Stepan Nikolaevich Kalmykov

The use of artificial intelligence (AI) tools in the preparation of scientific publications has become an integral part of research practice. Large language models assist in translating and editing texts, structuring articles, drafting abstracts, adapting manuscripts to journal requirements, and accelerating preliminary literature reviews, among other useful functions. However, the technical utility of the tool does not alter the fundamental principle: a scientific article remains the product of a researcher's work, for which they bear responsibility. AI cannot be recognized as a co-author, nor can it be held accountable for data authenticity, the correctness of chemical nomenclature, the logic of the presentation, the completeness of citations, or the validity of conclusions. This article presents the position of Editors-in-Chief and Editorial Board members from several Russian chemistry journals regarding the use of AI in preparing scientific publications. To practically regulate the use of AI in scientific article preparation, the VALENCE set of rules is proposed, in alignment with international publishing practices. Bibliography includes 42 references.

BADPA-18 was evaluated as a chelator for 212Pb-based radiopharmaceuticals, with 210Pb used as a surrogate for in vivo biodistribution studies. A three-column chromatographic procedure provided 212Pb in 0.01 M HCl with >90% yield, suitable for direct radiolabeling. [212Pb]PbBADPA-18 was obtained within 1–2 min at room temperature. In serum, the fraction of 212Bi associated with serum proteins was 7.5% for [212Pb]PbBADPA-18, compared with 34% for [212Pb]PbDOTA. [210Pb]PbBADPA-18 showed low tissue accumulation and rapid clearance in mice, indicating high in vivo stability of the complex over the observation period. These results demonstrate the potential of BADPA-18 for mild and rapid radiolabeling of 212Pb and support its further development for 203Pb/212Pb theranostic applications.

Liquid radioactive waste injected into deep geologic horizons poses a long-term hazard for the environment. Uranium-238, a major component of the nuclear fuel cycle and radioactive waste, has long half-life, high mobility, high toxicity, and complex chemical behavior. Sorption is a crucial process for the radionuclides retention in geosphere and isolation of the waste. In the present work, sorption of U(VI) on the sediments from Severny deep disposal site (Krasnoyarsk, Russia) and reference minerals (quartz and clay) was studied in laboratory-simulated low-level alkaline liquid radioactive waste solutions. U sorption behavior is strongly pH-dependent. It was determined that in the wide pH range U uptake is mostly controlled by quartz in the specific conditions. As uranyl-carbonate complexes play important role in the alkaline medium, carbonate concentration affects the U retention. Contribution of the aquifer constituent minerals was estimated using autoradiography method. Surface complexation reactions for U(VI) sorption on the aquifer sediments were modelled.

The possibility of using carboxymethylcellulose as a platform for transporting ruthenium or bismuth ions in the body along with a medicinal preparation (a thiourea-derived NO synthase activator) was examined. Carboxymethylcellulose microgels were obtained by cross-linking with ruthenium or bismuth ions in a biological environment, and differences in their physicochemical parameters were identified. Furthermore, it was found that the size and aggregation stability of the microgels depend on the amount of the introduced organic ligand-drug.

Nuclear energy contributes to reducing greenhouse gas emissions, but the reprocessing of spent nuclear fuel generates high-level waste that requires safe and efficient management. Diglycolamides (DGAs) are promising CHON-compliant, non-selective extractants widely investigated for actinide and lanthanide separation. Their extraction performance is strongly dependent on ligand structure, particularly on conformational flexibility and preorganization. Structural preorganization through cyclization of DGA-based ligands represents an effective strategy to modulate coordination behavior and extraction properties. In this work, a series of new cyclic diglycolamide ligands (L1–L4) were designed using computational modeling and subsequently synthesized. Their coordination behavior was investigated both in solution by NMR titration and in the solid state by single-crystal X-ray diffraction. Their extraction performance toward trivalent f-elements was systematically evaluated. For the first time, the formation of lanthanum complexes with the composition [LaL(NO₃)₄]₂[LaL₂(NO₃)(H₂O)₂], corresponding to 1 : 1 and 2 : 1 ligand-to-metal stoichiometries, was identified for DGA-based ligands. These findings demonstrate that ligand cyclization significantly affects coordination modes and extraction behavior, highlighting the potential of cyclic DGAs as extractants for nuclear waste management.

Extraction systems based on organophosphorus compounds (DEHPA, TBP, and TOPO) in HCl and HNO3 were studied for developing a reverse 44Ti/44Sc generator. The 1.8 M TBP-7 M HCl and 0.18 M TOPO-3 M HCl systems demonstrated high separation efficiency in a multistage process and provided 44Sc extraction yields of 96.4 and 93.6

The kinetic isotope effect (KIE) is essential in various chemical applications from reaction mechanism studies to tritium removal from water, however, its evaluation is associated with computational difficulties, mainly related to the correct determination of the geometry of the transition state. Traditional KIE evaluation relies on experimental measurements or computational approaches like density functional theory (DFT), which are often costly and whose accuracy strongly depends on the level of theory used. Here, we present a novel semi‐empirical method for rapid and precise KIE estimation in proton‐exchange reactions. By refining transition state identification through an iterative surface scan, our approach significantly improves accuracy while maintaining computational efficiency. Benchmarking against experimental data demonstrates superior performance compared to both DFT and conventional semi‐empirical methods. Additionally, validation with tritium exchange reactions confirms its robustness. The computational implementation is freely available, facilitating its integration into future research.

CeO ₂ nanoparticles undergo redox transformation in the lungs, forming needle-like Ce( iii ) phosphate crystallites enriched with calcium and potassium. These changes may contribute to the prolonged retention of cerium in lung tissue.