Computational Chemistry Simulations Research Articles

MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows.

Machine learning (ML) is increasingly becoming a common tool in computational chemistry. At the same time, the rapid development of ML methods requires a flexible software framework for designing custom workflows. MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows. This open-source package provides plenty of choice to the users who can run simulations with the command-line options, input files, or with scripts using MLatom as a Python package, both on their computers and on the online XACS cloud computing service at XACScloud.com. Computational chemists can calculate energies and thermochemical properties, optimize geometries, run molecular and quantum dynamics, and simulate (ro)vibrational, one-photon UV/vis absorption, and two-photon absorption spectra with ML, quantum mechanical, and combined models. The users can choose from an extensive library of methods containing pretrained ML models and quantum mechanical approximations such as AIQM1 approaching coupled-cluster accuracy. The developers can build their own models using various ML algorithms. The great flexibility of MLatom is largely due to the extensive use of the interfaces to many state-of-the-art software packages and libraries.

Unitary Coupled Cluster: Seizing the Quantum Moment.

Shallow, CNOT-efficient quantum circuits are crucial for performing accurate computational chemistry simulations on current noisy quantum hardware. Here, we explore the usefulness of noniterative energy corrections, based on the method of moments of coupled-cluster theory, for accelerating convergence toward full configuration interaction. Our preliminary numerical results relying on iteratively constructed ansätze suggest that chemically accurate energies can be obtained with substantially more compact circuits, implying enhanced resilience to gate and decoherence noise.

Formation of Complex Organic Molecules on Interstellar CO Ices? Insights from Computational Chemistry Simulations

The carbon (3P) atom is a reactive species that, according to laboratory experiments and theoretical calculations, condensates with interstellar ice components. This fact is of uttermost importance for the chemistry in the interstellar medium (ISM) because the condensation reaction is barrierless, and the subsequent species formed are still reactive given their open-shell character. Carbon condensation on CO-rich ices forms the C=C=O (3Σ−) species, which can be easily hydrogenated twice to form ketene (H2CCO). Ketene is very reactive in terrestrial conditions, usually found as an intermediate that is difficult to isolate in chemical synthesis laboratories. These characteristics suggest that ketene can be a good candidate to form interstellar complex organic molecules via a two-step process, i.e., its activation followed by a radical–radical coupling. In this work, reactions between ketene and atomic H and the OH and NH2 radicals on a CO-rich ice model have been explored by means of quantum chemical calculations complemented by kinetic calculations to evaluate if they are favorable in the ISM. Results indicate that the addition of H to ketene (helped by tunneling) to form the acetyl radical (CH3CO) is the most preferred path as the reactions with OH and NH2 possess activation energies (≥9 kJ mol−1) hard to surmount in the ISM conditions unless external processes provide energy to the system. Thus, acetaldehyde (CH3CHO) and, probably, ethanol (CH3CH2OH) formation via further hydrogenations, are the possible unique operating synthetic routes. Moreover, from the computed, relatively large binding energies of OH and NH2 on CO ice, slow diffusion is expected, hampering possible radical–radical couplings with CH3CO. The astrophysical implications of these findings are discussed considering the incoming James Webb Space Telescope observations.

Exploring the Impact of Nitrogen Doping on the Optical Properties of Carbon Dots Synthesized from Citric Acid.

The differences between bare carbon dots (CDs) and nitrogen-doped CDs synthesized from citric acid as a precursor are investigated, aiming at understanding the mechanisms of emission and the role of the doping atoms in shaping the optical properties. Despite their appealing emissive features, the origin of the peculiar excitation-dependent luminescence in doped CDs is still debated and intensively being examined. This study focuses on the identification of intrinsic and extrinsic emissive centers by using a multi-technique experimental approach and computational chemistry simulations. As compared to bare CDs, nitrogen doping causes the decrease in the relative content of O-containing functional groups and the formation of both N-related molecular and surface centers that enhance the quantum yield of the material. The optical analysis suggests that the main emission in undoped nanoparticles comes from low-efficient blue centers bonded to the carbogenic core, eventually with surface-attached carbonyl groups, the contribution in the green range being possibly related to larger aromatic domains. On the other hand, the emission features of N-doped CDs are mainly due to the presence of N-related molecules, with the computed absorption transitions calling for imidic rings fused to the carbogenic core as the potential structures for the emission in the green range.

