Atomic Charges Research Articles

Accurate protein-ligand binding free energy estimation using QM/MM on multi-conformers predicted from classical mining minima

Accurate prediction of binding free energy is crucial for the rational design of drug candidates and understanding protein-ligand interactions. To address this, we have developed four protocols that combine QM/MM calculations and the mining minima (M2) method, tested on 9 targets and 203 ligands. Our protocols carry out free energy processing with or without conformational search on the selected conformers obtained from M2 calculations, where their force field atomic charge parameters are substituted with those obtained from a QM/MM calculation. The method achieved a high Pearson’s correlation coefficient (0.81) with experimental binding free energies across diverse targets, demonstrating its generality. Using a differential evolution algorithm with a universal scaling factor of 0.2, we achieved a low mean absolute error of 0.60 kcal mol-1. This performance surpasses many existing methods and is comparable to popular relative binding free energy techniques but at significantly lower computational cost.

Structural characterisation of a cyanomesogen by X-ray diffraction and computational methods

The work reports the structural analysis of a cyanomesogen namely, p-cyanobenzylidene p-nonyloxyaniline belonging to the Schiff base class of compounds. It exhibits a partial bilayer/inter-digitated smectic Ad phase and a nematic phase. Polarising Optical Microscopy (POM) and Differential Scanning Calorimetry (DSC) studies have been carried out to study phase sequence and transition temperatures. Micro-structural parameters, like molecular length, spacing, crystallite size, activation energy and micro-strain, have been estimated and pair correlation function (PCF) studies have been done for exhibited mesophases using the X-ray diffraction technique. The study investigated the surface, electronic and optical properties of a compound by computational studies like Density Functional Theory (DFT) and Hirshfeld surface analysis (HSA) methods using the DFT B3LYP/6-311++G(d,p) level basis set. The results reveal that the polarity associated with the polar groups and alkoxy chain lengths, contributes majorly to the mesomorphic characteristics and stability. The Highest Occupied Molecular Orbitals (HOMO) and Lowest Unoccupied Molecular Orbitals (LUMO) analyses of the DFT optimised molecule give electronic and geometrical parameters, atomic charge distribution, polarisability factors which are used to interpret the characteristics of the mesophases and their suitability for electro-optical and non-linear optical applications of the compound in terms of the predicted data.

Exploring the Physical Properties of LiBeX (X = Sb, Bi) Compounds via Ab Initio Approach

In the current study, it is aimed to scrutinize the physical properties of LiBeX (X = Sb, Bi) compounds in detail. Density‐functional‐theory‐based WIEN2k and the Vienna Ab initio Simulation Package, employing the generalized gradient approximation of Perdew–Burke–Ernzerhof, Wu–Cohen, and Tran–Blaha‐modified Becke–Johnson (TB‐mBJ) exchange‐correlation schemes, are utilized to better validate the outcomes. The compounds exhibit energetic, lattice dynamic, and mechanical stability. Electronic structure calculations using the TB‐mBJ functional reveal indirect bandgaps of 1.007 eV for LiBeSb and 0.789 eV for LiBeBi compounds, respectively. The partial charge distribution in the highest occupied molecular orbital and the lowest unoccupied molecular orbital discloses maximum charge localization around the X site. The examination of the crystal orbital Hamilton population reveals the strongest BeX bonding interactions among the bonding pairs. The physio‐mechanical properties indicate brittle and mechanically anisotropic behavior of both compounds, with covalent bonding characteristics. The comparative analysis suggests that the TB‐mBJ potential is suitable for bandgap calculations due to its close alignment with experimental results. Additionally, the optimized results for these compounds indicate their potential for use in optoelectronic devices, such as visible to ultraviolet sensors and photovoltaics. The determined properties are consistent with previous theoretical findings.

