Global Energy Minimum Research Articles

APPLYING THE GENETIC ALGORITHM AND QUANTUM CHEMICAL CALCULATIONS TO STUDY THE STRUCTURE OF THE Sc2B6 CLUSTER AND ITS CO ADSORPTION

We used the genetic algorithm and quantum chemical calculations to study the structures of the Sc2B6 cluster. The global minimum energy structure has the shape of a hexagonal bipyramid with an Sc atom at each apex and a B6 ring that belongs to the D6h point group symmetry. The second most stable structure has the Cs point group symmetry and can be formed by substituting a Sc atom for a B atom in the ring and a B atom for Sc in one of the apexes. From the computational results, the Sc2B6 cluster is found to be a good candidate to form a nanomaterial for treating CO gas.

Bi-level task planning strategy for blended-wing-body underwater gliders

ABSTRACT This study focuses on the task planning problem of the blended-wing-body underwater glider (BWBUG), which must autonomously navigate through a sequence of underwater visitation points while ensuring safety and economy. Firstly, the task planning problem of the BWBUG is analysed, with attention given to operational space and task requirements. Subsequently, a bi-level planning framework that incorporates both the bottom-level and top-level planners is proposed. The bottom-level planner optimises the glide path between any two visit points by considering safety and glide angle constraints, with the objective of minimising energy usage. The top-level planner focuses on the task constraints and optimises the global visitation path of the BWBUG to achieve the objective of global energy minimisation. Simulations demonstrate the effectiveness of the bi-level based task planning strategy proposed in this study. The solution algorithms are highly competitive, capable of planning rational global visitation paths for the BWBUG.

An automated calculation pipeline for differential pair interaction energies with molecular force fields using the Tinker Molecular Modeling Package

An automated pipeline for comprehensive calculation of intermolecular interaction energies based on molecular force-fields using the Tinker molecular modelling package is presented. Starting with non-optimized chemically intuitive monomer structures, the pipeline allows the approximation of global minimum energy monomers and dimers, configuration sampling for various monomer–monomer distances, estimation of coordination numbers by molecular dynamics simulations, and the evaluation of differential pair interaction energies. The latter are used to derive Flory–Huggins parameters and isotropic particle–particle repulsions for Dissipative Particle Dynamics (DPD). The computational results for force fields MM3, MMFF94, OPLS-AA and AMOEBA09 are analyzed with Density Functional Theory (DFT) calculations and DPD simulations for a mixture of the non-ionic polyoxyethylene alkyl ether surfactant C10E4 with water to demonstrate the usefulness of the approach.Scientific ContributionTo our knowledge, there is currently no open computational pipeline for differential pair interaction energies at all. This work aims to contribute an (at least academically available, open) approach based on molecular force fields that provides a robust and efficient computational scheme for their automated calculation for small to medium-sized (organic) molecular dimers. The usefulness of the proposed new calculation scheme is demonstrated for the generation of mesoscopic particles with their mutual repulsive interactions.

Transferable, Living Data Sets for Predicting Global Minimum Energy Nanocluster Geometries.

Modeling of nanocluster geometries is essential for studying the dependence of catalytic activity on the available active sites. In heterogeneous catalysis, the interfacial interaction of the support with the metal can result in modification of the structural and electronic properties of the clusters. To tackle the study of a diverse array of cluster shapes, data-driven methodologies are essential to circumvent prohibitive computational costs. At their core, these methods require large data sets in order to achieve the necessary accuracy to drive structural exploration. Given the similarity in binding character of the transition metals, cluster shapes encountered for various systems show a large amount of overlap. This overlap has been utilized to construct a living data set which may be carried over across multiple studies. Iterative refinement of this data set provides a low-cost pathway for initialization of cluster studies. It is shown that utilization of transferable structural information can reduce model construction costs by more than 90%. The benefits of this approach are particularly notable for alloy systems, which possess significantly larger configurational spaces compared to the pure-phase counterparts.