Microemulsion interface model for chemical enhanced oil recovery design

The surfactant phase behavior laboratory test for chemical enhanced oil recovery (EOR) formulation design is time consuming. However, it is possible to use computational chemistry simulation to minimize the duration. The only known non-empirical approach to predict surfactant phase behavior is by surface tension analysis, but the optimum phase behavior boundary is unclear and its applicability in actual complex crude oil is unproven. This research overcomes these issues by developing a microemulsion interface model using digital oil model with accurate representation of atomistic components of actual crude oil as inputs to the simulation. The microemulsion interface model is developed based on physical chemistry of surface tension and torque concepts coupled with solution of interface bending rigidity in relation to surfactant solubilization and interface energy. The model is implemented in coarse-grained molecular dynamics simulation technique. The microemulsion interface model is verified with surfactant phase behavior laboratory data using actual crude oil. Good agreement for 12 out of 14 chemical EOR formulations between simulations and phase behavior laboratory results is achieved. This indicates that the main characteristics and physics of the formation of optimal microemulsion were captured correctly in the microemulsion interface model. The duration for surfactant phase behavior determination can be reduced from 14 days in laboratory down to 1.5 day by using the microemulsion interface model, resulting in 90%-time reduction. This faster and more informed formulation development process can minimize time and costly resources as chemical EOR formulations proceed into field implementation.

Three practical workflow schedulers for easy maximum parallelism

AbstractRuntime scheduling and workflow systems are an increasingly popular algorithmic component in HPC because they allow full system utilization with relaxed synchronization requirements. There are so many special‐purpose tools for task scheduling, one might wonder why more are needed. Use cases seen on the Summit supercomputer needed better integration with MPI and greater flexibility in job launch configurations. Preparation, execution, and analysis of computational chemistry simulations at the scale of tens of thousands of processors revealed three distinct workflow patterns. A separate job scheduler was implemented for each one using extremely simple and robust designs: file‐based, task‐list based, and bulk‐synchronous. Comparing to existing methods shows unique benefits of this work, including simplicity of design, suitability for HPC centers, short startup time, and well‐understood per‐task overhead. All three new tools have been shown to scale to full utilization of Summit, and have been made publicly available with tests and documentation. This work presents a complete characterization of the minimum effective task granularity for efficient scheduler usage scenarios. These schedulers have the same bottlenecks, and hence similar task granularities as those reported for existing tools following comparable paradigms.

Liquid state properties of SEI components in dimethoxyethane

The solid-electrolyte interphase (SEI) layer is a critical constituent of battery technology, which incorporates the use of lithium metals. Since the formation of the SEI is difficult to avoid, the engineering and harnessing of the SEI are absolutely critical to advancing energy storage. One problem is that much fundamental information about SEI properties is lacking due to the difficulty in probing a chemically complex interfacial system. One such property that is currently unknown is the dissolution of the SEI. This process can have significant effects on the stability of the SEI, which is critical to battery performance but is difficult to probe experimentally. Here, we report the use of ab initio computational chemistry simulations to probe the solution state properties of SEI components LiF, Li2O, LiOH, and Li2CO3 in order to study their dissolution and other solution-based characteristics. Ab initio molecular dynamics was used to study the solvation structures of the SEI with a combination of radial distribution functions, discrete solvation structure maps, and vibrational density of states, which allows for the determination of free energies. From the change in free energy of dissolution, we determined that LiOH is the most likely component to dissolve in the electrolyte followed by LiF, Li2CO3, and Li2O although none were favored thermodynamically. This indicates that dissolution is not probable, but Li2O would make the most stable SEI with regard to dissolution in the electrolyte.

Rapid prototyping of arbitrary 2D and 3D wireframe DNA origami.

Wireframe DNA origami assemblies can now be programmed automatically from the top-down using simple wireframe target geometries, or meshes, in 2D and 3D, using either rigid, six-helix bundle (6HB) or more compliant, two-helix bundle (DX) edges. While these assemblies have numerous applications in nanoscale materials fabrication due to their nanoscale spatial addressability and high degree of customization, no easy-to-use graphical user interface software yet exists to deploy these algorithmic approaches within a single, standalone interface. Further, top-down sequence design of 3D DX-based objects previously enabled by DAEDALUS was limited to discrete edge lengths and uniform vertex angles, limiting the scope of objects that can be designed. Here, we introduce the open-source software package ATHENA with a graphical user interface that automatically renders single-stranded DNA scaffold routing and staple strand sequences for any target wireframe DNA origami using DX or 6HB edges, including irregular, asymmetric DX-based polyhedra with variable edge lengths and vertices demonstrated experimentally, which significantly expands the set of possible 3D DNA-based assemblies that can be designed. ATHENA also enables external editing of sequences using caDNAno, demonstrated using asymmetric nanoscale positioning of gold nanoparticles, as well as providing atomic-level models for molecular dynamics, coarse-grained dynamics with oxDNA, and other computational chemistry simulation approaches.