Highly Polarization‐Sensitive Solar‐Blind Ultraviolet Photodetection Based on 1D Rb2CuCl3 Microwires

AbstractPolarization‐sensitive solar‐blind ultraviolet (UV) photodetectors are essential in both civilian and military applications. 1D perovskites derivative Rb2CuCl3 holds promise for polarization‐sensitive solar‐blind UV photodetectors due to its wide direct bandgap, anisotropic crystal structure, and long carrier lifetime. However, no studies on the polarization properties of Rb2CuCl3 are reported. Here, the electronic structural anisotropy of Rb2CuCl3 is confirmed by calculating the partial charge density distribution in the ac‐plane and bc‐plane. Then, the Raman‐active modes and corresponding atomic vibration modes are explored within the bc‐plane through joint experimental and theoretical Raman spectroscopy. Besides, angle‐resolved Raman, photoluminescence, and absorption spectroscopy reveal the intriguing anisotropic photoelectric characteristics of Rb2CuCl3 microwires (MWs). By using single Rb2CuCl3 MW as the photoactive layer, a polarization‐sensitive solar‐blind UV photodetector is fabricated, showing high photoresponsivity of 78 mA W−1 and photocurrent anisotropy ratio of ≈1.7 at 265 nm. Importantly, the proposed photodetectors without encapsulation exhibit excellent stability in ambient air, retaining the original photocurrent after two months, showcasing practical applicability. This study underscores the promise of Rb2CuCl3 for high‐performance polarization‐sensitive solar‐blind UV photodetectors, contributing valuable insights into its electronic structure, photoelectric properties, and practical applicability.

Predictive pretrained transformer (PPT) for real-time battery health diagnostics

Modeling and forecasting the evolution of battery systems involve complex interactions across physical, chemical, and electrochemical processes, influenced by diverse usage demands and dynamic operational patterns. In this study, we developed a predictive pre-trained Transformer (PPT) model equipped with 1,871,114 parameters that enhance identification of both short-term and long-term patterns in time-series data. This is achieved through the integration of convolutional layers and probabilistic sparse self-attention mechanisms, which collectively enhance prediction accuracy and efficiency in diagnosing battery health. Moreover, the customized hybrid-model fusion supports parallel computing and employs transfer learning, reducing computational costs while enhancing scalability and adaptability. Consequently, this allows for precise real-time health estimations across various battery cycles. We validated this method using a public dataset of 203 commercial lithium iron phosphate (LFP)/graphite batteries charged at rates ranging from 1C to 8C. By using only partial charge data—from an 80 % state of charge to the maximum charging voltage (3.6 V for LFP batteries, 4.2 V for ternary batteries)—and avoiding complex feature engineering, error metrics were achieved below 0.3 % for root mean square error (RMSE), weighted mean absolute percentage error (WMAPE), and mean absolute error (MAE), with an R2 of 98.9 %. The generalization capabilities were further demonstrated across 36 different testing protocols, encompassing 23,480 cycles throughout the entire life cycle, with a total inference time of 9.88 s during the testing phases. Further experiments on 30 nickel cobalt aluminum (NCA) batteries and 36 nickel cobalt manganese (NCM) batteries, across different battery types and operational scenarios, resulted in RMSE, WMAPE, and MAE all below 0.9 %, with R2 values of 94.1 % and 94.4 %, respectively. These findings highlight the potential of our customized deep transfer neural networks to enhance diagnostic accuracy, accelerate training, and improve generalization in real-time applications.

Catalytic behavior, electronic structure and spectroscopic (FT-IR, Raman, UV–vis) properties for the new ionic liquid imidazolium hydrogen sulfate

Catalytic performance, chemical reactivity, vibrational modes and electronic transitions of the ion pair [H–Im]+[HSO4]– were investigated in the current paper. Hence, a combined experimental (Hammett acidity function, infrared, Raman and ultraviolet-visible spectroscopies) and theoretical (molecular electrostatic potential surface, reduced density gradient, frontier molecular orbital analysis, quantum theory of atoms in molecules, net atomic charges, global and local reactivity descriptors) study was conducted. In terms of the catalytic performance, the acetic acid esterification with butanol was evaluated. Important kinetic (rate constant, activation energy, pre-exponential factor) and thermodynamic (enthalpy, entropy, Gibbs free energy barrier) factors for ester production as a function of the temperature and catalyst loading have been determined. Results revealed intensive electron density distribution in [H–Im]+[HSO4]– due to chemical interactions between the cationic and anionic moieties. These bonds were established as electrostatic in nature. The pronounced charge transfers within [H–Im]+[HSO4]– managed the title compound acidity (H0) and its catalytic behavior towards butyl acetate synthesis. Using the thermodynamic and kinetic measurements, a mechanism for acetic acid esterification with butanol in the presence of imidazolium hydrogen sulfate ionic liquid was offered.

Effect of three-body interaction on structural features of phosphate glasses from molecular dynamics simulations.