The unique geometries and magnetic anisotropy energy of FenPt (n = 3–13) clusters: A first-principles investigation

Enthusiasm for exploring magnetic anisotropy energy (MAE) and spin–orbit coupling (SOC) effects in magnetic studies of transition metal alloy clusters remains high. In this paper, the first-principle method was used to investigate the global minimum energy structure of FenPt (n = 3–13) clusters and their interesting magnetic properties. Comparative structural analyses show that FenPt (n = 3–13) clusters have unique structures, and their relative stability analyses indicate that the increase in the number of atoms influences the geometrical arrangement of the clusters. The exploration of magnetic properties has focused on two areas. First, FenPt (n = 3–13) is found to have a large magnetic moment, while the magnetic moment increment surprisingly varies in the same way in different cases with and without the inclusion of SOC effects. Second, the calculations show that FenPt (n = 3, 4, 9, 13) has MAE, ranging from 1.420-2.687 meV/atom. The SOC matrix results show the interaction of Pt dx2-y2 and Pt dxy, and the interaction of Pt dz2 and Pt dyz, exhibit an indispensable force in determining the MAE.

Bilinear optimization of protein structure prediction: An exact approach via AB off-lattice model

Protein structure prediction (PSP) remains a central challenge in computational biology due to its inherent complexity and high dimensionality. While numerous heuristic approaches have appeared in the literature, their success varies. The AB off-lattice model, which characterizes proteins as sequences of A (hydrophobic) and B (hydrophilic) beads, presents a simplified perspective on PSP. This work presents a mathematical optimization-based methodology capitalizing on the off-lattice AB model. Dissecting the inherent non-linearities of the energy landscape of protein folding allowed for formulating the PSP as a bilinear optimization problem. This formulation was achieved by introducing auxiliary variables and constraints that encapsulate the nuanced relationship between the protein’s conformational space and its energy landscape. The proposed bilinear model exhibited notable accuracy in pinpointing the global minimum energy conformations on a benchmark dataset presented by the Protein Data Bank (PDB). Compared to traditional heuristic-based methods, this bilinear approach yielded exact solutions, reducing the likelihood of local minima entrapment. This research highlights the potential of reframing the traditionally non-linear protein structure prediction problem into a bilinear optimization problem through the off-lattice AB model. Such a transformation offers a route toward methodologies that can determine the global solution, challenging current PSP paradigms. Exploration into hybrid models, merging bilinear optimization and heuristic components, might present an avenue for balancing accuracy with computational efficiency.

Bonobo Optimizer: A New Tool Toward the Global Optimization of Small Atomic Clusters.

In the realm of structural and bonding investigations within chemical systems, elucidating global minimum energy configurations stands as a paramount goal. As the systems increase in size and complexity, this pursuit becomes progressively challenging. Herein, we introduce Bonobo optimizer (BO), a metaheuristic algorithm inspired by the social and reproductive behaviors of bonobos, to the domain of chemical problem solving. Focusing on small carbon clusters, this study systematically evaluates BO's performance, showcasing its robustness and efficiency. Parametric studies highlight the algorithm's adaptability, consistently converging to global minimum structures. Rigorous statistical validation supports the results, and a comparative analysis against established global optimization algorithms underlines BO's superior efficiency. This exploration extends the applicability of BO to the optimization of atomic clusters, providing a promising avenue for future advancements in computational chemistry.

Hybrid Density Functional Theory Comparison of Oxygen Release and Solvent Decomposition Kinetics on LixNiO2 Surfaces.

High-nickel-content layered oxides are among the most promising electric vehicle battery cathode materials. However, their interfacial reactivity with electrolytes and tendency toward oxygen release (possibly yielding reactive 1O2) remain degradation concerns. Elucidating the most relevant (i.e., fastest) interfacial degradation mechanism will facilitate future mitigation strategies. We apply screened hybrid density functional (HSE06) calculations to compare the reaction kinetics of LixNiO2 surfaces with ethylene carbonate (EC) with those of O2 release. On both the (001) and (104) facets, EC oxidative decomposition exhibits lower activation energies than O2 release. Our calculations, coupled with previously computed liquid-phase reaction rates of 1O2 with EC, strongly question the role of "reactive 1O2" species in electrolyte oxidative degradation. The possible role of other oxygen species is discussed. To deal with the challenges of modeling LixNiO2 surface reactivity, we emphasize a "local structure" approach instead of pursuing the global energy minimum.

