Ab Initio Prediction Research Articles

Laser-induced epoxide ring opening on graphene oxide leading to C–O single bonds: An ab initio prediction

The dynamics of the epoxide in graphene oxide under laser irradiation were investigated based on the frameworks of time-dependent density functional theory and molecular dynamics within the Ehrenfest approximation. Two combinations of the laser wavelength (λ) and full width at half-maximum (FWHM) were examined: λ=266 nm with FWHM=100 fs and λ=810 nm with FWHM=35 fs. Upon tuning the laser fluence to just below the threshold for oxygen desorption, epoxide ring opening to form a carbon–oxygen (C–O) single bond was observed. Further simulations revealed that the laser-generated C–O bonds were inert in the presence of water molecules. Conventional static density functional theory calculations and complete-active-space self-consistent field calculations indicated that the C–O bonds were (meta)stable in the electronically excited and negatively charged states. Finally, the feasibility of experimentally observing the C–O bond was considered.

Hunting for Sulfur-containing Molecules in Space: A Spectroscopic Characterization of Cyclopropenethione Based on High-level Ab Initio Calculations

Cyclopropenethione falls into the class of complex organic molecules but has not yet been observed in the interstellar medium or any circumstellar disks. However, its existence is very likely, and thus this study provides high-level ab initio predictions, which may serve as reference data for future observations or experimental work. Rovibrational configuration interaction theory based on multidimensional potential energy surfaces being obtained from explicitly correlated coupled-cluster calculations has been used to predict the fundamental vibrational modes, the microwave spectrum, and low-lying rovibrational transitions. Rotational constants as well as quartic and sextic centrifugal distortion constants were obtained from vibrational perturbation theory.

A Chromosome-Scale and Annotated Reference Genome Assembly of Plecia longiforceps Duda, 1934 (Diptera: Bibionidae).

Urbanization is a leading factor effecting global biodiversity, driving rapid evolutionary processes in the local biota. Species that adapt and proliferate in city environments can become pests, with human activities facilitating their dispersal and excessive outbreaks. Here we present the first genome data of Plecia longiforceps, a lovebug pest in Eastern Asia with intensive aggregations recently occurring in the Seoul Metropolitan Area of Korea. PacBio HiFi and ONT Pore-C sequencing data were used to construct a highly continuous assembly with a total size of 707 Mb and 8 major pseudochromosomes, its integrity supported by the N50 length of 98.1 Mb and 96.8% BUSCO completeness. Structural and functional annotation using transcriptome data and ab initio predictions revealed a high proportion (69.3%) of repeat sequences, and synteny analysis with Bibio marci showed high levels of genomic collinearity. The genome will serve as an essential resource for both population genomics and molecular research on lovebug dispersal and outbreaks, and also implement studies on the eco-evolutionary processes of insects in urbanizing habitats.

High-Precision Mass Measurements of Neutron Deficient Silver Isotopes Probe the Robustness of the N=50 Shell Closure.

High-precision mass measurements of exotic ^{95-97}Ag isotopes close to the N=Z line have been conducted with the JYFLTRAP double Penning trap mass spectrometer, with the silver ions produced using the recently commissioned inductively heated hot cavity catcher laser ion source at the Ion Guide Isotope Separator On-Line facility. The atomic mass of ^{95}Ag was directly determined for the first time. In addition, the atomic masses of β-decaying 2^{+} and 8^{+} states in ^{96}Ag have been identified and measured for the first time, and the precision of the ^{97}Ag mass has been improved. The newly measured masses, with a precision of ≈1 keV/c^{2}, have been used to investigate the N=50 neutron shell closure, confirming it to be robust. Empirical shell-gap and pairing energies determined with the new ground-state mass data are compared with the state-of-the-art abinitio calculations with various chiral effective field theory Hamiltonians. The precise determination of the excitation energy of the ^{96m}Ag isomer in particular serves as a benchmark for abinitio predictions of nuclear properties beyond the ground state, specifically for odd-odd nuclei situated in proximity to the proton dripline below ^{100}Sn. In addition, density functional theory calculations and configuration-interaction shell-model calculations are compared with the experimental results. All theoretical approaches face challenges to reproduce the trend of nuclear ground-state properties in the silver isotopic chain across the N=50 neutron shell and toward the proton dripline.

