Mechanistic Insights Research Articles

Post-Translational Modifications of RNA-Modifying Proteins in Cellular Dynamics and Disease Progression.

RNA-modifying proteins, classified as "writers," "erasers," and "readers," dynamically modulate RNA by adding, removing, or interpreting chemical groups, thereby influencing RNA stability, functionality, and interactions. To date, over 170 distinct RNA chemical modifications and more than 100 RNA-modifying enzymes have been identified, with ongoing research expanding these numbers. Although significant progress has been made in understanding RNA modification, the regulatory mechanisms that govern RNA-modifying proteins themselves remain insufficiently explored. Post-translational modifications (PTMs) such as phosphorylation, ubiquitination, and acetylation are crucial in modulating the function and behavior of these proteins. However, the full extent of PTM influence on RNA-modifying proteins and their role in disease development remains to be fully elucidated. This review addresses these gaps by offering a comprehensive analysis of the roles PTMs play in regulating RNA-modifying proteins. Mechanistic insights are provided into how these modifications alter biological processes, contribute to cellular function, and drive disease progression. In addition, the current research landscape is examined, highlighting the therapeutic potential of targeting PTMs on RNA-modifying proteins for precision medicine. By advancing understanding of these regulatory networks, this review seeks to facilitate the development of more effective therapeutic strategies and inspire future research in the critical area of PTMs in RNA-modifying proteins.

Metal-Organic Frameworks for Sustainable Crop Disease Management: Current Applications, Mechanistic Insights, and Future Challenges.

Efficient management of crop diseases and yield enhancement are essential for addressing the increasing food demands due to global population growth. Metal-organic frameworks (MOFs), which have rapidly evolved throughout the 21st century, are notable for their vast surface area, porosity, and adaptability, establishing them as highly effective vehicles for controlled drug delivery. This review methodically categorizes common MOFs employed in crop disease management and details their effectiveness against various pathogens. Additionally, by critically evaluating existing research, it outlines strategic approaches for the design of drug-delivery MOFs and explains the mechanisms through which MOFs enhance disease resistance. Finally, this paper identifies the current challenges in MOF research for crop disease management and suggests directions for future research. Through this in-depth review, the paper seeks to enrich the understanding of MOFs applications in crop disease management and offers valuable insights for researchers and practitioners.

Structure of a Rhs effector clade domain provides mechanistic insights into type VI secretion system toxin delivery

The type VI secretion system (T6SS) is a molecular machine utilised by many Gram-negative bacteria to deliver antibacterial toxins into adjacent cells. Here we present the structure of Tse15, a T6SS Rhs effector from the nosocomial pathogen Acinetobacter baumannii. Tse15 forms a triple layered β-cocoon Rhs domain with an N-terminal α-helical clade domain and an unfolded C-terminal toxin domain inside the Rhs cage. Tse15 is cleaved into three domains, through independent auto-cleavage events involving aspartyl protease activity for toxin self-cleavage and a nucleophilic glutamic acid for N-terminal clade cleavage. Proteomic analyses identified that significantly more peptides from the N-terminal clade and toxin domains were secreted than from the Rhs cage, suggesting toxin delivery often occurs without the cage. We propose the clade domain acts as an internal chaperone to mediate toxin tethering to the T6SS machinery. Conservation of the clade domain in other Gram-negative bacteria suggests this may be a common mechanism for delivery.

Mechanistic Insights into Curvature Formation in Synthetic Vesicles

AbstractThe mimicking of natural lipid bilayers with synthetic amphiphilic systems is of great interest to researchers, as insights could lead to better understanding of the complexities of cell membranes, as well as new materials and healthcare technologies. Recapitulating natural lipid asymmetry across bilayer membranes has important implications for curvature in cell, vesicle, and organelle morphologies, but has been challenging to achieve with synthetic lipid combinations or standard amphiphilic block copolymers. In a recent article, Elizebath et al. report the synthesis of a new type of synthetic amphiphile able to induce asymmetry in an artificial bilayer membrane dynamically. The molecules were designed around an extended π‐conjugated hydrophobic core with tertiary amine‐terminated oxyalkylene side chains. Protonation of the tertiary amines on the bilayer exterior leads to curvature induction, bilayer fission, and vesicle formation as monitored by time‐resolved spectroscopy techniques and microscopy. The results were further validated with density functional theory (DFT) calculations. The delicate balance between different molecular scale interactions in the supramolecular structures led to the dynamic transformation of the bilayer membranes. Insights described could be used to advance the assembly of hierarchical life‐like materials.

