Electron Research Articles

Extended Active Space Ab Initio Ligand Field Theory: Applications to Transition-Metal Ions.

Ligand field theory (LFT) is one of the cornerstones of coordination chemistry since it provides a conceptual framework in which a great many properties of d- and f-element compounds can be discussed. While LFT serves as a powerful qualitative guide, it is not a tool for quantitative predictions on individual compounds since it incorporates semiempirical parameters that must be fitted to experiment. One way to connect the realms of first-principles electronic structure theory that has emerged as particularly powerful over the past decade is the ab initio ligand field theory (AILFT). The original formulation of this method involved the extraction of LFT parameters by fitting the ligand field Hamiltonian to a complete active space self-consistent field (CASSCF) Hamiltonian. The extraction was shown to be unique provided that the active space consists of 5/7 metal d/f-based molecular orbitals (MOs). Subsequent improvements have involved incorporating dynamical correlation using second-order N-electron valence state perturbation theory (NEVPT2) or second-order dynamical correlation dressed complete active space (DCDCAS). However, the limitation of past approaches is that the method requires a minimal space of 5/7 metal d- or f-based molecular orbitals. This leads to a number of limitations: (1) neglect of radial or semicore correlation would arise from the effect of a second d-shell or an sp-shell in the active space, (2) a more balanced description of metal-ligand bond covalency is lacking because the bonding ligand-based counterparts of the metal d/f orbitals are not in the active space. This usually leads to an exaggerated ionicity of the M-L bonds. In this work, we present an extended active space AILFT (esAILFT) that circumvents these limitations and is, in principle, applicable to arbitrary active spaces, as long as these contain the 5/7 metal d/f-based MOs as a subset. esAILFT was implemented in a development version of the ORCA software package. In order to help with the application of the new method, various criteria for active space extension were explored for 3d, 4d, and 5d transition-metal ions with varying charge. An interpretation of the trends in the Racah B parameter for these ions is also presented as a demonstration of the capabilities of esAILFT.

Enhancing Two-Photon Absorption of Green Fluorescent Protein by Quantum Entanglement.

Exploring the electronic states of molecules through excitation with entangled and classical photon pairs offers new insights into the nature of light-matter interactions and stimulates the development of quantum spectroscopy. Here, we address the importance of temporal entanglement of light in two-photon absorption (TPA) upon the S0 → S1 transition by the green fluorescent protein (GFP)─a key molecular unit in the bioimaging of living cells. By invoking a two-level model applicable when permanent dipole pathways dominate the two-photon transition, we derive a convenient closed-form analytical expression for the entangled TPA strength. For the first time, we disclose specific molecular properties that cause classical and entangled two-photon absorptions to be qualitatively different when exciting the same state. We reveal a new nonclassical contribution to the TPA strength, which is defined by the magnitude and directional alignment of permanent dipole moments in the initial and final states. Using high-level electronic structure theory, we show that the nonclassical contribution is intrinsically larger than the classical counterpart in GFP, leading to an enhancement of the TPA strength due to quantum entanglement by several orders of magnitude. We also present evidence that the classical and quantum TPA strengths can be modulated differently by the protein environment and demonstrate how to control the outcome by alterations in the local electric field of the protein caused by a single amino acid replacement. Our findings establish physical grounds for enhancing TPA in photoactive proteins by quantum entanglement, facilitating the rational design of high-efficiency biomarkers for future applications that utilize quantum light.

Free DNA partially clarifies discrepancies between qPCR and the conventional phage quantification method.

To use phages in a personalized therapy and industrial applications, an accurate quantification is needed. The gold standard method, namely the culture-based double agar overlay (DAO) method, provides an accurate estimate of the number of infectious phages but is laborious and time-intensive. Quantitative polymerase chain reaction (qPCR) can be used as a fast alternative but tends to overestimate the number of infectious phage particles. Here we describe the use of a DNase treatment before quantification of the Staphylococcus aureus phage ISP with qPCR to obtain a more accurate estimate of the number of infectious phage particles. We showed that DNase treatment results in a significant decrease of the concentration when measured with qPCR although for two out of three tested ISP phage stocks, there was still a significant difference with the DAO method. We also showed that the discrepancy between quantification with qPCR and the DAO method is dependent on the storage period of the phage stock, with a larger discrepancy for older stocks. Additionally, we used negative contrast immune electron microscopy to confirm the presence of DNA in the medium of the phage stock and the impact of the DNase treatment on the free DNA.