Understanding the structures of phosphate glasses is important to many of their technological applications. Molecular dynamics simulations are commonly used to generate structure models of sodium phosphate glasses, and those with partial charge pairwise potentials have been successfully applied for modeling other network glasses, such as silicate and aluminosilicate glasses. In this work, we show that the addition of a three-body term is essential in regulating the intertetrahedral bond angles, as well as Qn speciation in comparison to experiments. Simulation results with and without three-body terms were compared and validated with experimental results, including neutron structure factors. Further comparison with glass structures fully relaxed with first-principles density functional theory was performed to evaluate the simulation results. The results show that the addition of three-body terms is vital for the modeling of phosphate glasses, and it can significantly improve the description of short- and medium-range structures and properties.

Investigating the Role of Anions in the Adsorption of Pyrrolidinium Based Ionic Liquids on Pt(111) Surface Using Density Functional Theory

ABSTRACTThe adsorption properties of ionic liquids containing pyrrolidinium cations and various inorganic anions as electrolytes on a platinum surface were analyzed using first principle density functional theory. Three different orientations of the alkyl cation chain were observed during the adsorption process. The strength and structural stability varied between non‐fluorinated and fluorinated anions upon adsorption, with oxygen atoms influencing the mechanism of adsorption and driving the structural stability of the anion, while fluorine atoms played a role in determining the orientation of the cation during adsorption. Net atomic charges analysis, electron density difference methods, and electron density accumulation for this complex system were utilized to further investigate these phenomena. The results of this study provide valuable insights into the role of anions in the adsorption behavior of pyrrolidinium‐based ionic liquids on platinum surfaces, shedding light on the factors that influence their adsorption properties and structural stability on a molecular level. The findings of this study contribute to a better understanding of the interplay between anions and platinum surfaces in the adsorption of pyrrolidinium based ionic liquids, which can have implications for various applications such as electrochemistry, catalysis, and energy storage.

Mechanisms for forming methylglyoxal complexes with benzene and ethanol molecules. Nonempirical calculations

The formation mechanism of methylglyoxal monomers, dimers, trimers, methylglyoxal+benzene, and methylglyoxal+ethanol complexes was investigated using the density functional theory (DFT) approach and the B3LYP/6-311++G(d, p) functional set. Methylglyoxal has two C=O stretching vibrations, and in solvents, the intensity of the first C=O vibration band increased sharply, and the intensity of the second C=O vibration band decreased. This is due to the C=O···H hydrogen bond formed between methylglyoxal+benzene/ethanol solvents. Also, the calculations showed that among the molecules of methyglyoxal+benzene/ethanol mainly weak interactions, i.e. Van der Waals interactions, play a dominant role. Calculations are shown the complex formation energy increases as the number of molecules increases, but the average hydrogen bond energy corresponding to each bond remains unchanged. Also, the DFT method was used to study molecular structure, quantum chemical parameters such as Mulliken atomic charge distribution, atoms in molecules (AIM), reduced density gradient (RDG) and noncovalent interaction (NCI), electron localization functions (ELF), and localized orbital locator (LOL).

Parameterization of a Fluctuating Charge Model for Complexes Containing 3d Transition Metals.

Metalloproteins widely exist in biology, playing pivotal roles in diverse life processes. Meanwhile, molecular dynamics (MD) simulations based on classical force fields has emerged as an important tool in scientific research. Partial charges are critical parameters within classical force fields and usually derived from quantum mechanical (QM) calculations. However, QM calculations are often time-consuming and prone to basis set dependence. Alternatively, fluctuating charge (FQ) models offer another avenue for partial charge derivation, which has significant speed advantages and can be used for large-scale screening. Building upon our previous work, which introduced an FQ model for zinc-containing complexes, herein we extend this model to include additional 3d transition metals which are important to the life sciences, namely chromium, manganese, iron, cobalt, and nickel. Employing CM5 charges as target for parametrization, our FQ model accurately reproduces partial charges for 3d metal complexes featuring biologically relevant ligands. Furthermore, by using atomic charges derived by our FQ model, MD simulations have been performed. These charges showed excellent performance in simulating proteomic metal sites housing multiple metal ions, specifically, a metalloprotein containing an iron-sulfur cluster and another containing a dimanganese metal site, showcasing comparable performance to those of RESP charges. We anticipate that our study can accelerate the parametrization of atomic charges for metalloproteins featuring 3d transition metals, thereby facilitating simulations of relevant systems.