Tandem Solid‐Solution Phase Post‐Synthetic Modification of Porous Molecular Crystals for In‐Situ Generation of Fluorophores

AbstractConventional synthetic methods of organic luminescent molecules often involve labor‐intensive solution‐phase organic synthesis, which violate the principles of atom‐economic transformation. Post‐synthetic modification (PSM) offers a promising alternative, allowing direct transformation from one fluorophore to another. Although PSM is commonly implemented in extended frameworks, its application in porous molecular crystals remains challenging. Herein, we focus on utilizing porous molecular crystals, specifically tetraphenylethylene‐cored frameworks, as versatile platforms for tandem PSM reactions to customize organic fluorophores. The tailored skeleton design ensures both the formation of porous structures and the occurrence of tandem solid‐solution phase reactions while maintaining the solid state of reactants and products in each step. The inherent non‐covalent bonding nature of the frameworks facilitates processing and characterization, offering unparalleled advantages for porous networks. The accompanying solid‐state fluorescence transition from green to blue and then to green (or yellow) enables real‐time monitoring of tandem reactions and provides intuitive mechanistic insights. This phenomenon is exploited for the facile construction of a dynamic information encryption system using fluorescent quick response codes.

BONCAT-iTRAQ Labelling Reveals Molecular Markers of Adaptive Responses in Toxoplasma gondii to Pyrimethamine Treatment.

We employed a BONCAT-iTRAQ labelling approach to investigate newly synthesised proteins (NSPs) in Toxoplasma gondii subjected to varying concentrations of the antifolate drug pyrimethamine. Our results reveal that numerous NSPs exhibited altered expression levels in response to the drug, with significant upregulation observed at higher concentrations. Key proteins involved in protein synthesis, stress responses, energy metabolism, and cytoskeletal dynamics were identified, indicating that T. gondii undergoes complex adaptive responses to pyrimethamine treatment. While some of the identified pathways reflect a generic stress response, this study provides important molecular markers and mechanistic insights specific to the parasite's adaptation strategies. These findings contribute to understanding how T. gondii modulates its proteome in response to drug-induced stress and lay the groundwork for further investigations into potential therapeutic targets.

Mechanistic Insights into Clinically Relevant Ribosome-Targeting Antibiotics

Antibiotics targeting the bacterial ribosome are essential to combating bacterial infections. These antibiotics bind to various sites on the ribosome, inhibiting different stages of protein synthesis. This review provides a comprehensive overview of the mechanisms of action of clinically relevant antibiotics that target the bacterial ribosome, including macrolides, lincosamides, oxazolidinones, aminoglycosides, tetracyclines, and chloramphenicol. The structural and functional details of antibiotic interactions with ribosomal RNA, including specific binding sites, interactions with rRNA nucleotides, and their effects on translation processes, are discussed. Focus is placed on the diversity of these mechanisms and their clinical implications in treating bacterial infections, particularly in the context of emerging resistance. Understanding these mechanisms is crucial for developing novel therapeutic agents capable of overcoming bacterial resistance.