A detailed analysis of the key steps of the cyclopentene autoignition mechanism from calculated RRKM rate constants associated with ignition delay time simulations

Cyclopentene, a prototype for studying the combustion chemistry of cyclic olefins, appears in the oxidation of cyclic hydrocarbons and can provide key information in the understanding of the formation of polycyclic aromatic hydrocarbons. The ▪ addition to the double-bond is one of the main steps in low-temperature oxidation mechanisms of unsaturated organic compounds. In the case of cyclopentene, addition of ▪ yields a hydroxycyclopentyl radical, that can further react with O2. In this work, we studied the potential energy surface and reaction rates for the subsequent reactions of O2 with the hydroxycyclopentyl radical. The temperature and pressure dependence of the rate constants were determined using master equation simulations, with microcanonical rate coefficients calculated by RRKM theory. The potential energy surface was extracted from high-level electronic structure theory, based on geometries and frequencies obtained using density functional theory. Our results indicate that a Waddington-type mechanism, which produces glutaraldehyde and regenerates ▪ , is the dominant reaction pathway. However, at low-temperatures, a secondary pathway leading to the formation of epoxycyclopentanol and ▪ becomes equally significant. The thermochemistry of all ▪ radicals involved were also evaluated. The kinetic and thermodynamic data were incorporated into a comprehensive mechanism of cyclopentene autoignition, in order to simulate the associated ignition delays. The updated reaction mechanism resulted in shorter ignition delays compared to the non-updated mechanism. Sensitivity analysis was performed to identify the primary contributors.Novelty and Significance StatementCyclopentene is an important intermediate in the oxidation of cyclic olefins and serves as a precursor in the formation of polycyclic aromatic hydrocarbons. Kinetic modeling studies require detailed information on elementary reactions, much of which is typically unavailable from experiments. The novelty and significance of this study lie in the theoretical calculations of rate constants for key reactions in the oxidation of cyclopentene and their evaluation within the comprehensive mechanism proposed by Lokachari et al. The results demonstrate that the studied reactions significantly influence the ignition delays of cyclopentene at low temperatures. Furthermore, the data presented here can be applied in future studies focusing on the oxidation of cyclic olefins.

Topological nodal line features in NiSe semimetal: Insights from electronic transport and density functional theory studies

Topological nodal line features in NiSe semimetal: Insights from electronic transport and density functional theory studies

Non-adiabatic Couplings in Surface Hopping with Tight Binding Density Functional Theory: The Case of Molecular Motors.

Nonadiabatic molecular dynamics (NAMD) has become an essential computational technique for studying the photophysical relaxation of molecular systems after light absorption. These phenomena require approximations that go beyond the Born-Oppenheimer approximation, and the accuracy of the results heavily depends on the electronic structure theory employed. Sophisticated electronic methods, however, make these techniques computationally expensive, even for medium size systems. Consequently, simulations are often performed on simplified models to interpret the experimental results. In this context, a variety of techniques have been developed to perform NAMD using approximate methods, particularly density functional tight binding (DFTB). Despite the use of these techniques on large systems, where ab initio methods are computationally prohibitive, a comprehensive validation has been lacking. In this work, we present a new implementation of trajectory surface hopping combined with DFTB, utilizing nonadiabatic coupling vectors. We selected the methaniminium cation and furan systems for validation, providing an exhaustive comparison with the higher-level electronic structure methods. As a case study, we simulated a system from the class of molecular motors, which has been extensively studied experimentally but remains challenging to simulate with ab initio methods due to its inherent complexity. Our approach effectively captures the key photophysical mechanism of dihedral rotation after the absorption of light. Additionally, we successfully reproduced the transition from the bright to dark states observed in the time-dependent fluorescence experiments, providing valuable insights into this critical part of the photophysical behavior in molecular motors.