Cheminformatics-driven prediction of BACE-1 inhibitors: Affinity and molecular mechanism exploration

The β-secretase, sometimes referred to as BACE1 or Asp2, is the enzyme responsible for initiating the production of Aβ by breaking down the amyloid precursor protein. Hence, BACE is a pivotal target for pharmacological intervention aimed at diminishing the production of Aβ in Alzheimer's disease (AD). We did a quantitative structure-activity relationship (QSAR) study on 1235 compounds that had been experimentally reported as BACE-1 inhibitors (Ki) to find the target molecule and structural patterns linked to blocking the BACE-1 receptor. The OECD-recommended genetic algorithm-multiple linear regression (GA-MLR) QSAR model strikes a good balance between being able to make accurate predictions and understanding how things work. It achieves high values for many evaluation metrics, including R2tr = 0.8047, Q2LMO = 0.802, R2ex = 0.805, CCCex = 0.891, Q2-F1=0.801, Q2-F2=0.799, and Q2-F3=0.815. The mechanistic interpretation of QSAR has identified some nitrogen atoms that are required to block beta-secretase and make it less effective at doing its job. A positively charged aromatic carbon atom has a more significant impact on beta-secretase-1 inhibition. The docking study showed that the catalytic dye residues Asp32 and Asp228 become protonated when compound 27 is present, but they stay unprotonated when compound 27 is not present. These rings of pyrazine and pyridine interact hydrophobically with Tyr71 and Ile118 residues, confirming the pharmacophoric features seen in the QSAR data. We examined the stability of both the protein-ligand complex and the apo-protein. The apoprotein had an average gyration radius of 22.13, whereas the protein-ligand complex had an average gyration radius of 22.91. No changes were made to the results from the molecular docking, molecular dynamics (MD) simulation, MMGBSA (Molecular Mechanics Generalized Born Surface Area), or DFT analyses. Therefore, the current work could effectively contribute to the future development of BACE inhibitors in medication design.

Theoretical exploration of binary mixtures derived from hydrogen bond liquid crystalline soft materials for optical device fabrication

Binary mixtures are obtained from 4-Nitrobenzaldehyde (NBA), 4-(heptyloxy)benzoic acid (7OBA) and 4-(octyloxy)benzoic acid (8OBA) abbreviated as NBA + 7OBA and NBA + 8OBA. Density Functional Theory (DFT) is used to optimize the resultant molecular structures. HOMO–LUMO and NBO analysis are adapted in obtaining the charge transfer phenomenon of the binaries. Molecular electrostatic Potential (MEP) analysis reveals the active sites of liquid crystals. Atomic charge distribution of the binary mixture is investigated theoretically. Topological analysis is carried out to understand the intermolecular interaction between non mesogenic NBA and mesogenic precursors along with nonlinear optical properties. The results obtained are correlated with the experimental data obtained.

Non-covalent interactions and charge transfer in the CO activation by low-valent group 14 complexes.

The CO activation by low-valent group 14 catalysts encompasses the rupture of varied covalent bonds in a single transition state through a concerted pathway. The bond between the central main group atom and the hydride in the complex is elongated to trigger the formation of the C-H bond with CO accompanied by the concomitant formation of the E-O bond between the complex and CO to lead the corresponding formate product. Prior studies have established that besides the apolar nature of CO , its initial interaction with the complex is primarily governed by electrostatic interactions. Notably, other stabilizing interactions and the transfer of charge between catalysts and CO during the initial phases of the reaction have been ignored. In this study, we have quantified the non-covalent interactions and charge transfer that facilitate the activation of CO by group 14 main group complex. Our findings indicate that electrostatic interactions predominantly stabilize the complex and CO in the reactant region. However, induction energy becomes the main stabilizing force as the reaction progresses towards the transition state, surpassing electrostatics. Induction contributes about 50% to the stabilization at the transition state, followed by electrostatics (40%) and dispersion interactions (10%). Atomic charges calculated with the minimal basis iterative stockholder (MBIS) method reveal larger charge transfer for the back-side reaction path in which CO approaches the catalysts in contrast to the front-side approach. Notably, it was discovered that a minor initial bending of CO to approximately initiates the charge transfer process for all systems. Furthermore, our investigation of group 14 elements demonstrates a systematic reduction in both activation energies and charge transfer to CO while descending in group 14. All studied reactions were characterized along the reaction coordinate obtained with the intrinsic reaction coordinate (IRC) methodology at the M06-2X/6-31g(d,p) level of theory. Gibbs free energy in toluene was computed using electronic energies at the DLPNO-CCSD(T)/cc-pVTZ-SSD(E) level of theory. Vibrational and translational entropy corrections were applied to provide a more accurate description of the obtained Gibbs free energies. To better characterize the changes in the reaction coordinate for all reactions, the reaction force analysis (RFA) has been employed. It enables the partition of the reaction coordinate into the reactant, transition state, and product regions where different stages of the mechanism occur. A detailed characterization of the main non-covalent driving forces in the initial stages of the activation of CO by low-valent group 14 complexes was performed using symmetry-adapted perturbation theory (SAPT). The SAPT0-CT/def2-SVP method was employed for these computations. Charge transfer descriptors based on atomic population using the MBIS scheme were also obtained to complement the SAPT analyses.

