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Development of a High-Energy-Density Lithiated Silicon-Sulfur Full Cell with Enhanced Stability and Longevity
No full textSilicon-sulfur (Si-S) batteries represent a promising energy storage solution due to their high theoretical energy density. However, practical applications have been hindered by substantial volume expansion of silicon and the dissolution of sulfur species. Here, we combine a triazine-based graphdiyne-coated silicon (TzG@Si) anode and a sulfurized polyacrylonitrile (S@PAN) cathode into a cell that uniquely mitigates the volume expansion of silicon and prevents sulfur migration. Notably, the integration of TzG@Si and S@PAN results in the formation of a stable, LiF-rich solid-electrolyte interphase (SEI) on both electrodes, significantly enhancing the cycling stability. The optimized cell exhibits an energy density of 414.3 Wh kg-1 based on electrodes’ mass (Si anode and S@PAN cathode), with a capacity retention exceeding 80% after 400 cycles. Moreover, we explore the lithiation mechanisms within the S@PAN cathode, revealing that controlled voltage windows can further improve performance by preventing deep discharge. Our findings suggest that by engineering the electrodes, this Si-S battery system can achieve long cycle life and high energy density. This work not only advances the understanding of Si-S battery chemistry but also highlights the importance of synergistic electrode and electrolyte design in developing practical solutions for high-energy-density batteries
Unified, Biosynthesis-Inspired, Completely Stereocontrolled Total Synthesis of All Highest-Order [n+1] Oligocyclotryptamine Alkaloids
No full textWe describe the unified enantioselective total synthesis of the polycyclotryptamine natural products (+)-quadrigemine H, (+)-isopsychotridine C, (+)-oleoidine, and (+)-caledonine. Inspired by our hypothesis for the biogenesis of these alkaloids via an iterative concatenative addition of homochiral cyclotryptamines to a meso-chimonanthine headcap, we leverage the modular, diazene-directed assembly of stereodefined cyclotryptamines to introduce successive C3a−C7\u27 quaternary stereocenters on a heterodimeric meso-chimonanthine surrogate with full stereochemical control at each quaternary linkage. We developed a new strategy for iterative aryl-alkyl diazene synthesis using increasingly complex oligomeric hydrazide nucleophiles and a bifunctional cyclotryptamine bearing a C3a leaving group and a pendant C7 pronucleophile. The utility of this strategy is demonstrated by the first total synthesis of heptamer (+)-caledonine and hexamer (+)-oleoidine. Enabled by our completely stereoselective total syntheses and expanded characterization data sets, we provide the first complete stereochemical assignment of pentamer (+)-isopsychotridine C, provide evidence that it is identical to the alkaloid known as (+)-isopsychotridine B, and report that tetramer (+)-quadrigemine H is identical to the alkaloid called (+)-quadrigemine I, resolving longstanding questions about the structures of the highest-order [n+1] oligocyclotryotamine alkaloids
Chiral Triazole-substituted Iodonium Salts in Enantioselective Halogen Bond Catalysis
No full textHerein, we present the synthesis of chiral triazole-based diaryliodonium salts and their
application as monodentate asymmetric iodine(III) derivates in halogen bond (XB) catalyzed
reactions. These potential Lewis acids were successfully benchmarked in the vinylogous
Mannich reaction of cyanomethyl coumarin with isatin-derived ketimine to obtain the addition
product in up to 99% yield and >99:1 e.r. Furthermore, these halogen bond catalysts allowed
an efficient functionalization of ketimines with various alcohols toward N,O-acetals in up to 99%
yield and 90:10 e.r. Additionally, we studied the origin of the enantioselectivity based on Density
Functional Theory (DFT) and the catalyst crystal structure. These unveiled the first approach
of asymmetric induction facilitated by using σ-hole stabilized chiral moieties in iodine(III)-based
catalysts and exclusively predicated upon XB activation
Advancing Catalysis Research through FAIR Data Principles Implemented in a Local Data Infrastructure - A Case Study of an Automated Test Reactor
No full textFindable, Accessible, Interoperable, and Reusable (FAIR) data is currently emerging as an indispensable element in the advancement of science and requires the development of new methods for data acquisition, storage and sharing. This is becoming even more critical as the increasing application of artificial intelligence demands significantly higher data quality in terms of reliability, reproducibility and consistency of datasets. This paper presents methods for the digital and automatic acquisition and storage of data and metadata in catalysis experiments based on open-source software solutions. The successful implementation of a digitalization concept, which includes working according to machine-readable standardized operating procedures (SOPs) is outlined using a reactor for catalytic tests that has been automated with the open-source software tool EPICS (Experimental Physics and Industrial Control System). The process of data acquisition, standardized analysis, upload to a database and generation of relationships between database entries is fully automated. Application programming interfaces (APIs) have been developed to enable data exchange within the local data infrastructure and beyond to overarching repositories, paving the way for autonomous catalyst discovery and machine learning applications