Pseudo Molecular Doping and Ambipolarity Tuning in Si Junctionless Nanowire Transistors Using Gaseous Nitrogen Dioxide

AbstractAmbipolar transistors facilitate concurrent transport of both positive (holes) and negative (electrons) charge carriers in the semiconducting channel. Effective manipulation of conduction symmetry and electrical characteristics in ambipolar silicon junctionless nanowire transistors (Si‐JNTs) is demonstrated using gaseous nitrogen dioxide (NO2). This involves a dual reaction in both p‐ and n‐type conduction, resulting in a significant decrease in the current in n‐conduction mode and an increase in the p‐conduction mode upon NO2 exposure. Various Si‐JNT parameters, including “on”‐current (Ion), threshold voltage (Vth), and mobility (µ) exhibit dynamic changes in both the p‐ and n‐conduction modes of the ambipolar transistor upon interaction with NO2 (concentration between 2.5 – 50 ppm). Additionally, NO2 exposure to Si‐JNTs with different surface morphologies, that is, unpassivated Si‐JNTs with a native oxide or with a thermally grown oxide (10 nm), show distinct influences on Ion, Vth, and µ, highlighting the effect of surface oxide on NO2‐mediated charge transfer. Interaction with NO2 alters the carrier concentration in the JNT channel, with NO2 acting as an electron acceptor and inducing holes, as supported by Density Functional Theory (DFT) calculations, providing a pathway for charge transfer and “pseudo” molecular doping in ambipolar Si‐JNTs.

Creating Benchmarks for Lithium Clusters and Using Them for Testing and Validation.

Metal clusters often have a variety of possible structures, and they are calculated by a wide range of methods; however, fully converged benchmarks on the energy differences of structures and spin states that could be used to test or validate these methods are rare or nonexistent. Small lithium clusters are good candidates for such benchmarks to test different methods against well-converged relative energetics for qualitatively different structures because they have a small number of electrons. The present study provides fully converged benchmarks for Li4 and Li5 clusters and uses them to test a diverse group of approximation methods. To create a dataset of well-converged single-point energies for Li4 and Li5, stationary structures were optimized by Kohn-Sham density functional theory (KS-DFT) and then single-point energy calculations at these structures were carried out by two quite different beyond-CCSD(T) methods. To test other methods single-point energy calculations at these structures were carried out by KS-DFT, Mo̷ller-Plesset (MP) theory, coupled cluster (CC) theory, five composite methods (Gaussian-4, the Wuhan-Minnesota (WM) composite method, and the W2X, W3X, and W3X-L composite methods of Radom and co-workers), multiconfiguration pair-density functional theory (MC-PDFT), complete active space second-order perturbation theory (CASPT2), and n-electron valence state second-order perturbation theory (NEVPT2). Our results show that rhomboid and trigonal bipyramid (TBP) geometries are the most stable structures for Li4 and Li5, respectively. Using the W3X-L method to obtain our best estimates, the mean unsigned deviations were calculated for other methods for several structures and spin states of both Li4 and Li5. Binding energies and M diagnostics were calculated for all structures. The data in this paper are valuable for assessing the reliability of current electronic structure theories and also developing new density functionals and machine learned models.

Improvement of interfacial electron extraction efficiency by suppressing Auger recombination in an indium-doped mixed cationic perovskite heterostructure

The electron extraction of indium (In3+)-doped mixed cationic perovskite heterostructure, SnO2/Cs0.05(MA0.17FA0.83)0.95Pb(I0.83Br0.17)3:In3+ (SnO2/M:In3+), is explored by optical pump-terahertz (THz) probe technology. The difference of the conductivity maxima (Δσdm) of M and SnO2/M is used to calculate the electron extraction efficiency of SnO2/M with photoexcited carrier density of 2.66 × 1018 ∼ 1.33 × 1019 cm−3, which are 33.14 %, 32.01 %, 31.17 %, −3.73 %, and –23.66 %, respectively. The negative electron extraction efficiency of SnO2/M with photoexcited carrier density from 1.06 × 1019 to 1.33 × 1019 cm−3 is caused by the extraction of electrons from SnO2 into M. For SnO2/M:In3+, electron extraction efficiencies are 51.76 %, 52.68 %, 49.51 %, 48.03 % and 48.03 % with photoexcited carrier density increased from 2.66 × 1018 cm−3 to1.33 × 1019 cm−3, respectively, which are all positive and about 20 % higher than that of SnO2/M, related to the suppression of Auger recombination and super-injection phenomenon by In3+ doping. The insights of this investigation provide important experimental data and theoretical basis for design and production of efficient perovskite solar cells.