The Quality of Embedding Charges Is Critical for Convergence of Many-Body Expansions When BSSE Is Absent.

There is conflicting evidence in the literature concerning the benefits of charge embedding on the convergence of many-body expansions (MBEs). Using a systematic series of water and ion-water clusters of varying size, this study indicates that the effects of charge embedding can be masked by basis set superposition error (BSSE). When BSSE is removed, this study demonstrates that charge embedding can significantly accelerate MBE convergence, where the electrostatically embedded two-body method, EE-MBE(2), can often yield accuracy close to the four-body method, MBE(4). Contrary to previous studies on smaller systems, this work shows that the performance of EE-MBE is highly sensitive to the charge model, with the best performance obtained when the natural population analysis (NPA) charge model is used and generated at the same level of theory used in the subsystem and supersystem calculations. It was demonstrated that the "3c" composite method, PBEh-3c, yields NPA atomic charges that are in excellent agreement with those obtained from supersystem density functional theory calculations. The linear-scaling X-Polarization method provides a more general approach to estimating these supersystem QM atomic charges, but its performance depends on how the fragments are defined.

Electrostatic Preorganization in Three Distinct Heterogeneous Proteasome β-Subunits.

The origin of the enzyme's powerful role in accelerating chemical reactions is one of the most critical and still widely discussed questions. It is already accepted that enzymes impose an electrostatic field onto their substrates by adopting complex three-dimensional structures; therefore, the preorganization of electric fields inside protein active sites has been proposed as a crucial contributor to catalytic mechanisms and rate constant enhancement. In this work, we focus on three catalytically active β-subunits of 20S proteasomes with low sequence identity (∼30%) whose active sites, although situated in an electrostatically miscellaneous environment, catalyze the same chemical reaction with similar catalytic efficiency. Our in silico experiments reproduce the experimentally observed equivalent reactivity of the three sites and show that obliteration of the electrostatic potential in all active sites would deprive the enzymes of their catalytic power by slowing down the chemical process by a factor of 1035. To regain enzymatic efficiency, besides catalytic Thr1 and Lys33 residues, the presence of aspartic acid in position 17 and an aqueous solvent is required, proving that the electrostatic potential generated by the remaining residues is insignificant for catalysis. Moreover, it was found that the gradual decay of atomic charges on Asp17 strongly correlates with the enzyme's catalytic rate deterioration as well as with a change in the charge distributions due to introduced mutations. The computational procedure used and described here may help identify key residues for catalysis in other biomolecular systems and consequently may contribute to the process of designing enzyme-like synthetic catalysts.

Resonance Effects from Substituents on L-Type Ligands Mediate Synthetic Control of Gold Nanocluster Frontier Orbital Energies.

The ligands of metal nanoclusters can be used to control their properties and reactivity, but a framework guiding their use remains elusive. Hammett studies of Au8(PPh3)72+ and Au9(PPh3)83+ nanoclusters with para- and meta-methyl and -methoxy groups indicate that resonance effects, not inductive effects, yield quantitative shifts of the HOMO-LUMO transitions involving orbitals local to the cluster core. Individual ligand exchanges reveal that these shifts are caused by only four of seven ligands, inconsistent with inductive effects. Quantum chemical calculations predict no trend in Au atom charges with respect to Hammett parameter but do predict bond length trends expected for a resonance structure that includes the Au atoms. Computed orbitals show contributions from specific para-OMe oxygen lone pairs to the HOMO, indicating delocalization from the core to specific ligands. These results suggest that resonance structures could be drawn including Au and ligands, guiding efforts to modulate nanocluster electronic structure and energy transfer.