Comments on “Planar Tetracoordinate Hydrogen: Pushing the Limit of Multicentre Bonding”

AbstractIn a recent communication (Angew. Chem. Int. Ed. 2024, 63, e202317312), Kalita et al. studied In4H+ system within the frame of single‐reference approximation (SRA) and found that the global energy minimum (1 a) adopted the singlet state and a planar tetracoordinate hydrogen (ptH), while the second lowest isomer (1 b) located 3.0 kcal/mol above 1 a and adopted the triplet state as well as non‐planar structure with a quasi‐ptH. They assessed the reliability of SRA by checking the T1‐diagnostic values of coupled cluster calculations. However, according to our multi‐configurational second‐order perturbation theory calculations at the CASPT2(12,13)/aug‐cc‐pVQZ (aug‐cc‐pVQZ‐PP for In) level, both 1 a and 1 b exhibit obvious multi‐referential characters, as reflected by their largest reference coefficients of 0.928 (86.1 %) and 0.938 (88.0 %), respectively. Moreover, 1 b is 5.05 kcal/mol lower than 1 a at this level, that is, what can be observed in In4H+ system is the quasi‐ptH.

Adsorption behavior of formaldehyde gas on two-dimensional semiconductor monolayers MS2 (M=W, Mo)

Detecting methanal molecule, an indoor air pollutant and potential carcinogen, is crucial for safeguarding human health, ensuring occupational safety, and maintaining environmental quality. In this study, density functional theory calculations have been performed to explore the adsorption behavior of formaldehyde (methanal) gas on the surface of two-dimensional semiconductor monolayers MS2 (M=W, Mo). Using the Computational DFT-based Nanoscope tool, we compute binding energies and determine configurations at global minimum energy of molecule adsorbed monolayer MS2. Five nonlocal van der Waals functionals; revPBE-vdW, optPBE-vdW, vdW-DF2, optB88-vdW, and optB86b-vdW are used to compute the adsorption energy profiles. The calculated results show that: (i) the optPBE-vdW functional products the largest adsorption energy magnitude, (ii) Methanal molecule exhibits physical adsorption on both MoS2 and WS2 materials (iii) Adsorption of methanal molecules may enhance the electrical conductivity of MoS2 and WS2 upon the electron donation to molecule by substrates. The adsorption energy magnitude, bandgap reduction, and charge transfer of the methanal-MoS2 adsorption system are respectively 1.04, 1.27, and 1.47 times larger than those of the methanal-WS2 adsorption system, while the diffusion barrier energy is 0.25 times smaller. These characteristic adsorption parameters imply that methanal exhibits higher sensitivity to the MoS2 substrate. This study also provides an in-depth discussion regarding the interaction between methanal and the MS2 substrate, focusing on aspects of relaxed geometrical structures, potential energy surface, adsorption energy, response length, recovery time, work function, charge transfer, density of states, and energy band structure.

Biophysical and structural characterization of tetramethrin serum protein complex and its toxicological implications.