Photoassisted electron emission from planar-type electron source based on graphene/oxide/silicon structure

This paper reports on photoassisted electron emission from a planar-type electron emission source based on a graphene/oxide/p-Si structure under visible laser light irradiation. The electron source is expected to be useful as a photocathode with a high quantum efficiency and an ultrafast pulsed electron beam. The electron emission efficiency is found to be 12%, independent of laser light irradiation. Without a negative electron affinity surface, the emission current generated by irradiation shows an increase of several orders of magnitude compared with that in the dark, and a quantum efficiency of 0.3% is achieved. This electron source exhibits advanced photoassisted electron emission characteristics with high photosensitivity in the order of milliamps per watt. The photoassisted emission from the device shows a photoresponse with a rise and fall time of 70 μs at a wavelength of 633 nm, which is determined by the diffusion process of photoexcited electrons in the bulk. The use of a heavily doped p-type silicon substrate provides a practical route for further improvement.

Theoretically grounded approaches to account for polarization effects in fixed-charge force fields.

Non-polarizable, or fixed-charge, force fields are the workhorses of most molecular simulation studies. They attempt to describe the potential energy surface (PES) of the system by including polarization effects in an implicit way. This has historically been done in a rather empirical and ad hoc manner. Recent theoretical treatments of polarization, however, offer promise for getting the most out of fixed-charge force fields by judicious choice of parameters (most significantly the net charge or dipole moment of the model) and application of post facto polarization corrections. This Perspective describes these polarization theories, namely the "halfway-charge" theory and the molecular dynamics in electronic continuum theory, and shows that they lead to qualitatively (and often, quantitatively) similar predictions. Moreover, they can be reconciled into a unified approach to construct a force field development workflow that can yield non-polarizable models with charge/dipole values that provide an optimal description of the PES. Several applications of this approach are reviewed, and avenues for future research are proposed.

Comparing parameterized and self-consistent approaches to abinitio cavity quantum electrodynamics for electronic strong coupling.

Molecules under strong or ultra-strong light-matter coupling present an intriguing route to modify chemical structure, properties, and reactivity. A rigorous theoretical treatment of such systems requires handling matter and photon degrees of freedom on an equal quantum mechanical footing. In the regime of molecular electronic strong or ultra-strong coupling to one or a few molecules, it is desirable to treat the molecular electronic degrees of freedom using the tools of abinitio quantum chemistry, yielding an approach referred to as abinitio cavity quantum electrodynamics (ai-QED), where the photon degrees of freedom are treated at the level of cavity QED. We analyze two complementary approaches to ai-QED: (1) a parameterized ai-QED, a two-step approach where the matter degrees of freedom are computed using existing electronic structure theories, enabling the construction of rigorous ai-QED Hamiltonians in a basis of many-electron eigenstates, and (2) self-consistent ai-QED, a one-step approach where electronic structure methods are generalized to include coupling between electronic and photon degrees of freedom. Although these approaches are equivalent in their exact limits, we identify a disparity between the projection of the two-body dipole self-energy operator that appears in the parameterized approach and its exact counterpart in the self-consistent approach. We provide a theoretical argument that this disparity resolves only under the limit of a complete orbital basis and a complete many-electron basis for the projection. We present numerical results highlighting this disparity and its resolution in a particularly simple molecular system of helium hydride cation, where it is possible to approach these two complete basis limits simultaneously. In this same helium hydride system, we examine and compare the practical issue of the computational cost required to converge each approach toward the complete orbital and many-electron bases limit. Finally, we assess the aspect of photonic convergence for polar and charged species, finding comparable behavior between parameterized and self-consistent approaches.

Theoretical study on the lattice distortion and electronic structure in the Al–Co–Cr–Fe–Ni multicomponent alloys

At present, the phase structure design for multicomponent alloys (MCAs) is mainly based on the valence electron concentration (VEC). In this work, based on the classification of valence electrons by the empirical electron theory of solid and molecule (EET), the VEC is further dissected and found that the covalent electron concentration (CEC) can be used as a criterion for determining the phase structure of MCAs. The Alx(CoCrFeNi)1-x (x = 0, 1/24, 1/12 and 1/8) alloys are designed on the basis of the CEC. The effect of Al content on the lattice distortion in the FCC phase of the alloys by combining density functional theory (DFT) and EET. The results show that the degree of lattice distortion in the FCC phase gradually increases with the increase of Al content and the interatomic bonding decreases before the phase structure transition. The alloy reaches the criticality of the phase structure transition when the Al content is 9.48 at.%.