An outlook on structural biology after AlphaFold: tools, limits and perspectives.

AlphaFold and similar groundbreaking, AI-based tools, have revolutionized the field of structural bioinformatics, with their remarkable accuracy in ab-initio protein structure prediction. This success has catalyzed the development of new software and pipelines aimed at incorporating AlphaFold's predictions, often focusing on addressing the algorithm's remaining challenges. Here, we present the current landscape of structural bioinformatics shaped by AlphaFold, and discuss how the field is dynamically responding to this revolution, with new software, methods, and pipelines. While the excitement around AI-based tools led to their widespread application, it is essential to acknowledge that their practical success hinges on their integration into established protocols within structural bioinformatics, often neglected in the context of AI-driven advancements. Indeed, user-driven intervention is still as pivotal in the structure prediction process as in complementing state-of-the-art algorithms with functional and biological knowledge.

Factorized Quadruples and a Predictor of Higher-Level Correlation in Thermochemistry.

Coupled cluster theory has had a momentous impact on the ab initio prediction of molecular properties, and remains a staple ingratiate in high-accuracy thermochemical model chemistries. However, these methods require inclusion of at least some connected quadruple excitations, which generally scale at best as with the number of basis functions. It is very difficult to predict, a priori, the effect correlation of past CCSD(T) on a given reaction energy. The purpose of this work is to examine cost-effective quadruple corrections based on the factorization theorem of the many-body perturbation theory that may address these challenges. We show that the factorized CCSD(TQf) method introduces minimal error to predicted correlation and reaction energies as compared to the CCSD(TQ). Further, we examine the performance of Goodson's continued fraction method in the estimation of CCSDT(Q)Λ contributions to reaction energies as well as a "new" method related to %TAE[(T)] that we refer to as a scaled perturbation estimator. We find that the scaled perturbation estimator based upon CCSD(TQf)/cc-pVDZ is capable of predicting CCSDT(Q)Λ/cc-pVDZ contributions to reaction energies with an average error of 0.07 kcal mol-1 and an L2D of 0.52 kcal mol-1 when applied to a test-suite of nearly 3000 reactions. This offers a means by which to reliably "ballpark" how important post-CCSD(T) contributions are to reaction energies while incurring no more than CCSD(T) formal cost and a little mental math.

MP2-Based Composite Extrapolation Schemes Can Predict Core-Ionization Energies for First-Row Elements with Coupled-Cluster Level Accuracy.

X-ray photoelectron spectroscopy (XPS) measures core-electron binding energies (CEBEs) to reveal element-specific insights into the chemical environment and bonding. Accurate theoretical CEBE prediction aids XPS interpretation but requires proper modeling of orbital relaxation and electron correlation upon core-ionization. This work systematically investigates basis set selection for extrapolation to the complete basis set limit of CEBEs from ΔMP2 and ΔCC energies across 94 K-edges in diverse organic molecules. We demonstrate that an alternative composite scheme using ΔMP2 in a large basis corrected by ΔCC-ΔMP2 difference in a small basis can quantitatively recover optimally extrapolated ΔCC CEBEs within 0.02 eV. Unlike ΔCC, MP2 calculations do not suffer from convergence issues and are computationally cheaper, and thus, the composite ΔMP2/ΔCC scheme balances accuracy and cost, overcoming limitations of solely using either method. We conclude by providing a comprehensive analysis of the choice of small and large basis sets for the composite schemes and provide practical recommendations for highly accurate (within 0.10-0.15 eV MAE) ab initio prediction of XPS data.