Machine Learning Strategies for Forecasting Discharge Capacity in Lithium-Ion Batteries with NCM Layered Cathode Material
No full textThe nuanced grasp of determinants impacting discharge capacity stands as an imperative linchpin for propelling the evolution of lithium-ion batteries to new frontiers. We have curated a dataset comprising data from 147 sets of lithium-ion battery cathodes, scrupulously extracted from pertinent literature. Initially, the relationships between variables were visually depicted through Pearson correlation coefficient plots. Subsequently, six models were employed for data prediction. Notably, the gradient boosting model exhibited superior performance, yielding minimal root mean square errors for initial discharge capacity and post-cycling discharge capacity at 12.58 mAh∙g-1 and 15.00 mAh∙g-1, respectively. Subsequently, we conducted an analysis of feature importance and Shapley additive explanations (SHAP) plots to identify the primary factors influencing both initial discharge capacity and discharge capacity after cycling. Among them, for the IC, the highest importance scores are assigned to current density and maximum cyclic voltage, standing at 0.225 and 0.154, respectively. This implies that, compared to other descriptors, current density and maximum cyclic voltage exert a more substantial influence on the GBM model. In the case of the EC, the importance score for the IC significantly surpasses others, reaching 0.353, showcasing a heightened level of contribution to the model. This analysis offers valuable insights guiding the subsequent exploration of conditions impacting discharge efficiency in Li[NixCoyMn1–x–y]O2 (NCM) cathode materials
Non-Markovian Dynamic Models Identify Non-Canonical KRAS-VHL Encounter Complex Conformations for Novel PROTAC Design
No full textTargeted protein degradation (TPD) is emerging as a promising therapeutic approach for cancer and other diseases, with an increasing number of programs demonstrating its efficacy in human clinical trials. One notable method for TPD is Proteolysis Targeting Chimeras (PROTACs, or heterobifunctional degraders) that selectively degrade a protein of interest (POI) through E3-ligase induced ubiquitination followed by proteasomal degradation. PROTACs utilize a warhead-linker-ligand architecture to bring the POI (bound to the warhead) and the E3 ligase (bound to the ligand) into close proximity. The resulting non-native protein-protein interactions (PPIs) formed between the POI and E3 ligase lead to the formation of a stable POI-degrader-ligase ternary complex, enhancing cooperativity for TPD. A significant challenge in PROTAC design is the time-consuming and resource-intensive screening of the degrader linkers to induce favorable non-native PPIs between POI and E3 ligase. In this work, we present a physics-based computational protocol to systematically predict non-canonical and metastable PPI interfaces between an E3 ligase and a given POI, aiding in the design of linkers to stabilize the PROTAC ternary complex and enhance degradation. In our protocol, we build the non-Markovian dynamic model using the Integrative Generalized Master Equation (IGME) method from approximately 1.5 millisecond all-atom molecular dynamics (MD) simulations of linker-less encounter complex, to systematically explore the inherent PPIs between the oncogene homologue (KRAS) protein and the von Hippel-Lindau (VHL) E3 ligase. Our IGME model successfully revealed six metastable states each containing a different PPI interface. We selected three of these metastable states containing promising PPIs for linker design. Our selection criterion included the thermodynamic and kinetic stabilities of these PPIs and the accessibility of the linker to the solvent-exposed sites on the warheads and the E3 ligand. One of our selected PPIs closely matches a recent co-crystal PPI interface structure induced by an experimentally designed PROTAC with potent degradation efficacy. We anticipate that our IGME approach has significant potential for widespread application in predicting metastable POI-ligase encounter complex interfaces that can enable subsequent rational design of novel PROTACs
Ion- Exchange of Zeolitic Brønsted Acid Sites with Metal Cations Influences the Hydrocarbon Pools (HCP) during Tandem CO2 Hydrogenation