Molecular quantum chemical data sets and databases for machine learning potentials

Abstract The field of computational chemistry is increasingly leveraging machine learning (ML) potentials to predict molecular properties with high accuracy and efficiency, providing a viable alternative to traditional quantum mechanical (QM) methods, which are often computationally intensive. Central to the success of ML models is the quality and comprehensiveness of the data sets on which they are trained. Quantum chemistry data sets and databases, comprising extensive information on molecular structures, energies, forces, and other properties derived from QM calculations, are crucial for developing robust and generalizable ML potentials.
In this review, we provide an overview of the current landscape of quantum chemical data sets and databases. We examine key characteristics and functionalities of prominent resources, including the types of information they store, the level of electronic structure theory employed, the diversity of chemical space covered, and the methodologies used for data creation. Additionally, an updatable resource is provided to track new data sets and databases at https://github.com/Arif-PhyChem/datasets_and_databases_4_MLPs. This resource also has the overview in a machine-readable database format with the Jupyter notebook example for analysis.
Looking forward, we discuss the challenges associated with the rapid growth of quantum chemical data sets and databases, emphasizing the need for updatable and accessible resources to ensure the long-term utility of them. We also address the importance of data format standardization and the ongoing efforts to align with the FAIR principles to enhance data interoperability and reusability. Drawing inspiration from established materials databases, we advocate for the development of user-friendly and sustainable platforms for these data sets and databases.

Analytical treatment of the Yukawa screened Coulomb interaction in a plane-wave basis

The calculation of the many-electron (screened) Coulomb and exchange integrals is a very common task to perform in modern electronic structure theory. While an analytical treatment of the complete integrals is too complicated to be attempted directly, essential insight can be gained by focusing on the most significant contributions, as determined by a physical criterion. The monopole term of the screened Coulomb interaction is particularly important, since it defines the Hubbard interaction U among a set of localized electrons, which is an essential parameter for effective models of strongly correlated systems. Here, we derive an analytical solution for the matrix elements of the screened Coulomb interaction on a plane-wave basis, which is routinely used in the most common methods for electronic structure calculations. Screening is treated using a Yukawa potential, which is suitable to describe the valence electrons in the Fermi level region. For the solution of the integrals, the plane waves and the Yukawa potential are first expanded in Bessel functions of first and second kind. Then, by means of the lower and upper incomplete gamma functions, we are able to obtain closed-form integrals of a series that remains convergent for realistic parameters. Our exact solution for the radial integrals of the monopole term can find usage in plane-wave codes for electronic structure calculations, both as an output tool as well as within the computational cycle, as e.g., for many-body extensions of density-functional theory. Considering the importance of Bessel functions in solid state physics and electronic structure theory, it is also easy to foresee that our solution to the various integrals across this work may become useful to several other problems in the field.

Aggregation Dynamics of a 150 kDa Aβ42 Oligomer: Insights from Cryo Electron Microscopy and Multimodal Analysis

Protein misfolding is a widespread phenomenon that can result in the formation of protein aggregates, which are markers of various disease states, including Alzheimer's disease (AD). In AD, amyloid beta (Aβ) peptides are key players in the disease's progression, particularly the 40- and 42 residue variants, Aβ40 and Aβ42. These peptides aggregate to form amyloid plaques and contribute to neuronal toxicity. Recent research has shifted attention from solely Aβ fibrils to also include Aβ protofibrils and oligomers as potentially critical pathogenic agents. Particularly, oligomers demonstrate more significant toxicity compared to other Aβ specie. Hence, there is an increased interest in studying the correlation between toxicity and their structure and aggregation pathway. The present study investigates the aggregation of a 150kDa Aβ42 oligomer that does not lead to fibril formation. Using negative stain transmission electron microscopy (TEM), size exclusion chromatography (SEC), dynamic light scattering (DLS), and cryo-electron microscopy (cryo-EM), we demonstrate that 150kDa Aβ42 oligomers form higher-order string-like assemblies over time. These strings are unique from the classical Aβ fibrils. The significance of our work lies in elucidating molecular behavior of a novel non-fibrillar form of Aβ42 aggregate.

Quantum field theory of electrons and nuclei

Abstract We develop a non-relativistic quantum field theory of electrons and nuclei with Coulomb interactions. We derive the exact equations of motion and write these equations in the form of Hedin’s equations for all species of identical particles involved. Theory derived allows the computation of exact observables and provides a rigorous starting point to derive approximations in a systematic way.