A Multiscale Approach for Estimating Permeability Properties of Polymers with Complex Aromatic Backbones: A Case Study on Diffusivity of Small Gas Molecules in Polyphenylene Ether

AbstractState‐of‐the‐art multiscale computational chemistry simulations is employed to predict diffusivity of small gaseous molecules in a generic polyphenylene ether (PPE). The diffusivities are obtained from trajectory analysis of gaseous molecules in molecular dynamics simulations using coarse‐grained dissipative particle dynamics (DPD) simulations to design the amorphous starting structure. Required intra‐ and intermolecular parameters of the DPD simulations are automatically generated using the automated fragmentation and parametrization protocol. A comparison of calculated diffusion coefficients with experimental data for five gaseous molecules in PPE shows adequate accuracy of computational‐chemistry‐based approaches in the prediction of diffusion coefficients. These estimates, validated against measurements reported in the literature, serve as proof of concept for applicability of these new multiscale modeling strategies for complex polymers with aromatic backbones.

Towards chemically accurate QM/MM simulations on GPUs

Computational chemistry simulations are extensively used to model natural phenomena. To maintain performance similar to molecular mechanics, but achieve comparable accuracy to quantum mechanical calculations, many researchers are using hybrid QM/MM methods. In this article we evaluate our GPU-accelerated ONIOM implementation by measurements on the crambin and HIV integrase proteins with different size QM model systems. We demonstrate that by using a larger QM region, a better energy accuracy can be achieved at the expense of simulation time. This trade-off is important to consider for the researcher running QM/MM calculations. Furthermore, we show that the ONIOM energy monotonically approaches the pure quantum mechanical energy of the whole system. The experiments are made feasible by utilizing the cutting-edge BrianQC quantum chemistry module for Hartree-Fock level SCF and our GPU-accelerated MMFF94 force field implementation for molecular mechanics calculations.

Computational chemistry experiments performed directly on a blockchain virtual computer.

Blockchain technology has had a substantial impact across multiple disciplines, creating new methods for storing and processing data with improved transparency, immutability, and reproducibility. These developments come at a time when the reproducibility of many scientific findings has been called into question, including computational studies. Here we present a computational chemistry simulation run directly on a blockchain virtual machine, using a harmonic potential to model the vibration of carbon monoxide. The results demonstrate for the first time that computational science calculations are feasible entirely within a blockchain environment and that they can be used to increase transparency and accessibility across the computational sciences.

COBRAMM 2.0 - A software interface for tailoring molecular electronic structure calculations and running nanoscale (QM/MM) simulations.

We present a new version of the simulation software COBRAMM, a program package interfacing widely known commercial and academic software for molecular modeling. It allows a problem-driven tailoring of computational chemistry simulations with effortless ground and excited-state electronic structure computations. Calculations can be executed within a pure QM or combined quantum mechanical/molecular mechanical (QM/MM) framework, bridging from the atomistic to the nanoscale. The user can perform all necessary steps to simulate ground state and photoreactions in vacuum, complex biopolymer, or solvent environments. Starting from ground-state optimization, reaction path computations, initial conditions sampling, spectroscopy simulation, and photodynamics with deactivation events, COBRAMM is designed to assist in characterization and analysis of complex molecular materials and their properties. Interpretation of recorded spectra range from steady-state to time-resolved measurements. Various tools help the user to set up the system of interest and analyze the results.

