Renewable energy (RE) utilization is expected to increase in the coming years due to its decreasing costs and the mounting socio-political pressure to decarbonize the world’s energy systems. On the other hand, lithium-ion (Li-ion) batteries are on track to hit the target 100 USD/kWh price in the next decade due to economy of scale and manufacturing process improvements, evident in the rise in Li-ion gigafactories. The forecast of RE and Li-ion technology costs is important for planning RE integration into existing energy systems. Previous cost predictions on Li-ion batteries were conducted using conventional learning curve models based on a single factor, such as either installed capacity or innovation activity. A two-stage learning curve model was recently investigated wherein mineral costs were taken as a factor for material cost to set the floor price, and material cost was a major factor for the battery pack price. However, these models resulted in the overestimation of future prices. In this work, the future prices of Li-ion nickel manganese cobalt oxide (NMC) battery packs - a battery chemistry of choice in the electric vehicle and stationary grid storage markets - were projected up to year 2025 using multi-factor learning curve models. Among the generated models, the two-factor learning curve model has the most realistic and statistically sound results having learning rates of 21.18% for battery demand and 3.0% for innovation. By year 2024, the projected price would fall below the 100 USD/kWh industry benchmark battery pack price, consistent with most market research predictions. Techno-economic case studies on the microgrid applications of the forecasted prices of Li-ion NMC batteries were conducted. Results showed that the decrease in future prices of Li-ion NMC batteries would make 2020 and 2023 the best years to start investing in an optimum (solar photovoltaic + wind + diesel generator + Li-ion NMC) and 100% RE (solar photovoltaic + wind + Li-ion NMC) off-grid energy system, respectively. A hybrid grid-tied (solar photovoltaic + grid + Li-ion NMC) configuration is the best grid-tied energy system under the current net metering policy, with 2020 being the best year to deploy the investment.

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Sluggish kinetics in oxygen reduction reaction (ORR) requires low-cost and highly durable electrocatalysts ideally produced from facile methods. In this work, we explored the conversion and utilization of waste biomass as potential carbon support for α-MnO2 catalyst in enhancing its ORR performance. Carbon supports were derived from different waste biomass via hydrothermal carbonization (HTC) at different temperature and duration, followed by KOH activation and subsequent heat treatment. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDX) and X-Ray diffraction (XRD) were used for morphological, chemical, and structural characterization, which revealed porous and amorphous carbon supports for α-MnO2. Electrochemical studies on ORR activity suggest that carbon-supported α-MnO2 derived from HTC of corncobs at 250 °C for 12 h (CCAC + MnO2 250-12) gives the highest limiting current density and lowest overpotential among the synthesized carbon-supported catalysts. Moreover, CCAC + MnO2 250-12 facilitates ORR through a 4-e‑ pathway, and exhibits higher stability compared to VC + MnO2 (Vulcan XC-72) and 20% Pt/C. The synthesis conditions preserve oxygen functional groups and form porous structures in corncobs, which resulted in a highly stable catalyst. Thus, this work provides a new and cost-effective method of deriving carbon support from biomass that can enhance the activity of α-MnO2 towards ORR.

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