Semiempirical Hamiltonian Research Articles

A computational study of adsorption on activated carbons containing basic oxygenated surface groups of two priority organochlorine pesticides from water

In previous work, molecular modeling was used to investigate how acidic and nitrogen-containing surface groups (SG) on an activated carbon (AC) model affect the adsorption of chlordecone (CLD) and β-hexachlorocyclohexane (β-HCH), considering the effects of pH and hydration. Interactions involving acidic SGs at neutral pH indicated chemisorption, while interactions with nitrogen basic SGs suggested physisorption. This study presents a theoretical investigation of the interactions between these pesticides and oxygenated SGs on AC. A coronene molecule with functional groups—specifically pyrone, chromene, or ketone at the edges was used as a simplified model of AC. The Multiple Minima Hypersurface methodology was employed to study the interactions between CLD and β-HCH with SGs on AC using the PM7 semi-empirical Hamiltonian. Further re-optimization of the obtained structures for pesticide-AC complexes was performed using Density Functional Theory. The Quantum Theory of Atoms in Molecules was applied to characterize the interaction types using the Nakanishi criteria. No interactions were observed at acidic pH for both pollutants, whereas dispersive interactions were found at neutral and basic pH, indicating a physisorption process. Molecular dynamics simulations were also conducted to illustrate these findings. Ultimately, our previous studies showed that the adsorption process of CLD and β-HCH on AC is more effectively enhanced with acidic SGs rather than basic SGs. Moreover, MD simulations of β-HCH and CLD pesticides at concentrations higher than their solubilities reveal aggregation in both pure aqueous solutions and those containing AC. Analysis of MD trajectories and RDFs shows that hydrophobic interactions lead to aggregation of these molecules. RDFs indicate that β-HCH aggregates more in the solution due to its lower solubility compared to CLD. This aggregation reduces pesticide adsorption on AC surfaces, with β-HCH showing a more significant decrease in adsorption, dropping by more than half. Similar effects were observed with other biochar models for both pesticides.

Reactivity assessment of oligomeric systems associated with crystalline and amorphous cellulose for bioethanol production: a DFT study.

The production of bioethanol from renewable raw materials is a decisive factor in the economic development of many countries. However, the complexity of the processes and the numerous experimental variables involved require a deeper understanding of the chemical reactions that take place during bioethanol production to define optimal parameters. Here, we have employed density functional theory-based calculations to investigate the local reactivity of oligomeric systems by consideringcrystalline and amorphous cellulose models to better understand some details regarding pulp pretreatment processes. Our results evidence a higher chemical susceptibility of amorphous portions of cellulose to chemicals typically employed in acid hydrolysis. Additionally, we observed that glucose monomers coming from cellulose hydrolysis may undergo oxidation, leading to the formation of byproducts such as hydroxymethylfurfural (HMF), acetic acid, formic acid, and levulinic acid. The analysis of local chemical softness indexes indicated that cellulose hydrolysis may be associated with intermediate chemical steps. Finally, we investigated the influence of distinct solvents (dielectric constants) on the local reactivity of the systems, evidencing a relevant role of the solvent dielectric constant for cellulose degradation in glucose. Initial three-dimensional structures were constructed. Pre-optimizations were performed in a Hartree-Fock (HF) approach employing thePM7 semi-empirical hamiltonian. The structures were then re-optimized via density functional theory (DFT). The local reactivity study of the systems was conducted through the condensed-to-atoms Fukui indexes (CAFI). Systematic changes of the dielectric constants were also considered in geometry optimization and CAFI calculations to estimate the influence of solvents on the reactivity of the systems.

The Role of Double Excitations in Exciton Dynamics of Multiazobenzenes: Trisazobenzenophane as a Test Case.

Molecular exciton dynamics underlie energy and charge transfer processes in organic multichromophoric systems. A particularly interesting class of the latter is multiphotochromic systems made of molecules capable of photochemical transformations. Exciton dynamics in assemblies of photoswitches have been recently investigated using either the molecular exciton model or supermolecular configuration interaction (CI) singles, both approaches being based on a semiempirical Hamiltonian and combined with surface hopping molecular dynamics. Here, we study how inclusion of double excitations in nonadiabatic dynamics simulations affects exciton dynamics of multiazobenzenes, using trisazobenzenophane as an example. We find that both CI singles and CI singles and doubles yield virtually the same time scale of dynamical exciton localization, ∼50 fs for the studied multiazobenzene. However, inclusion of double excitations considerably affects the excited state lifetimes and isomerization quantum yields.

Charge-Transfer Complexes: Halogen-Doped Anthracene as a Case of Study.

Charge transfer (CT) crystals exhibit unique electronic and magnetic properties with interesting applications. We present a rational and easy guide which allows to foresee the effective charge transfer co-crystal production and that is based on the comparison of the frontier molecular orbital (MO) energies of a donor and acceptor couple. For the sake of comparison, theoretical calculations have been carried out by using the cheap and fast PM6 semiempirical Hamiltonian and pure HF/cc-pVTZ level of the theory. The results are then compared with experimental results obtained both by chemical (bromine and iodine were used as the acceptor) and electrochemical doping (exploiting an original experimental set-up by this laboratory: the electrochemical transistor). Infra-red vibrational experimental results and theoretically calculated spectra are compared to assess both the effective donor-acceptor (D/A) charge-transfer and transport mechanism (giant IRAV polaron signature). XPS spectra have been collected (carbon (1 s) and iodine (3d5/2)) signals, yielding further evidence of the effective formation of the CT anthracene:iodine complex.