A First-Principles Study on Interaction between Carbon Nanotubes (10,10) and Gallates Derivatives as Vehicles for Drug Delivery

First principles calculations were carried out for investigation the novel 7-hydroxycoumarinyl gallates derivatives in gas and liquid phases using density functional theory (DFT) method. Computational chemistry simulations were carried out to compare calculated quantum chemical parameters for gallates derivatives. All calculations were performed using DMol3 code which is based on DFT. The Double Numerical basis set with double numerical plus d-function (DND) was used. Calculations were carried out to study the interaction of covalently binding gallates derivatives to the armchair single-walled carbon nanotube (10, 10). The local reactivity was studied through the fukui indices in order to predict both the reactive centers and the practicable sites of nucleophilic and electrophilic attacks. The adsorption energies, the quantum molecular descriptors analysis and the structural changes at the adsorption site are indicative of chemisorption on the armchair single-walled carbon nanotube (10, 10) surface. The HOMO and LUMO are witness to the substantial changes in the electronic properties of the SWCNT systems. Adsorption energies indicate that 7-hydroxycoumarinyl gallates derivatives are physicosorbed on carbon nanotube (10, 10). This property enables the delivery of these derivatives with anti-cancer potential from the nanotube at the targeted sites. These results are extremely relevant in order to diagnosis the potential applications of carbon nanotubes as efficient boats for targeted drug delivery.

Theoretical study of functionalized single-walled carbon nanotube (5, 5) with Mitoxantrone drug

Objective(s): First principles calculations were performed to study four multiple sclerosis drugs namely, Ampyra, Fingolimod, Mitoxantrone and Eliprodil in gas and liquid phases using Density Functional Theory (DFT). Computational chemistry simulations were carried out to compare calculated quantum chemical parameters for Ampyra, Fingolimod, Mitoxantrone and Eliprodil. Materials and Methods: All calculations were performed using DMol3 code which is based on DFT. The Double Numerical basis set with Polarization functions (DNP) was used.Results: Mitoxantrone has highest HOMO energy, global softness, solvation energy and molecular mass and lowest LUMO energy, energy gap, global hardness and total energy in comparison to Ampyra, Fingolimod and Eliprodil in gas and solvent phases. Calculations were carried out to study the interaction of covalently binding Mitoxantrone to functionalized carbon nanotube. The Mitoxantrone local reactivity was studied through the Fukui indices in order to predict both the reactive centers and the possible sites of nucleophilic and electrophilic attacks. The Mitoxantrone binding energy is calculated to be 6.507 eV in gas phase and -9.943 eV in solvent phase that is a decrease in BE as the drug phase changes from gas to liquid.Conclusion: The simulation results show Mitoxantrone is quite a reactive drug. The quantum chemical parameters of pristine nanotube and f-SWNT-Mitoxantrone showed that reactivity of f-SWNT-Mitoxantrone increased in comparison to pristine nanotube in both phases.

Toward a ligand specific of Pb2+ with respect to the Zn2+ and Ca2+ cations: A track from quantum chemistry

From computational chemistry simulations, a ligand has emerged that could be selective of Pb2+ toward Zn2+ and Ca2+, an important point when designing new chelators usable in vivo as remediation agents against lead poisoning (saturnism). Some electronic properties of 1,4,7,10,13,16-hexaoxa-cyclooctadeca-2,5,8,11,14,17-hexaene (hoc-18) are examined here in details, together with those of some thio-analogs. Several interpretative ab initio methodologies that allow clarifying a number of characteristics of hoc-18 towards Zn2+, Ca2+ and Pb2+ are considered from the viewpoint of coordination chemistry.

Effect of Formic Acid Addition on Water Cluster Stability and Structure

Computational chemistry simulations were performed to determine the effect that the addition of a single formic acid molecule has on the structure and stability of protonated water clusters. Previous experimental studies showed that addition of formic acid to protonated pure water results in higher intensities of large-sized clusters when compared to pure water and methanol-water mixed clusters. For larger, protonated clusters, molecular dynamics simulations were performed on H(+)(H(2)O)(n), H(+)(H(2)O)(n)CH(3)OH, and H(+)(H(2)O)(n)CHOOH clusters, 19-28 molecules in size, using a reactive force field (ReaxFF). Based on these computations, formic acid-water clusters were found to have significantly higher binding energies per molecule. Addition of formic acid to a water cluster was found to alter the structure of the hydrogen-bonding network, creating selective sites within the cluster, enabling the formation of new hydrogen bonds, and increasing both the stability of the cluster and its rate of growth.

QSAR, Experimental and Computational Chemistry Simulation Studies on the Inhibition Potentials of Some Amino Acids for the Corrosion of Mild Steel in 0.1 M HCl

QSAR, Experimental and Computational Chemistry Simulation Studies on the Inhibition Potentials of Some Amino Acids for the Corrosion of Mild Steel in 0.1 M HCl