Sustainable Lithium Recovery from Hypersaline Salt-Lakes by Selective Electrodialysis: Transport and Thermodynamics.

Evaporative technology for lithium mining from salt-lakes exacerbates freshwater scarcity and wetland destruction, and suffers from protracted production cycles. Electrodialysis (ED) offers an environmentally benign alternative for continuous lithium extraction and is amenable to renewable energy usage. Salt-lake brines, however, are hypersaline multicomponent mixtures, and the impact of the complex brine-membrane interactions remains poorly understood. Here, we quantify the influence of the solution composition, salinity, and acidity on the counterion selectivity and thermodynamic efficiency of electrodialysis, leveraging 1250 original measurements with salt-lake brines that span four feed salinities, three pH levels, and five current densities. Our experiments reveal that commonly used binary cation solutions, which neglect Na+ and K+ transport, may overestimate the Li+/Mg2+ selectivity by 250% and underpredict the specific energy consumption (SEC) by a factor of 54.8. As a result of the hypersaline conditions, exposure to salt-lake brine weakens the efficacy of Donnan exclusion, amplifying Mg2+ leakage. Higher current densities enhance the Donnan potential across the solution-membrane interface and ameliorate the selectivity degradation with hypersaline brines. However, a steep trade-off between counterion selectivity and thermodynamic efficiency governs ED's performance: a 6.25 times enhancement in Li+/Mg2+ selectivity is accompanied by a 71.6% increase in the SEC. Lastly, our analysis suggests that an industrial-scale ED module can meet existing salt-lake production capacities, while being powered by a photovoltaic farm that utilizes <1% of the salt-flat area.

Modeling COVID-19 transmission between age groups in the United States considering virus mutations, vaccinations, and reinfection.

The in-depth understanding of the dynamics of COVID-19 transmission among different age groups is of great interest for governments and health authorities so that strategies can be devised to reduce the pandemic's detrimental effects. We developed the SIRDV-Virulence (Susceptible-Infected-Recovered-Dead-Vaccinated-Virulence) epidemiological model based on a population balance equation to study the effects virus mutants, vaccination strategies, 'Anti/Non Vaxxer' proportions, and reinfection rates to provide methods to mitigate COVID-19 transmission among the United States population. Based on publicly available data, we obtain the key parameters governing the spread of the pandemic. The results show that a large fraction of infected cases comes from the adult and children populations in the presence of a highly infectious COVID-19 mutant. Given the situation at the end of July 2021, the results show that prioritizing children and adult vaccinations over that of seniors can contain the spread of the active cases, thereby preventing the healthcare system from being overwhelmed and minimizing subsequent deaths. The model suggests that the only option to curb the effects of this pandemic is to reduce the population of unvaccinated individuals. A higher fraction of 'Anti/Non-vaxxers' and a higher reinfection rate can both independently lead to the resurgence of the pandemic.