Effects of Dynamic Surface Transformation on the Activity and Stability of Mixed Co‐Mn Cubic Spinel Oxides in the Oxygen Evolution Reaction in Alkaline Media

AbstractAn atomic‐scale understanding of how electrocatalyst surfaces reconstruct and transform during electrocatalytic reactions is essential for optimizing their activity and longevity. This is particularly important for the oxygen evolution reaction (OER), where dynamic and substantial structural and compositional changes occur during the reaction. Herein, a multimodal method is developed by combining X‐ray fine structure absorption and photoemission spectroscopy, transmission electron microscopy, and atom probe tomography with electrochemical measurements to interrogate the temporal evolution of oxidation states, atom coordination, structure, and composition on Co2MnO4 and CoMn2O4 cubic spinel nanoparticle surfaces upon OER cycling in alkaline media. Co2MnO4 is activated at the onset of OER due to the formation of ≈2 nm Co‐Mn oxyhydroxides with an optimal Co/Mn ratio of ≈3. As OER proceeds, Mn dissolution and redeposition occur for the CoMn oxyhydroxides, extending the OER stability of Co2MnO4. Such dynamic dissolution and redeposition are also observed for CoMn2O4, leading to the formation of less OER‐active Mn‐rich oxides on the nanoparticle surfaces. This study provides mechanistic insights into how dynamic surface reconstruction and transformation affect the activity and stability of mixed CoMn cubic spinels toward OER.

Investigating Full-Length circRNA Transcripts to Reveal circRNAMediated Regulation of Competing Endogenous RNAs in Gastric Cancer

Background: Circular RNAs (circRNAs) play important regulatory roles in the progression of gastric cancer (GC), but the exact mechanisms governing their regulation remain incompletely understood. Prior studies typically used back-spliced junctions (BSJs) to represent a range of circRNA isoforms, overlooking the prevalence of alternative splicing (AS) events within circRNAs, which could lead to unreliable or even incorrect conclusions in subsequent analyses, hindering our comprehension of the specific functions of circRNAs in GC. Objective: This study aimed to explore the potential functional roles of the dysregulated circRNA transcripts in GC and provide new biomarkers and effective novel therapeutic strategies for GC treatment. Methods: RNA-seq data with rRNA depletion and RNase R treatment was employed to characterize the expression profiles of circRNAs in GC, and RNA-seq data only with rRNA depletion was employed to identify differentially expressed mRNAs in GC. Based on the full-sequence information and accurate isoform-level quantification of circRNA transcripts calculated by the CircAST tool, we performed a series of bioinformatic analyses. A circRNA-miRNA-hub gene regulatory network was constructed to reveal the circRNA-mediated regulation of competing endogenous RNAs in GC, and then the protein-protein interaction (PPI) network was built to identify hub genes. Results: A total of 18,398 circular transcripts were successfully reconstructed in the samples. Herein, 351 upregulated and 177 downregulated circRNA transcripts were identified. Functional enrichment analysis revealed that their parental genes were strongly associated with GC. After several screening steps, 19 dysregulated circRNA transcripts, 40 related miRNAs, and 65 target genes (mRNAs) were selected to construct the ceRNA network. Through PPI analysis, five hub genes (COL5A2, PDGFRB, SPARC, COL1A2, and COL4A1) were excavated. All these hub genes may play vital roles in gastric cancer cell proliferation and invasion. Conclusion: Our study revealed a comprehensive profile of full-length circRNA transcripts in GC, which could provide potential prognostic biomarkers and targets for GC treatment. The results would be helpful for further studies on the biological roles of circRNAs in GC and offer new mechanistic insights into the pathogenesis of GC.

Super-enhancer-driven ZFP36L1 promotes PD-L1 expression in infiltrative gastric cancer