Tetramethrin (TMT) is a commonly used insecticide and has a carcinogenic and neurodegenerative effect on humans. The binding mechanism and toxicological implications of TMT to human serum albumin (HSA) were examined in this study employing a combination of biophysical and computational methods indicating moderate binding affinity and potential hepato and renal toxicity. Fluorescence quenching experiments showed that TMT binds to HSA with a moderate affinity, and the binding process was spontaneous and predominantly enthalpy-driven. Circular dichroism spectroscopy revealed that TMT binding did not induce any significant conformational changes in HSA, resulting in no changes in its alpha-helix content. The binding site and modalities of TMT interactions with HSA as computed by molecular docking and molecular dynamics simulations revealed that it binds to Sudlow site II of HSA via hydrophobic interactions through its dimethylcyclopropane carboxylate methyl propanyl group. The structural dynamics of TMT induce proper fit into the binding site creating increased and stabilizing interactions. Additionally, molecular mechanics-Poisson Boltzmann surface area calculations also indicated that non-polar and van der Waals were found to be the major contributors to the high binding free energy of the complex. Quantum mechanics (QM) revealed the conformational energies of the binding confirmation and the degree of deviation from the global minimum energy conformation of TMT. The results of this study provide a comprehensive understanding of the binding mechanism of TMT with HSA, which is important for evaluating the toxicity of this insecticide in humans.

Revisiting the vibrational spectrum of formic acid anhydride

The potential energy surface of formic acid anhydride has been investigated at highly accurate quantum chemical methods. The rotation of CHO group in global minimum conformer of formic acid anhydride can lead two different local minimum conformers. Both local minimum conformers are around three kcal/mol higher in energy than the global minimum conformer. One conformer is planar and another has two rotamers which rapidly interconvert to each others via planar transition state. In some earlier studies, this planar transition state has incorrectly assigned to be a local minimum structure. We calculated anharmonic vibrational frequencies for the global and local minimum energy conformers and compared the theoretical wavenumbers with experimental gas phase and argon matrix measurements. Our results suggest that some of the experimentally detected peaks are overtone and combination bands. In previous studies with harmonic calculations, those peaks have assigned to be fundamental bands with zero intensities. We confirmed that the higher energy conformer produced in argon matrix by ultra violet induced rotamerization of global minimum conformer belongs to the planar conformer.

Unveiling the Morphology of Carbon-Supported Ru Nanoparticles by Multiscale Modeling.

Simulating the behavior of metal nanoparticles on supports is crucial for boosting their catalytic performance and various nanotechnology applications; however, such simulations are limited by the conflicts between accuracy and efficiency. Herein, we introduce a multiscale modeling strategy to unveil the morphology of Ru supported on pristine and N-doped graphene. Our multiscale modeling started with the electronic structures of a supported Ru single atom, revealing the strong metal-support interaction around pyridinic nitrogen sites. To determine the stable configurations of Ru2-13 clusters on three different graphene supports, global energy minimum searches were performed. The sintering of the global minimum Ru13 clusters on supports was further simulated by ab initio molecular dynamics (AIMD). The AIMD data set was then collected for deep potential molecular dynamics to study the melting of Ru nanoparticles. This study presents comprehensive descriptions of carbon-supported Ru and develops modeling approaches that bridge different scales and can be applied to various supported nanoparticle systems.

On the Global Minimum of the Classical Potential Energy for Clusters Bound by Many-Body Forces

On the Global Minimum of the Classical Potential Energy for Clusters Bound by Many-Body Forces

Breaking the Hoff/Le Bel rule by an electron-compensation strategy: the global energy minimum of NGa4S4.

In tetracoordinate chemistry, there is an attractive scientific problem of how to make the planar configuration more stable than the tetrahedral configuration. For tetracoordinate nitrogen, the abundant studies indicate that the planar tetracoordinate nitrogen (ptN) is far less stable than the tetrahedral tetracoordinate nitrogen (ttN). Herein, we introduced four S atoms to the unstable ptN-NGa4+ and stable ttN-NGa4+ by following an electron-compensation strategy. Surprisingly, ptN-NGa4S4+ is more stable than ttN-NGa4S4+. Thermodynamically, ptN-NGa4S4+ is the global energy minimum, which is 46.7 kcal mol-1 lower in energy than ttN-NGa4S4+. Dynamically, the BOMD simulations indicated that ptN-NGa4S4+ has excellent dynamic stability at 4, 298, 500 and 1000 K, but the ttN-NGa4S4+ is isomerized at 1000 K. Electronically, the HOMO-LUMO gap of ptN-NGa4S4+ (6.91 eV) is much wider than that of ttN-NGa4S4+ (5.25 eV). Moreover, AdNDP analyses showed that the eight 2c-2e Ga-S σ-bonds eliminated the 4s2 lone pair/4s2 lone pair repulsion between the four Ga atoms and provided a strong spatial protection for ptN-NGa4S4+; and that the four 3c-2e Ga-S-Ga π back-bonds could compensate electrons for Ga, weakening the electron-deficiency of Ga. Simultaneously, the double 6σ/2π aromaticity further enhanced the stability of ptN-NGa4S4+. Thus, as the dynamically stable global energy minimum displaying double aromaticity, ptN-NGa4S4+ will be more promising than ttN-NGa4S4+ in gas phase generation.

