Synthesis and applications of bismuth-impregnated biochars originated from spent coffee grounds for efficient adsorption of radioactive iodine: A mechanism study

Unraveling the nuclear isotope tapestry: Applications, challenges, and future horizons in a dynamic landscape

Nuclear isotopes, distinct atoms characterized by varying neutron counts, have profoundly influenced a myriad of sectors, spanning from medical diagnostics and therapeutic interventions to energy production and defense strategies. Their multifaceted applications have been celebrated for catalyzing revolutionary breakthroughs, yet these advancements simultaneously introduce intricate challenges that warrant thorough investigation. These challenges encompass safety protocols, potential environmental detriments, and the complex geopolitical landscape surrounding nuclear proliferation and disarmament. This comprehensive review embarks on a deep exploration of nuclear isotopes, elucidating their nuanced classifications, wide-ranging applications, intricate governing policies, and the multifaceted impacts of their unintended emissions or leaks. Furthermore, the study meticulously examines the cutting-edge remediation techniques currently employed to counteract nuclear contamination while projecting future innovations in this domain. By weaving together historical context, current applications, and forward-looking perspectives, this review offers a panoramic view of the nuclear isotope landscape. In conclusion, the significance of nuclear isotopes cannot be understated. As we stand at the crossroads of technological advancement and ethical responsibility, this review underscores the paramount importance of harnessing nuclear isotopes' potential in a manner that prioritizes safety, sustainability, and the greater good of humanity.

Transformer-based deep learning models for adsorption capacity prediction of heavy metal ions toward biochar-based adsorbents

Biochar adsorbents synthesized from food and agricultural wastes are commonly applied to eliminate heavy metal (HM) ions from wastewater. However, biochar's diverse characteristics and varied experimental conditions make the accurate estimation of their adsorption capacity (qe) challenging. Herein, various machine-learning (ML) and three deep learning (DL) models were built using 1518 data points to predict the qe of HM on various biochars. The recursive feature elimination technique with 28 inputs suggested that 14 inputs were significant for model building. FT-transformer with the highest test R2 (0.98) and lowest root mean square error (RMSE) (0.296) and mean absolute error (MAE) (0.145) outperformed various ML and DL models. The SHAP feature importance analysis of the FT-transformer model predicted that the adsorption conditions (72.12%) were more important than the pyrolysis conditions (25.73%), elemental composition (1.39%), and biochar's physical properties (0.73%). The two-feature SHAP analysis proposed the optimized process conditions including adsorbent loading of 0.25 g, initial concentration of 12 mg/L, and solution pH of 9 using phosphoric-acid pre-treated biochar synthesized from banana-peel with a higher O/C ratio. The t-SNE technique was applied to transform the 14-input matrix of the FT-Transformer into two-dimensional data. Finally, we outlined the study's environmental implications.

Microbial involvement in iodine cycle: mechanisms and potential applications

Stable iodine isotopes are essential for humans as they are necessary for producing thyroid gland hormones. However, there are hazardous radioactive iodine isotopes that are emitted into the environment through radioactive waste generated by nuclear power plants, nuclear weapon tests, and medical practice. Due to the biophilic character of iodine radionuclides and their enormous biomagnification potential, their elimination from contaminated environments is essential to prevent the spread of radioactive pollution in ecosystems. Since microorganisms play a vital role in controlling iodine cycling and fate in the environment, they also can be efficiently utilized in solving the issue of contamination spread. Thus, this paper summarizes all known on microbial processes that are involved in iodine transformation to highlight their prospects in remediation of the sites contaminated with radioactive iodine isotopes.

Functionalization of pine sawdust biochars with Mg/Al layered double hydroxides to enhance adsorption capacity of synthetic azo dyes: Adsorption mechanisms and reusability

This study determined that the adsorption of azo dyes, Methyl Orange (MO) and Sunset Yellow FCF (SYF), using the pristine pine sawdust biochar (PSB) and post-modified PSB with Mg/Al layered double hydroxides (PSB-LDH_MgAl) was examined to offer valuable information into the differences in their adsorption mechanisms. Although a lower specific surface area of PSB-LDH_MgAl (147.2 m² g^-1) than PSB (495.7 m² g^-1), LDH_MgAl were successfully functionalized on the PSB surface through co-precipitation, which was highly related to the improvements of adsorption capacity of PSB-LDH_MgAl toward MO and SYF. The MO and SYF adsorption kinetics by PSB and PSB-LDH_MgAl were confirmed to the pseudo-second-order and considered chemisorption. The adsorption capacity of MO and SYF adsorbed onto PSB-LDH_MgAl (MO = 21.8 mg g^-1, SYF = 23.6 mg g^-1) were significantly higher than that of PSB (MO = 2.2 mg g^-1, SYF = 1.6 mg g^-1). The adsorption isotherms of MO and SYF by PSB were well fitted by Freundlich isotherm, whereas the MO and SYF via PSB-LDH_MgAl were by Langmuir isotherm. Even after 3 adsorption-desorption cycles using desorbents, the PSB-LDH_MgAl remained excellent reusability (reuse efficiency: >81.2%). These findings suggest that post-modification with LDH_MgAl might accelerate the adsorption performance (i.e., electrostatic interaction) of azo dyes to PSB in water.