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. Despite the widespread recognition of tumor immunotherapy in treating unresectable GC, challenges, including ineffective immunotherapy and drug resistance, persist. Therefore, understanding the regulatory mechanisms of PD-L1, particularly in the context of super-enhancers (SEs) and zinc finger protein 36 ring finger protein-like 1 (ZFP36L1) RNA-binding protein, is crucial. In this study, we performed H3K27ac Cleavage Under Targets and Tagmentation (CUT&Tag) sequencing, investigated the heterogeneity of SEs between two GC subtypes with differential growth patterns, and revealed the immune escape signatures driven by ZFP36L1-SE in infiltrative GC through SEs inhibitors treatment. The regulation of ZFP36L1 to PD-L1 was evaluated by quantitative PCR, western blot, flow cytometry, and immunohistochemistry. Furthermore, we explored its regulatory mechanisms using a combination of molecular biology techniques, including luciferase reporter assay, GST/RNA pull-down, chromatin immunoprecipitation (ChIP)/RIP experiments, and in vivo functional assays. We demonstrated that ZFP36L1, driven by an SE, enhances IFN-γ-induced PD-L1 expression, with SPI1 identified as the specific transcription factor binding to ZFP36L1-SE. Mechanistically, ZFP36L1 binds to the adenylate uridylate-rich element in the 3ʹ untranslated region (3ʹUTR) of HDAC3 mRNA, exacerbating its mRNA decay, and thereby facilitating PD-L1 abnormal transcriptional activation. Collectively, our findings provide mechanistic insights into the role of the SPI1-ZFP36L1-HDAC3-PD-L1 signaling axis in orchestrating immune escape mechanisms in GC, thereby offering valuable insights into the potential targets for immune checkpoint therapy in GC management.

Molecular permeation through large pore channels: computational approaches and insights.

Computational methods such as molecular dynamics (MD) have illuminated how single-atom ions permeate membrane channels and how selectivity among them is achieved. Much less is understood about molecular permeation through eukaryotic channels that mediate the flux of small molecules (e.g. connexins, pannexins, LRRC8s, CALHMs). Here we describe computational methods that have been profitably employed to explore the movements of molecules through wide pores, revealing mechanistic insights, guiding experiments, and suggesting testable hypotheses. This review illustrates MD techniques such as voltage-driven flux, potential of mean force, and mean first-passage-time calculations, as applied to molecular permeation through wide pores. These techniques have enabled detailed and quantitative modeling of molecular interactions and movement of permeants at the atomic level. We highlight novel contributors to the transit of molecules through these wide pathways. In particular, the flexibility and anisotropic nature of permeant molecules, coupled with the dynamics of pore-lining residues, lead to bespoke permeation dynamics. As more eukaryotic large-pore channel structures and functional data become available, these insights and approaches will be important for understanding the physical principles underlying molecular permeation and as guides for experimental design.

Self-Inhibition Phenomena in Cu3Pt Oxidation by CO2.

This study investigates the oxidation behavior of Cu3Pt(100) in CO2 using a combination of ambient-pressure X-ray photoelectron spectroscopy, mass spectroscopy, and density functional theory modeling. Our in situ measurements reveal the simultaneous oxidation and reduction of Cu2O due to the opposing effects of atomic oxygen and CO generated from dissociative CO2 adsorption, leading to a dynamic equilibrium state of simultaneously occurring redox reactions. Complementary atomistic calculations elucidate the inhibitory effects of subsurface Pt enrichment and the counteracting roles of CO2 and CO in surface oxidation and reduction. These results provide mechanistic insights into the dissociative pathway of CO2 molecules and dynamic evolution of surface composition and reactivity of Cu-based alloy catalysts in CO2-rich environments, with broader implications for tuning gas-surface reactions by manipulating gas reactants or solid surface composition.

Super-enhancer-driven ZFP36L1 promotes PD-L1 expression in infiltrative gastric cancer.