Ab Initio Prediction and Characterization of TiB2 as a Two-Dimensional Dirac Anode for Metal (Li/Na/Mg) Ion Batteries

Ab Initio Prediction and Characterization of TiB₂ as a Two-Dimensional Dirac Anode for Metal (Li/Na/Mg) Ion Batteries

A Framework for Developing Tools to Predict PFAS Physical–Chemical Properties and Mass-Partitioning Parameters

A framework for developing predictive models for PFAS physical–chemical properties and mass-partitioning parameters is presented. The framework is based on the objective of developing tools that are of sufficient simplicity to be used rapidly and routinely for initial site investigations and risk assessments. This is accomplished by the use of bespoke PFAS-specific QSPR models. The development of these models entails aggregation and curation of measured data sets for a target property or parameter, supplemented by estimates produced with quantum–chemical ab initio predictions. The application of bespoke QSPR models for PFAS is illustrated with several examples, including partitioning to different interfaces, uptake by several fish species, and partitioning to four different biological materials. Reasonable correlations to molar volume were observed for all systems. One notable observation is that the slopes of all of the regression functions are similar. This suggests that the partitioning processes in all of these systems are to some degree mediated by the same mechanism, namely hydrophobic interaction. Special factors and elements requiring consideration in the development of predictive models are discussed, including differences in bulk-phase versus interface partitioning processes.

Ab Initio Prediction of Two-Dimensional GeSiBi2 Monolayer as Potential Anode Materials for Sodium-Ion Batteries.

The conceptualization and deployment of electrode materials for rechargeable sodium-ion batteries are key concerns for next-generation energy storage systems. In this contribution, the configuration stability of single-layer GeSiBi2 is systematically discussed based on first-principles calculations, and its potential as an anode material is further investigated. It is demonstrated that the phonon spectrum confirms the dynamic stability and the adsorption energy identifies a strong interaction between Na atoms and the substrate material. The electronic bands indicative of inherent metallicity contribute to the enhancement of electronic conductivity after Na adsorption. The multilayer adsorption of Na provides a theoretical capacity of 361.7 mAh/g, which is comparable to that of other representative two-dimensional anode materials. Moreover, the low diffusion barriers of 0.19 and 0.15 eV further guarantee the fast diffusion kinetics. These contributions signal that GeSiBi2 can be a compatible candidate for sodium-ion batteries anodes.

A database of high-pressure crystal structures from hydrogen to lanthanum

This paper introduces the HEX (High-pressure Elemental Xstals) database, a complete database of the ground-state crystal structures of the first 57 elements of the periodic table, from H to La, at 0, 100, 200 and 300 GPa. HEX aims to provide a unified reference for high-pressure research, by compiling all available experimental information on elements at high pressure, and complementing it with the results of accurate evolutionary crystal structure prediction runs based on Density Functional Theory. Besides offering a much-needed reference, our work also serves as a benchmark of the accuracy of current ab-initio methods for crystal structure prediction. We find that, in 98% of the cases in which experimental information is available, ab-initio crystal structure prediction yields structures which either coincide or are degenerate in enthalpy to within 300 K with experimental ones. The main manuscript contains synthetic tables and figures, while the Crystallographic Information File (cif) for all structures can be downloaded from the related figshare online repository.

Chromosome-level genome assembly and annotation of a potential model organism Gossypium arboreum ZB-1

Recent advancements in plant regeneration and synthetic polyploid creation have been documented in Gossypium arboreum ZB-1. These developments make ZB-1 a potential model within the Gossypium genus for investigating gene function and polyploidy. This work generated the sequence and annotation of the ZB-1 genome. The contig-level genome was constructed using the PacBio high-fidelity reads, encompassing 81 contigs with an N50 length of 112.12 Mb. The Hi-C data assisted the construction of the chromosome-level genome, which consists of 13 pseudo-chromosomes and 39 un-anchored contigs, with a total length of about 1.67 Gb. Repetitive sequences accounted for about 69.7% of the genome in length. Based on ab initio and evidence-based prediction, we have identified 48,021 protein-coding genes in the ZB-1 genome. Comparative genomics analysis revealed conserved gene content and arrangement between ZB-1 and G. arboreum SXY1. The single nucleotide polymorphism occurrence rate between ZB-1 and SXY1 was about 0.54 per 1,000 nucleotides. This study enriched the genomic resources for further exploration into cotton regeneration and polyploidy mechanisms.

Multireference Ab Initio Calculations on Excited Electronic States of Carbazole-Based Organic Compounds for Thermally Activated Delayed Fluorescence.