Observation of metastable structures of the ethylene glycol-water dimer in helium nanodroplets.

Ethylene glycol (EG) is the simplest organic diol. Here we measure infrared spectra of the EG monomer and its dimer with water, the complex, EG(H2O), embedded in superfluid helium nanodroplets. For the monomer, only a single, gauche, conformation is observed. For EG(H2O), no trace of the global energy minimum is seen, a structure that would maximize the hydrogen bonding contacts. Instead, only metastable structures are formed, suggesting that dimerization in a superfluid environment leads to kinetic trapping in local energy minima. In addition, we obtain evidence for a dimer where the conformation of EG switches from gauche to trans on account of dimerization with a water molecule. This observation is assumed to be driven over an energy barrier by utilizing the energy released as hydrogen bonding occurs.

Chemical Correlation of Cistendiol Obtained from Cativic Acid in Two Different Pathways

Objective This study aims to convert cativic acid, which was isolated from Ageratina jocotepecana, into cistendiol (5), an analog of cistenolic acid isolated from Cistus symphytifolius. The position of hydroxyl at C-7 in compound 5 could be achieved by applying the Schenck reaction with singlet oxygen (1O2) through photooxidation reaction of 6. Additionally, epoxidation reaction of 1, followed by further reduction and acid treatment, can serve as another pathway to obtain compound 5. Methods Cativic acid was isolated from Ageratina jocotepecana flowers, reduction methodology was realized with THF and LiAlH4, epoxidation reaction was carried out with mCPBA in CH2Cl2 and K2CO3, oxidation of alcohol with PCC in CH2Cl2 and MgSO4, photooxidation reaction was realized with blue and white light using singlet oxygen (1O2) and photosensitizers such as eosin, methylene blue and Ru(bpy)3(PF6)2 in acetonitrile. Geometry optimizations for transition states were performed using MMFF94 with Monte Carlo protocol, and GDFT was used B3LYP/DGDZVP level of theory with Gaussian 09. Results Cistendiol was synthesized by photooxidation reaction of 6 with Ru(bpy)3(PF6)2 and air such oxidant with a ratio of 8:1, while epoxidation of 1 further reduction and acid treatment afforded cistendiol with a ratio of 9:1, the ratio was determined by NMR, additionally the global minimum energy structures GDFT calculated values supports the results described by NMR ratio. The stereochemistry was also confirmed by NOESY experiment and the comparison is in agreement with literature data. Conclusion Herein, we described the conversion of cativic acid isolated from Ageratina jocotepecana employing a new photooxidation methodology and classic epoxidation techniques, to produce an analog of cistenolic acid isolated from Cistus symphytifolius. The results, which include Supplemental material, enable comparison of stereochemistry, specifically the 13 S for C-13 of Ageratina jocotepecana with other compounds such as cistenolic or salvic acid, which had been the subject of study by researchers.

Theoretical Studies on the Isomerization Kinetics of Low-Lying Isomers of the SiC4H2 System.