No full textWe demonstrate that the exchange of zeolitic Brønsted acid sites (BAS) with cations from metal-oxides plays a pivotal role in the propagation of hydrocarbon pools (HCP) during CO2 hydrogenation. We estimated the likelihood of cationic species migration from different oxides-In2O3, ZnZrOx, Cr2O3 and their exchange with BAS by computing metal vacancy formation energies. Accordingly, we integrated metal-oxides and SAPO-34 at nanoscale proximity (~1400 nm), to probe the propensity of the cations to exchange with BAS. To assess the influence of ion-exchange on HCP, we measured propylene-to-ethylene (indicates relative propagation of olefin-to-aromatic cycles) and paraffin-to-olefins ratios, which revealed that Inδ+ species inhibited HCP propagation, Znδ+ species enhanced hydrogen transfer, and Crδ+ species did not influence HCP. Combining reactivity data with ammonia temperature programmed desorption, occluded hydrocarbon analysis, 13C solid-state nuclear magnetic resonance (ssNMR) and X-ray photoelectron spectroscopy analysis (XPS), we provide insights into the influence of ion-exchanged species on HCP for rational integration of bifunctional catalysts
Towards Efficient and Unified Treatment of Static and Dynamic Correlations in Generalized Kohn-Sham Density Functional Theory
No full textAccurate description of the static correlation poses a persistent challenge for electronic structure theory, particularly when it has to be concurrently considered with the dynamic correlation. We develop here a ground breaking method in the generalized Kohn-Sham density functional theory (DFT) framework, named R-xDH7-SCC15, which achieves an unprecedented accuracy in capturing the static correlation, while maintaining a good description of the dynamic correlation on par with the state-of-the-art DFT and wave function theory methods, all grounded in the same single-reference black-box methodology. Central to R-xDH7-SCC15 is a novel, general-purpose static correlation correction (SCC) model applied to the renormalized XYG3-type doubly hybrid method (R-xDH7). The SCC model development pioneers a hybrid machine learning strategy that ingeniously harmonizing symbolic regression with nonlinear parameter optimization, to strike a balance between enhanced generalization capability, rigorous numerical accuracy, and retained interpretability of the SCC model. Extensive benchmark studies confirm the robustness and broad applicability of R-xDH7-SCC15 across a diverse array of chemical scenarios. Notably, it displays exceptional aptitude in accurately characterizing intricate reaction kinetics and dynamic processes in regions distant from equilibrium, where the influence of static correlation is most profound. Its capability to consistently and efficiently predict energy profiles, activation barriers, and reaction pathways within a user-friendly “black-box” framework, signifies a paradigm shift in our ability to model and comprehend complex chemical transformations, thereby marking a significant stride in the field of electronic-structure theory
Role of Kinetic Exchange and Coulomb Interaction in Bonding of Hydrogen Molecular Systems and Excited States
No full textWe present a detailed investigation of the electronic structure and bonding characteristics of hydrogen-based molecular systems (\ch{H2+}, \ch{H2}, \ch{H2-}) using the Exact Diagonalization Ab Initio (EDABI) approach within the framework of combined first- and second-quantization. By analyzing the relative contributions of kinetic exchange and effective Coulomb interactions, we provide a comprehensive understanding of covalency, atomicity, and ionicity as a function of interatomic distances. Our approach leverages exact solutions of the extended Heitler-London model to quantify these interactions, extending the analysis to the discussion of properties of excited states and the dissociation limit to these molecules. The findings reveal significant differences in bonding characteristics, particularly highlighting the stability and bonding nature of the neutral \ch{H2} molecule compared to its ionic counterparts. This study not only enhances an understanding of molecular interactions in hydrogen systems but also demonstrates the potential of the EDABI approach in developing more accurate computational models in quantum chemistry
Quantitative Reactivity Models for Oxidative Addition to L2Pd(0): Additional Substrate Classes, Solvents, and Mechanistic Insights
No full textQuantitative molecular structure-reactivity models are useful for generating predictions to guide synthesis design, and in formulating and testing mechanistic hypotheses. We report an expanded multivariate linear regression (MLR) model for the rate of (hetero)aryl (pseudo)halide oxidative addition to L2Pd(0), here exemplified by Pd(PCy3)2. This builds on a prior model from our group, with additional substrate classes (aryl chlorides and iodides) and reaction solvents (THF, toluene, THF/DMF mixture). Overall solvent effects across the entire substrate set are minimal under these conditions, enabling a unified MLR model without introduction of new molecular descriptors beyond the original five. Examining the mechanistic origin of the two molecular electrostatic potential (ESP) descriptors led to generation of a simpler, four descriptor model that is suitable for aryl halides, but not for 2-halopyridines. Using this model we identified a mechanistic outlier, 2-pyridyl triflate, which undergoes a nucleophilic displacement oxidative addition that does not involve the adjacent nitrogen atom. Finally, we discuss the relationship between C–X bond strength and oxidative addition rates, and compare the intrinsic bond strength index (IBSI) to bond dissociation enthalpy (BDE) as a bond strength descriptor