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. Despite the widespread recognition of tumor immunotherapy in treating unresectable GC, challenges, including ineffective immunotherapy and drug resistance, persist. Therefore, understanding the regulatory mechanisms of PD-L1, particularly in the context of super-enhancers (SEs) and zinc finger protein 36 ring finger protein-like 1 (ZFP36L1) RNA-binding protein, is crucial. In this study, we performed H3K27ac Cleavage Under Targets and Tagmentation (CUT&Tag) sequencing, investigated the heterogeneity of SEs between two GC subtypes with differential growth patterns, and revealed the immune escape signatures driven by ZFP36L1-SE in infiltrative GC through SEs inhibitors treatment. The regulation of ZFP36L1 to PD-L1 was evaluated by quantitative PCR, western blot, flow cytometry, and immunohistochemistry. Furthermore, we explored its regulatory mechanisms using a combination of molecular biology techniques, including luciferase reporter assay, GST/RNA pull-down, chromatin immunoprecipitation (ChIP)/RIP experiments, and in vivo functional assays. We demonstrated that ZFP36L1, driven by an SE, enhances IFN-γ-induced PD-L1 expression, with SPI1 identified as the specific transcription factor binding to ZFP36L1-SE. Mechanistically, ZFP36L1 binds to the adenylate uridylate-rich element in the 3' untranslated region (3'UTR) of HDAC3 mRNA, exacerbating its mRNA decay, and thereby facilitating PD-L1 abnormal transcriptional activation. Collectively, our findings provide mechanistic insights into the role of the SPI1-ZFP36L1-HDAC3-PD-L1 signaling axis in orchestrating immune escape mechanisms in GC, thereby offering valuable insights into the potential targets for immune checkpoint therapy in GC management.

Contrastive Functional Connectivity Defines Neurophysiology-informed Symptom Dimensions in Major Depression.

Major depressive disorder (MDD) is a prevalent psychiatric disorder characterized by substantial clinical and neurobiological heterogeneity. Conventional studies that solely focus on clinical symptoms or neuroimaging metrics often fail to capture the intricate relationship between these modalities, limiting their ability to disentangle the complexity in MDD. Moreover, patient neuroimaging data typically contains normal sources of variance shared with healthy controls, which can obscure disorder-specific variance and complicate the delineation of disease heterogeneity. We employed contrastive principal component analysis to extract disorder-specific variations in fMRI-based resting-state functional connectivity (RSFC) by contrasting MDD patients (N=233) with age-matched healthy controls (N=285). We then applied sparse canonical correlation analysis to identify latent dimensions in the disorder variations by linking the extracted contrastive connectivity features to clinical symptoms in MDD patients. Two significant and generalizable dimensions linking distinct brain circuits and clinical profiles were discovered. The first dimension, associated with an apparent "internalizing-externalizing" symptom dimension, was characterized by self-connections within the visual network and also associated with choice reaction times of cognitive tasks. The second dimension, associated with personality facets such as extraversion and conscientiousness typically inversely associated with depression symptoms, is primarily driven by self-connections within the dorsal attention network. This "depression-protective personality" dimension is also associated with multiple cognitive task performances related to psychomotor slowing and cognitive control. Our contrastive RSFC-based dimensional approach offers a new avenue to dissect clinical heterogeneity underlying MDD. By identifying two stable, neurophysiology-informed symptom dimensions in MDD patients, our findings may enhance disease mechanism insights and facilitate precision phenotyping, thus advancing the development of targeted therapeutics for precision mental health.

Efficient photocatalytic degradation of microplastics by constructing a novel Z-scheme Fe-doped BiO2−x/BiOI heterojunction with full-spectrum response: Mechanistic insights and theory calculations

Recently, microplastics (MPs) have garnered significant attention as a challenging emerging pollutant to address. Here, a full-spectrum light-driven Fe-doping BiO2−x/BiOI (FBI) Z-scheme heterojunction was constructed for efficiently degrading MPs in waters. Compared with BiO2−x, Fe doping BiO2−x, and BiOI, the optimal photocatalyst (40-FBI) can cause deep cracks in the polyethylene terephthalate (PET) within 10 h under the irradiation of full-spectrum light. Meanwhile, FT-IR characterization revealed that the absorption peak intensities of the C-O group, CO group, -CH stretching vibration, and -OH group on the MPs surface gradually increased with degradation time. A series of experiments and theory calculations revealed that the introduction of Fe creates impurity levels, accelerating the separation of photo-generated carriers and reducing the work function of BiO2−x, thereby enhancing the transport of photo-generated carriers between Z-scheme heterojunctions. This study offers a valuable idea for designing an efficient photocatalyst by simultaneously introducing ion doping and constructing heterojunctions for enhancing MPs degradation.