The Linear Mixing Approximation in Silica–Water Mixtures at Planetary Conditions

The linear mixing approximation (LMA) is often used in planetary models for calculating the equations of state (EOS) of mixtures. A commonly assumed planetary composition is a mixture of rock and water. Here we assess the accuracy of the LMA for pressure–temperature conditions relevant to the interiors of Uranus and Neptune. We perform molecular dynamics simulations using ab initio simulations and consider pure water, pure silica, and 1:1 and 1:4 silica–water molecular fractions at a temperature of 3000 K and pressures between 30 and 600 GPa. We find that the LMA is valid within a few percent (< ∼5%) between ∼150 and 600 Gpa, where the sign of the difference in inferred density depends on the specific composition of the mixture. We also show that the presence of rocks delays the transition to superionic water by ∼70 GPa for the 1:4 silica–water mixture. Finally, we note that the choice of electronic theory (functionals) affects the EOS and introduces an uncertainty of the order of 10% in density. Our study demonstrates the complexity of phase diagrams in planetary conditions and the need for a better understanding of rock–water mixtures and their effect on the inferred planetary composition.

Exploring deep eutectic solvents of methane sulfonic acid and choline chloride: Formation, properties, and metal solvent effectiveness

Methane sulfonic acid (MSA), a hydrogen bond donor (HBD), was combined with choline chloride (HBA) at varying molar ratios (1:1, 1:2 and 2:1) to explore the formation of deep eutectic solvents (DES). The resulting blends, at 1:1 and 2:1 ratio, remained liquid at ambient temperature. Among these combinations, the DES formed with a 1:1 molar ratio (MSA-ChCl) exhibited the highest decomposition temperature (166 °C) followed by MSA-ChCl (1:2) and MSA-ChCl (2:1). Alongside, the glass transition temperature of the DES also remained relatively unaffected by the molar ratio of its components. Notably, both density and viscosity were observed to be temperature dependent. To elucidate hydrogen bonding interactions between choline chloride and MSA, Fourier Transform Infrared (FTIR) and Nuclear Magnetic Resonance (NMR) spectroscopy were employed. The broadening and shifting of IR peaks illustrate the formation of intermolecular bonding between MSA and ChCl. Density Functional Theory (DFT) calculations were conducted to optimise molecular structures, analyse HOMO-LUMO levels, estimate electronegativity and ionization potential, and generate electrostatic potential surfaces of the DES. As per calculated Molecular Electrostatic Potential (MEP) by DFT of pure MSA and ChCl, SO of MSA has most electron deficient region and it has potential to interact with electron positive OH part of ChCl, which is also demonstrated by IR spectra. MSA-ChCl (2:1) displayed the most negative electron density and proved to be the most effective metal solvent among the DES formulations tested. Exceptional solubility of lithium in MSA-ChCl (2:1) was observed, exceeding 105 mg/L. Moreover, zinc, copper, cobalt, and iron also demonstrated good solubility in MSA-ChCl (2:1), ranging from 105 to 104 mg/L.

Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints

The self-consistent field (SCF) generation of the three-dimensional (3D) electron density distribution (ρ) represents a fundamental aspect of density functional theory (DFT) and related first-principles calculations, and how one can shorten or bypass the SCF loop represents a critical question in electronic structure theory from both practical and fundamental standpoints. Herein, a machine learning strategy, DeepSCF, is presented in which the map between the SCF ρ and the initial guess density (ρ0) constructed by the summation of neutral atomic densities is learned using 3D convolutional neural networks (CNNs). High accuracy and transferability of DeepSCF are achieved by first encoding ρ0 on a 3D grid and then expanding the input features to include atomic fingerprints beyond ρ0. The prediction of the residual density (δρ) rather than ρ itself is targeted, and given that δρ is indicative of chemical bonding information, a dataset of small-sized organic molecules featuring diverse bonding characters is adopted. The fidelity of DeepSCF is finally enhanced by subjecting the atomic geometries of the dataset to random rotations and strains. The effectiveness of DeepSCF is demonstrated using a complex carbon nanotube-based DNA sequencer model. This work evidences that the nearsightedness in electronic structure can be optimally represented via the spatial locality in CNNs, offering insight into the success of various machine learning-based atomistic materials simulations.