% overall accuracy was achieved for a group of adulterated samples. Beef and lamb samples for both adulterated and pure classes had the highest classification accuracy value of 85%, whereas chicken had the lowest value of 78% for each category. This paper introduces a comprehensive spectrum analysis for pure and adulterated samples of beef, chicken, lamb, and lard. Moreover, we present a rapid M-SVM model for an accurate classification of lard adulteration in different samples despite its low-level presence.