The emerging technology of organic light-emitting diodes takes advantage of the thermally activated delayed fluorescence (TADF) mechanism for improved efficiency. Carbazole-based organic molecules are suitable for TADF emission because of charge transfer excitations between the electron-donor carbazole and an electron-acceptor unit. Computational design of new TADF molecules with the desired properties is challenging because charge-transfer excitations cannot be predicted accurately by time-dependent density functional theory. Four groups of carbazole-based donor-acceptor molecules have been studied using multireference ab initio methods to understand the nature of excited electronic states. The state-averaged complete active space self-consistent field (SA-CASSCF) and the N-electron valence state perturbation theory (NEVPT2) were used to calculate energies and oscillator strengths for multiple excited electronic states. The number of active electrons and orbitals and the number of excited states included in state-averaged CASSCF were selected such that the accuracy of ab initio predictions could be improved systematically. The procedure introduced here for the calculation of multiple excited electronic states of TADF candidates can be used to accelerate the computational search for efficient TADF materials.

Interfacial optical anisotropy of Cu(110) electrochemistry using singular value decomposition

Understanding surface/interface states (SIs) in metal–electrolyte environments is crucial for diverse scientific and technological fields. This work investigates the reflectance anisotropy spectroscopy (RAS) of Cu(110) in HCl solution to gain deeper insights. Using the singular-value decomposition (SVD) method, we extract three distinct RAS features that track electrochemical changes. We argue that these features stem from surface-induced bulk optical anisotropies and Cl− adsorption. Their correlation with cyclic voltammetry (CV) further supports this interpretation. Specifically, we link these lineshapes to HCl adsorption, and microscale surface roughness resembling a lamellar grating, as verified by electrochemical scanning tunneling microscopy (EC-STM), and another one correlated to ab initio calculations bearing transitions between bulk and surface states of Cu(110). Our findings shed light on SIs behavior in metal–electrolyte interfaces. The combination of SVD and RAS establishes a robust methodology for studying metallic surfaces in electrochemical systems, enabling comparisons with ab initio predictions.

Ab Initio Prediction of the Structural, Elastic and Thermodynamic Properties Under Hydrostatic Pressure of the Ternary Tetragonal Phosphides XRh2P2 (X = Ca, Ba) for Superconducting Application

Ab Initio Prediction of the Structural, Elastic and Thermodynamic Properties Under Hydrostatic Pressure of the Ternary Tetragonal Phosphides XRh2P2 (X = Ca, Ba) for Superconducting Application

Ab initio prediction of half-metallic and metallic ferromagnetism in ZnO:(Co,Cr) systems

Doping effects on the electronic and magnetic properties of Zn1−x (Co,Cr) x O systems are investigated within Local Spin Density Approximation and Hubbard U methods. Based on Density Functional Theory the spin-polarization band structures, density of states for investigated systems are calculated. Systematic analysis of the electronic properties shows that TM-doped ZnO has generated new energy levels in the vicinity of Fermi energy level. From first-principle calculations we obtained Cr-ZnO and Co-ZnO systems are metallic and half-metallic ferromagnetic materials, respectively. The obtained results for Cr-doped ZnO 128- and 192-atom supercell systems show magnetic properties with higher Curie temperature than room temperature. There are large local moments, ∼2.9 and ∼4.2 for Co and Cr dopants, respectively. Magnetic moments are related with two electron defects in the supercell structure and unpaired electrons of transition metal. The ferromagnetic and antiferromagnetic phases and the total energy are obtained for x = 2.08%, 3.125%, 4.16%, 6.25%, 8.3%, 12.5%, and 25% impurity concentrations for doped ZnO.