Performance and mechanism insights into S-doped superhydrophilic carbon nitride for photocatalytic hydrogen evolution and degradation

Carbon nitride (CN) photocatalyst possesses great potential in alleviating energy and environmental crisis, while the insufficient active sites exposure, limited light harvest and poor charge behavior, as well as inferior dispersibility in water limit its photocatalytic activity. In this research, a loose porous crimp S doped CN photocatalyst with superhydrophilicity was tailored via facile one-pot thermal-melting followed thermal induce copolymerization of urea with 2-mercaptonicotinic acid. The dope of 2-mercaptonicotinic acid leads to the significant enhancement of specific surface area, range/intensity of visible-light harvest and charge behavior, as well as hydrophilicity of CN. The photocatalytic hydrogen evolution rate achieves a remarkable improvement of 7.61 times compared to CN alone, reaching 88.14 μmol h−1. Additionally, the photodegradation of tetracycline is enhanced by approximately 3.96 times compared to pristine CN, resulting in a degradation efficiency of 90.5 %. Via active species capture tests, ESR, LC-MS, toxicity prediction and DFT calculations, the main active species, degradation pathway, intermediates toxicity and promoted mechanism of photocatalytic performance are explored. This study presents a straightforward and cost-effective approach to enhance the intrinsic activity of CN-based photocatalysts by simultaneously regulating their active sites exposure, light absorption and charge behavior for addressing environmental and energy concerns.

Mechanistic insight of neurodegeneration due to micro/nano-plastic-induced gut dysbiosis.

Despite offering significant conveniences, plastic materials contribute substantially in developing environmental hazards and pollutants. Plastic trash that has not been adequately managed may eventually break down into fragments caused by human or ecological factors. Arguably, the crucial element for determining the biological toxicities of plastics are micro/nano-forms ofplastics (MPs/NPs), which infiltrate the mammalian tissue through different mediaand routes. Infiltration of MPs/NPs across the intestinal barrier leads to microbial architectural dysfunction, which further modulates the population of gastrointestinal microbes. Thereby, it triggers inflammatory mediators (e.g., IL-1α/β, TNF-α, and IFN-γ) by activating specific receptors located in the gut barrier. Mounting evidence indicates that MPs/NPs disrupt host pathophysiological function through modification of junctional proteins and effector cells. Moreover, the alteration of microbial diversity by MPs/NPs causes the breakdown of the blood-brain barrier and translocation of metabolites (e.g., SCFAs, LPS) through the vagus nerve. Potent penetration affects the neuronal networks, neuronal protein accumulation, acceleration of oxidative stress, and alteration of neurofibrillary tangles, and hinders distinctive communicatingpathways. Conclusively, alterations of these neurotoxic factors are possibly responsible forthe associated neurodegenerative disordersdue to the exposure of MPs/NPs. In this review, the hypothesis on MPs/NPs associated with gut microbial dysbiosis has been interlinked to the distinct neurological impairment through the gut-brain axis.

Integrated approach of machine learning, Mendelian randomization and experimental validation for biomarker discovery in diabetic nephropathy.

To identify potential biomarkers and explore the mechanisms underlying diabetic nephropathy (DN) by integrating machine learning, Mendelian randomization (MR) and experimental validation. Microarray and RNA-sequencing datasets (GSE47184, GSE96804, GSE104948, GSE104954, GSE142025 and GSE175759) were obtained from the Gene Expression Omnibus database. Differential expression analysis identified the differentially expressed genes (DEGs) between patients with DN and controls. Diverse machine learning algorithms, including least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest, were used to enhance gene selection accuracy and predictive power. We integrated summary-level data from genome-wide association studies on DN with expression quantitative trait loci data to identify genes with potential causal relationships to DN. The predictive performance of the biomarker gene was validated using receiver operating characteristic (ROC) curves. Gene set enrichment and correlation analyses were conducted to investigate potential mechanisms. Finally, the biomarker gene was validated using quantitative real-time polymerase chain reaction in clinical samples from patients with DN and controls. Based on identified 314 DEGs, seven characteristic genes with high predictive performance were identified using three integrated machine learning algorithms. MR analysis revealed 219 genes with significant causal effects on DN, ultimately identifying one co-expressed gene, carbonic anhydrase II (CA2), as a key biomarker for DN. The ROC curves demonstrated the excellent predictive performance of CA2, with area under the curve values consistently above 0.878 across all datasets. Additionally, our analysis indicated a significant association between CA2 and infiltrating immune cells in DN, providing potential mechanistic insights. This biomarker was validated using clinical samples, confirming the reliability of our findings in clinical practice. By integrating machine learning, MR and experimental validation, we successfully identified and validated CA2 as a promising biomarker for DN with excellent predictive performance. The biomarker may play a role in the pathogenesis and progression of DN via immune-related pathways. These findings provide important insights into the molecular mechanisms underlying DN and may inform the development of personalized treatment strategies for this disease.

