Intrinsic challenges and strategic approaches for enhancing the potential of natural rubber and its derivatives: A review

Natural rubber (NR) and its derivatives play indispensable roles in various industries due to their unique properties and versatile applications. However, the widespread utilization of NR faces intrinsic challenges such as limited mechanical strength, poor resistance to heat and organic solvent, poor electrical conductivity, and low compatibility with other materials, prompting researchers to explore enhancing its performance. Modified NRs (MNRs) like cyclization, deproteinization, chlorination, epoxidation, or grafting NR demonstrated a few enhanced merits compared to NR. However, various strategies, such as blending, vulcanization, crosslinking, grafting, plasticization, reinforcement, and nanostructuring, overcame most drawbacks. This review comprehensively examines these challenges and delves into the modification strategies employed to enhance the properties and expand the applications of NR and its derivatives. Furthermore, the review explores future visions for the NR industry, emphasizing integrating advanced modification techniques, adopting sustainable practices, and promoting circular economy principles. By elucidating the inherent challenges, outlining effective modification strategies, and envisioning future trajectories, this review provides valuable insights for stakeholders seeking to navigate and contribute to the sustainable development of the NR sector.

Free-Radical Photopolymerization of Acrylonitrile Grafted onto Epoxidized Natural Rubber

The exploitation of epoxidized natural rubber (ENR) in electrochemical applications is approaching its limits because of its poor thermo-mechanical properties. These properties could be improved by chemical and/or physical modification, including grafting and/or crosslinking techniques. In this work, acrylonitrile (ACN) has been successfully grafted onto ENR- 25 by a radical photopolymerization technique. The effect of (ACN to ENR) mole ratios on chemical structure and interaction, thermo-mechanical behaviour and that related to the viscoelastic properties of the polymer was investigated. The existence of the –C≡N functional group at the end-product of ACN-g-ENR is confirmed by infrared (FT-IR) and nuclear magnetic resonance (NMR) analyses. An enhanced grafting efficiency (~57%) was obtained after ACN was grafted onto the isoprene unit of ENR- 25 and showing a significant improvement in thermal stability and dielectric properties. The viscoelastic behaviour of the sample analysis showed an increase of storage modulus up to 150 × 10³ MPa and the temperature of glass transition (T_g) was between −40 and 10 °C. The loss modulus, relaxation process, and tan delta were also described. Overall, the ACN-g-ENR shows a distinctive improvement in characteristics compared to ENR and can be widely used in many applications where natural rubber is used but improved thermal and mechanical properties are required. Likewise, it may also be used in electronic applications, for example, as a polymer electrolyte in batteries or supercapacitor.

Combined mechanistic and genetic programming approach to modeling pilot NBR production: influence of feed compositions on rubber Mooney viscosity

Mooney viscosity is an essential parameter in quality control during the production of nitrile-butadiene rubber (NBR) by emulsion polymerization. A process model that could help understand the influence of feed compositions on the Mooney viscosity of NBR products is of vital importance for its intelligent manufacture. In this work, a process model comprised of a mechanistic model based on emulsion polymerization kinetics and a data-driven model derived from genetic programming (GP) for Mooney viscosity is developed to correlate the feed compositions (including impurities) and process conditions to Mooney viscosity of NBR products. The feed compositions are inputs of the mechanistic model to generate the number-, weight-averaged molecular weights (M n, M w) and branching degree (BRD) of NBR polymers. With these generated data, the GP model is used to output the optimal correlation for the Mooney viscosity of NBR. In a pilot NBR production, Mooney viscosity data of NBR predicted by the process model agree quite well with experimental values. Furthermore, the process model enables the analyses of the univariate and multivariate influence of feed compositions on NBR Mooney viscosity, and the variables include the contents of vinyl acetylene and dimer in 1,3-butadiene, as well as the mass flow rate of the chain transfer agent (CTA) in the process. Based on the results, it is recommended to control the content of vinyl acetylene in the 1,3-butadiene feed below 14 ppm and the content of dimer below 1100 ppm. This developed process model would help stabilize NBR viscosity for a better control of the product quality.