The low-lying isomers of SiC4H2 are investigated to understand the kinetics of isomerization pathways using density functional theory. In our earlier work, we studied the various possible isomers (J. Phys. Chem. A, 2020, 124, 987-1002) and the chemical bonding of low-lying isomers of SiC4H2 (J. Phys. Chem. A, 2022, 126, 9366-9374). Among them, four isomers, 1-ethynyl-3-silacycloprop-1-en-3-ylidene (1), 3-silapent-1,4-diyn-3-ylidene (2), 1-silapent-1,2,3,4-tetraen-1-ylidene (4), and 1-silapent-2,4-diyn-1-ylidene (5) have already been identified in the laboratory. The previously known theoretical isomer 2-methylene-1-silabicyclo[1.1.0]but-1(3)-en-4-ylidene (3) and the newly identified unknown isomer through the present kinetic studies 5-silabicyclo[2.1.0]pent-1(4),2-dien-5-ylidene (N6) remain elusive in the laboratory to date. The isomerization pathways of the low-lying isomers of SiC4H2 are predicted through the transition state structures. Intrinsic reaction coordinate analysis identifies the minimum energy reaction pathways connecting the transition state from one isomer to another of the investigated system. The present kinetic data reveal the isomerization of global minimum energy isomer 1 to thermodynamically stable low-lying isomers, 2 and 5. Interestingly, isomer 3 interconverts to the experimentally known low-energy isomer 4, the second most thermodynamically stable isomer among them. The thermodynamic and kinetic parameters of the low-lying isomers of SiC4H2 are also documented in this work. The rate coefficient and equilibrium constant for isomerization reactions are calculated using the Rice-Ramsperger-Kassel-Marcus theory. The equilibrium constant delineates the difficulties in forming N6 and 3 through the isomerization pathways. Furthermore, ab initio molecular dynamics studies dictate the stability of low-lying isomers of SiC4H2 within the time scale of the simulation.

Monte Carlo-Simulated Annealing and Machine Learning-Based Funneled Approach for Finding the Global Minimum Structure of Molecular Clusters.

Understanding the physical underpinnings and geometry of molecular clusters is of great importance in many fields, ranging from studying the beginning of the universe to the formation of atmospheric particles. To this end, several approaches have been suggested, yet identifying the most stable cluster geometry (i.e., global potential energy minimum) remains a challenge, especially for highly symmetric clusters. Here, we suggest a new funneled Monte Carlo-based simulated annealing (SA) approach, which includes two key steps: generation of symmetrical clusters and classification of the clusters according to their geometry using machine learning (MCSA-ML). We demonstrate the merits of the MCSA-ML method in comparison to other approaches on several Lennard-Jones (LJ) clusters and four molecular clusters-Ser8(Cl-)2, H+(H2O)6, Ag+(CO2)8, and Bet4Cl-. For the latter of these clusters, the correct structure is unknown, and hence, we compare the experimental and simulated fragmentation patterns, and the fragmentation of the proposed global minimum matches experiments closely. Additionally, based on the fragmentation of the predicted betaine cluster, we were able to identify hitherto unknown neutral fragmentation channels. In comparison to results obtained with other methods, we demonstrated a superior ability of MCSA-ML to predict clusters with high symmetry and similar abilities to predict clusters with asymmetrical structures.

Fast-Converging Simulated Annealing for Ising Models Based on Integral Stochastic Computing.

Probabilistic bits (p-bits) have recently been presented as a spin (basic computing element) for the simulated annealing (SA) of Ising models. In this brief, we introduce fast-converging SA based on p-bits designed using integral stochastic computing. The stochastic implementation approximates a p-bit function, which can search for a solution to a combinatorial optimization problem at lower energy than conventional p-bits. Searching around the global minimum energy can increase the probability of finding a solution. The proposed stochastic computing-based SA method is compared with conventional SA and quantum annealing (QA) with a D-Wave Two quantum annealer on the traveling salesman, maximum cut (MAX-CUT), and graph isomorphism (GI) problems. The proposed method achieves a convergence speed a few orders of magnitude faster while dealing with an order of magnitude larger number of spins than the other methods.