An improved chromosome-level genome assembly and annotation of Echeneis naucrates

Echeneis naucrates, as known as live sharksucker, is famous for the behavior of attaching to hosts using a highly modified dorsal fin with oval-shaped sucking disc. Here, we generated an improved high-quality chromosome-level genome assembly of E. naucrates using Illumina short reads, PacBio long reads and Hi-C data. Our assembled genome spans 572.85 Mb with a contig N50 of 23.19 Mb and is positioned to 24 pseudo-chromosomes. Additionally, at least one telomere was identified for 23 out of 24 chromosomes. Furthermore, we identified a total of 22,161 protein-coding genes, of which 21,402 genes (96.9%) were annotated successfully with functions. The combination of ab initio predictions and Repbase-based searches revealed that 15.57% of the assembled E. naucrates genome was identified as repetitive sequences. The completeness of the genome assembly and the gene annotation were estimated to be 97.5% and 95.4% with BUSCO analyses. This work enhances the utility of the live sharksucker genome and provides a valuable groundwork for the future study of genomics, biology and adaptive evolution in this species.

De novo transcriptome assembly and genome annotation of the fat-tailed dunnart (Sminthopsis crassicaudata).

Marsupials exhibit distinctive modes of reproduction and early development that set them apart from their eutherian counterparts and render them invaluable for comparative studies. However, marsupial genomic resources still lag far behind those of eutherian mammals. We present a series of novel genomic resources for the fat-tailed dunnart (Sminthopsis crassicaudata), a mouse-like marsupial that, due to its ease of husbandry and ex-utero development, is emerging as a laboratory model. We constructed a highly representative multi-tissue de novo transcriptome assembly of dunnart RNA-seq reads spanning 12 tissues. The transcriptome includes 2,093,982 assembled transcripts and has a mammalian transcriptome BUSCO completeness score of 93.3%, the highest amongst currently published marsupial transcriptomes. This global transcriptome, along with ab initio predictions, supported annotation of the existing dunnart genome, revealing 21,622 protein-coding genes. Altogether, these resources will enable wider use of the dunnart as a model marsupial and deepen our understanding of mammalian genome evolution.

Accelerating the discovery of direct bandgap doped-spinel photovoltaic materials: A target-driven approach using interpretable machine learning

The spinel structure, unifying tetrahedral and octahedral coordination within a single crystal lattice, emerges as a promising alternative to perovskite and traditional semiconductors, particularly in the context of photovoltaic applications. However, the majority of surveyed spinels exhibit an indirect bandgap, imposing substantial limitations on their utility. Consequently, doping is required to tailor indirect bandgap spinels into direct ones. In this study, leveraging machine learning (ML) algorithms, we design a target-driven framework to accelerate the ab initio predictions of unknown doped-spinels using elements from the periodic table. Utilizing this approach, we have introduced a novel machine learning classification model designed for the prediction of the direct-indirect bandgap nature in spinel materials. This pioneering model shows promising potential for achieving rapid and precise predictions, particularly in scenarios involving small dataset. Especially, a full list of potential 3449 (AxA′1-x)B2X4-type doped-spinels and 3809 A(BxB′2-x)X4-type doped-spinels with direct bandgaps is identified from the vast pool of unknown doped-spinel materials. Further, the application of interpretable ML extracts the first ionization energy of the B-site ion as the most important feature for the nature of bandgap, offering insightful design rules. This research provides a novel perspective on unraveling spinel materials, and the proposed design framework proves effective in identifying high-performance materials within a vast chemical space, all while minimizing computational costs.

A chromosome-level genome assembly of the spider mite Tetranychus piercei McGregor

Despite the rapid advances in sequencing technology, limited genomic resources are currently available for phytophagous spider mites, which include many important agricultural pests. One of these pests is Tetranychus piercei (McGregor), a serious banana pest in East Asia exhibiting remarkable tolerance to high temperature. In this study, we assembled a high-quality genome of T. piercei using a combination of PacBio long reads and Illumina short reads sequencing. With the assistance of chromatin conformation capture technology, 99.9% of the contigs were anchored into three pseudochromosomes with a total size of 86.02 Mb. Repetitive elements, accounting for 14.16% of this genome (12.20 Mb), are predominantly composed of long-terminal repeats (30.7%). By combining evidence of ab initio prediction, transcripts, and homologous proteins, we annotated 11,881 protein-coding genes. Both the genome and proteins have high BUSCO completeness scores (>94%). This high-quality genome, along with reliable annotation, provides a valuable resource for investigating the high-temperature tolerance of this species and exploring the genomic basis that underlies the host range evolution of spider mites.