Degradation Mechanism and Enhanced Stability of Organolithium for Chemical Lithiation

AbstractOrganolithium solutions, especially Li‐arene solutions (LASs) with high reactivity and controllable redox potentials, have gained significant attention because of their wide applications in chemical lithiation, liquid anodes, and battery recycling. However, the sudden loss of reactivity when stored or applied at room temperature is still puzzling and inhibits the application of LASs. In this work, the degradation mechanism of LASs is fully investigated and revealed by combining various experimental characterization and computational simulations. A hierarchical reaction mechanism for lithium biphenyl/2‐methyl tetrahydrofuran (Li‐Bp‐2MT), a lithiation solution used for most anodes, explains degradation and side product formation. Specifically, the dimerization of the active component Li1Bp[2MT]1 forms an inactive dimer that is irreversibly reduced in the presence of locally accumulated highly reductive Li0. This reaction mechanism reveals the atomic origins of lithiation solution deactivation and accounts for all solid and gaseous byproducts. LiH is identified as the dominating solid byproduct, indicating irreversible destruction of the active components and facilitating side reactions producing H2 and CH4. Based on reaction mechanism insights, modifying molecular interactions and reaction kinetics are experimentally shown to inhibit Li0 aggregation kinetics, enhancing long‐term prelithiation performance. This research provides comprehensive guidelines for practical applications of LASs.

Mechanistic insights into pore water conversion to gas hydrates in clay minerals

The conversion of pore water to gas hydrates is an important prerequisite for natural gas hydrates (NGHs) accumulation and hydrate-based CO2 sequestration. However, the mechanism of water-to-hydrate conversion in clays, which are prevalent in hydrate reservoirs or marine sediments serving as potential hosts for CO2 hydrates, still remains poorly understood, impeding further advancements in exploiting NGHs and developing CO2 sequestration strategies. In this paper, the characteristics of pore water conversion to hydrates in montmorillonite and kaolin were comprehensively examined through quantitative measurements and NMR analysis, and compared with those in silt and coarse sand. It revealed that the water-to-hydrate conversion was more restricted in clays than in sands. Especially in montmorillonite, since almost all pore water was detected as bound water, the final water conversion was extremely low and sensitive to the subcooling degree. Additionally, as the initial water content increased from 15 wt% to 35 wt%, the final water conversion in kaolin, silt, and coarse sand decreased exponentially due to intensified kinetic limitation, whereas that in montmorillonite initially rose and then fell, attaining the maximum at a threshold of 20 wt%. It is found that the competition between thermodynamic and kinetic limitations controls water-to-hydrate conversion in clays. Specifically, in kaolin, silt and coarse sand, the main controlling factor of water-to-hydrate conversion is the kinetic limitation, as their unconverted equilibrium water is negligible. However, in montmorillonite, the thermodynamic limitation dominates at low water contents, transitioning to kinetic limitation at high water contents. This study provides direct evidence and mechanistic insights into how clays affect water-to-hydrate conversion in porous media, which has significant implications for the geological accumulation of NGHs and the site selection for hydrate-based CO2 sequestration.