Biodegradable biobased polymers derived from biomass (such as plant, animal, marine, or forestry material) show promise in replacing conventional petrochemical polymers. Research and development have been conducted for decades on potential biodegradable biobased polymers such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs), and succinate polymers. These materials have been evaluated for practicality, cost, and production capabilities as limiting factors in commercialization; however, challenges, such as the environmental limitations on the biodegradation rates for biodegradable biobased polymer, need to be addressed. This review provides a history and overview of the current development in the synthesis process and properties of biodegradable biobased polymers, along with a techno-commercial analysis and discussion on the environmental impacts of biodegradable biobased polymers. Specifically, the techno-commercial analysis focuses on the commercial potential, financial assessment, and life-cycle assessment of these materials, as well as government initiatives to facilitate the transition towards biodegradable biobased polymers. Lastly, the environmental assessment focuses on the current challenges with biodegradation and methods of improving the recycling process and reusability of biodegradable biobased polymers.

Products made from additive manufacturing processes have attracted great attention in engineering, health care, and society at large. However, there is little knowledge about the failure of additively manufactured alloys, in particular, corrosion and wear seen in most engineering applications. The haphazard and inefficient usage of such alloys raised concerns about safety, compatibility, reliability, cost, and consumer satisfaction. To address those concerns, we studied the mechanisms of the most common failure modes, corrosion and wear, of alloys fabricated through additive manufacturing based on published literature. It was found that the processing conditions have profound influence on microstructure and thus corrosion and wear resistance of alloys. Because of the layered structure, the initiation and growth of both corrosion and wear exhibited anisotropic behavior. The insights from this review could be used as a reference of the state-of-the art and to help in the development of future additively manufactured alloys with improved corrosion and wear properties.

This review compares machine learning approaches for property prediction of materials, optimization, and energy storage device health estimation. Current challenges and prospects for high-impact areas in machine learning research are highlighted.

As modern devices and systems continue to advance, device wear remains a key factor in limiting their performance and lifetime, as well as environmental and health effects. Traditional approaches often rely on wear prediction based on physical models, but due to device complexity and uncertainty, these methods often fail to provide accurate predictions and accurate wear identification. Machine learning, as a data-driven approach based on its ability to discover patterns and correlations in complex systems, has enormous potential for monitoring and predicting device wear. Here, we review recent advances in applying machine learning for predicting the wear of mechanical components. Machine learning for wear prediction shows significant potential in optimizing material selection, manufacturing processes, and equipment maintenance, ultimately enhancing productivity and resource efficiency. Successful implementation relies on careful data collection, standardized evaluation methods, and the selection of effective algorithms, with artificial neural networks (ANNs) frequently demonstrating notable success in predictive accuracy.

The demand for energy storage devices made from biodegradable materials has increased significantly due to sustainability. Currently, such devices possess vital issues, such as high manufacturing costs and toxicity, low reliability, as well as poor electrochemical performance. In this research, microwave synthesis was conducted to fabricate a low-cost, high-performing, plant-based electroactive material. MnO₂ microparticles fabricated via microwave irradiation were deposited on two plant-based materials as substrates made of Al/lignin and Al/AC/lignin. The quasi-solid-state supercapacitors were assembled using a polymeric gel electrolyte of PVA/H₃PO₄. Scanning electron microscopy was performed to examine the polydispersity, morphology, and porosity of the micro-MnO2 deposited materials. FTIR and UV-vis spectroscopy were performed to study the composition and verify deposition of micro-MnO₂ on the lignin-based matrixes. Cyclic voltammetry (CV) was employed to study the polarization resistance of the system. The cyclic charge-discharge (CCD) and electrochemical impedance spectroscopy (EIS) were performed to observe cyclic performance and interfacial resistances. Electrochemical tests showed that after 700 cycles of charge-discharge, both the supercapacitors exhibited high capacitance retention above 90%. Compared to the existing technology, this method enables consistent material structurization with tunable properties due to the controlled heating time and exposure to radiation with minimal waste. This work provides an alternative approach to synthesize low-cost and scalable green composite electrodes for flexible supercapacitors.

Due to demands for sustainability, the interest in energy storage devices constructed from green materials has increased immensely. These devices currently have yet to be satisfactory. Issues include high production costs and toxicity, limited dependability, and subpar electrochemical performance. In this research, low-cost, plant-based electroactive Cu₃Mo₂O₉ materials were synthesized via co-precipitation followed by an annealing method using two different structure-directing agents, i.e., the commonly used surfactant cetyltrimethylammonium bromide (CTAB) and the biomolecule deoxyribonucleic acid (DNA) as a greener alternative, and these materials were studied for the first time. Further, the Cu₃Mo₂O₉ nanoparticles developed using CTAB and DNA were integrated into the lignin matrix and studied as flexible electrodes for supercapacitor application. Here, the morphological advantages of the nanorods and nanosheets formed by varying the synthesis methods and their effects during supercapacitor studies were studied in detail. After 1200 cycles, the Al/lig-Cu₃Mo₂O₉@DNA supercapacitor exhibited higher capacitive performance when compared to the Al/lig-Cu₃Mo₂O₉@CTAB supercapacitor. The Al/Lig-Cu₃Mo₂O₉@DNA supercapacitor had an initial specific capacitance of 404.64 mF g⁻¹ with a ~70% retention, while the Al/Lig-Cu₃Mo₂O₉@CTAB supercapacitor had an initial specific capacitance of 309.59 mF g⁻¹ with a ~50% retention. This study offers a new approach to creating scalable, low-cost, green composite CuMoO₄-based electrodes for flexible supercapacitors.