Machine Learning-Driven precise design of stable OLED Materials: Predicting and enhancing Multi-State C-N bond dissociation energies

The intrinsic stability of organic light-emitting diode (OLED) materials critically hinges on the bond dissociation energies (BDEs) of fragile bonds, particularly C-N bonds. Despite the necessity of considering BDEs in multiple electronic states due to the complex working conditions of organic materials in OLED devices, comprehensive exploration remains challenging. Herein, we constructed a high-quality dataset, CNBDE-24, comprising nearly 1500 data points for BDEs across multiple electronic states, obtained through an active learning-guided density functional theory (DFT) calculation strategy. Machine learning models trained on the CNBDE-24 dataset exhibit excellent accuracy in predicting BDEs for OLED materials in neutral, triplet excited (T1), and anionic states, achieving an adjusted coefficient of determination exceeding 0.90 on the test set and bypassing the need for high-cost calculation. Moreover, utilizing neutral state BDEs as pre-training data significantly reduces model error and provides deeper insights into the relationships between different BDEs. We find that BDEs in neutral are influenced by the electronic properties of the nitrogen atom, as indicated by descriptors such as Gasteiger charges. Incorporating C-N bonds into aromatic systems and slightly dispersing N atom charges can inherently increase multi-state BDEs without altering luminescent properties. Additionally, anionic BDEs are determined by the extent of charge transfer during bond cleavage and can be regulated by modifying the C-side fragment. High-throughput virtual screening reveals a new stable purple emitter with a dominant 0–0 transition at 360 nm, which was validated through DFT and excited-state property evaluations. Strategies for enhancing BDEs in multiple resonance thermally activated delayed fluorescence materials without altering excited-state properties are also demonstrated.

Semi-empirical supported, Ab initio derived thermodynamic properties for ClO2 and its sub and extended species, applied in water treatment cycles

This paper describes a group of sixty (60) sub and extended chlorine oxide species with the general formulae of ClxOy (with x ≤ 2, y ≤ 8). Their role in water treatment cycles, behaving as key reactive species, is represented by a complex sequence of chemical inter-dependencies, exposed as a cohesive set of chemical reactions to demonstrate their cyclic role in aqueous media. An empirical/semi-empirical computational approach, supported by Ab Initio simulations, in accordance with open-shell character, has been followed to determine their optimum molecular geometries, to obtain their thermochemical properties. Besides a single molecular analysis, Grand Canonical Ensemble simulations, supported by a revised library of force field parameters, constituted a core component of the computational approach and proved to be invaluable in confirming thermochemical properties. This approach also offered finite estimates of optimum model sizes, a benefit with wider modelling application. Extended molecular species of ClO2 display a complex sequence of bonding character, with a variable charge dissipation (reported as partial charges), which complicates selection of basis sets in optimizing molecular geometries, during Ab Initio analyses.Optimum molecular geometries were obtained using Gaussian and MOPAC, which in turn resulted in reliable Heats of Formation. These correlated well with energies extracted from the open literature. Thermodynamic Analysis of the reaction of selected chlorine oxides with water using FactSage, predicted the production of known and two previously undetected chlorine species, [ClO4]- and [ClOH2]+.

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Zwitterion Intercalated Manganese Dioxide Nanosheets as High-Performance Cathode Materials for Aqueous Zinc Ion Batteries.

In this study, a novel approach is introduced to address the challenges associated with structural instability and sluggish reaction kinetics of δ-MnO2 in aqueous zinc ion batteries. By leveraging zwitterionic betaine (Bet) for intercalation, a departure from traditional cation intercalation methods, Bet-intercalated MnO2 (MnO2-Bet) is synthesized. The positively charged quaternary ammonium groups in Bet form strong electrostatic interactions with the negatively charged oxygen atoms in the δ-MnO2 layers, enhancing structural stability and preventing layer collapse. Concurrently, the negatively charged carboxylate groups in Bet facilitate the rapid diffusion of H+/Zn2+ ions through their interactions, thus improving reaction kinetics. The resulting MnO2-Bet cathode demonstrates high specific capacity, excellent rate capability, fast reaction kinetics, and extended cycle life. This dual-function intercalation strategy significantly optimizes the electrochemical performance of δ-MnO2, establishing it as a promising cathode material for advanced aqueous zinc ion batteries.