Ultraviolet response data of liquid crystals for bioprocess monitoring: A methodical exploration

From the homologues series of 2,3-n-dialkyloxy-4-(4-chlorobenzoyloxy)-4′-(4-methylbenzoyloxy)-azobenzene (nOClAB; n = 5, 6, 7, 8) have been chosen for bioprocess monitoring based on their ultraviolet (UV) response. The optimization of molecular structures of these compounds has been performed via functional B3LYP together with 6–31+G (d) basis set. Further, the UV response of these compounds have been analyzed by implementing the configuration interaction singles (CIS) method along with calculation of excited states using semiempirical ZINDO Hamiltonian. The INDO/S+CI approach has been used for comparative analysis. Geometries of four liquid crystals (LCs) in the biosensing, their usefulness, as well as their applications are described. The spectral associated parameters have been summarized. Using this data the UV response mechanism and its implication in analyzing bioprocess monitoring, bio sensing, and bio oscillator applications have been methodically explored. These liquid crystal structures are expected to fulfill the purpose of the processors that can transform the biomolecule signals into the optical signals.

Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host-Guest Binding: IV. The QM Treatment, GB Models and the Multi-Trajectory Extension

Due to the similarity of host–guest complexes and protein–ligand and protein–protein assemblies, computational tools for protein–drug complexes are commonly applied in host–guest binding. One of the methods with the highest popularity is the end-point free energy technique, which estimates the binding affinity with gas-phase and solvation contributions extracted from simplified end-point sampling. Our series papers on a set of carboxylated-pillararene host–guest complexes have proven with solid numerical evidence that standard end-point techniques are practically useless in host–guest binding, but alterations, such as slightly increasing interior dielectric constant in post-processing calculation and shifting to the multi-trajectory realization in conformational sampling, could better the situation and pull the end-point method back to the pool of usable tools. Also, the force-field selection plays a critical role, as it determines the sampled region in the conformational space. In the current work, we continue the efforts to explore potentially promising end-point modifications in host–guest binding and further extend the sampling time to an unprecedent length. Specifically, we comprehensively benchmarked the shift from the original MM description to QM Hamiltonians in post-processing the popular single-trajectory sampling. Two critical settings in the multi-scale QM/GBSA regime are the selections of the QM Hamiltonian and the implicit-solvent model, and a scan of combinations of popular semi-empirical QM Hamiltonians and GB models is performed. The multi-scale QM/GBSA treatment is further combined with the three-trajectory sampling protocol, introducing a further advanced modification. The sampling lengths in the host–guest complex, solvated guest and solvated host ensembles are extended to 500 ns, 500 ns and 12,000 ns. As a result, the sampling quality in end-point calculations is unprecedently high, enabling us to draw conclusive pictures of investigated forms of modified end-point free energy methods. Numerical results suggest that the shift to the QM Hamiltonian does not better the situation in the popular single-trajectory regime, but noticeable improvements are observed in the three-trajectory sampling regime, especially for the DFTB/GBSA parameter combination (either DFTB2 or its third-order extension), the quality metrics of which reach an unprecedently high level and surpass existing predictions (including costly alchemical transformations) on this dataset, hinting on the applicability of the advanced three-trajectory QM/GBSA end-point modification for host–guest complexes.

Treating Semiempirical Hamiltonians as Flexible Machine Learning Models Yields Accurate and Interpretable Results.

Quantum chemistry provides chemists with invaluable information, but the high computational cost limits the size and type of systems that can be studied. Machine learning (ML) has emerged as a means to dramatically lower the cost while maintaining high accuracy. However, ML models often sacrifice interpretability by using components such as the artificial neural networks of deep learning that function as black boxes. These components impart the flexibility needed to learn from large volumes of data but make it difficult to gain insight into the physical or chemical basis for the predictions. Here, we demonstrate that semiempirical quantum chemical (SEQC) models can learn from large volumes of data without sacrificing interpretability. The SEQC model is that of density-functional-based tight binding (DFTB) with fixed atomic orbital energies and interactions that are one-dimensional functions of the interatomic distance. This model is trained to ab initio data in a manner that is analogous to that used to train deep learning models. Using benchmarks that reflect the accuracy of the training data, we show that the resulting model maintains a physically reasonable functional form while achieving an accuracy, relative to coupled cluster energies with a complete basis set extrapolation (CCSD(T)*/CBS), that is comparable to that of density functional theory (DFT). This suggests that trained SEQC models can achieve a low computational cost and high accuracy without sacrificing interpretability. Use of a physically motivated model form also substantially reduces the amount of ab initio data needed to train the model compared to that required for deep learning models.

Dynamic Effects on Hole Transport in Amorphous Organic Semiconductors: a Combined QM/MM and kMC Study.

Small-molecule-based amorphous organic semiconductors (OSCs) are essential components of organic photovoltaics and organic light-emitting diodes. The charge carrier mobility of these materials is an integral and limiting factor in regard to their performance. Integrated computational models for the hole mobility, taking into account structural disorder in systems of several thousand molecules, have been the object of research in the past. Due to static and dynamic contributions to the total structural disorder, efficient strategies to sample the charge transfer parameters become necessary. In this paper, we investigate the impact of structural disorder in amorphous OSCs on the transfer parameters and charge mobilities in different materials. We present a sampling strategy for incorporating static and dynamic structural disorder which are based on QM/MM methods using semiempirical Hamiltonians and extensive MD sampling. We show how the disorder affects the distributions of HOMO energies and intermolecular couplings and validate the results using kinetic Monte Carlo simulations of the mobility. We find that dynamic disorder causes an order of magnitude difference in the calculated mobility between morphologies of the same material. Our method allows the sampling of disorder in HOMO energies and couplings, and the statistical analysis enables us to characterize the relevant time scales on which charge transfer occurs in these complex materials. The findings presented here shed light on the interplay of the fluctuating amorphous matrix with charge carrier transport and aid in the development of a better understanding of these complex processes.

SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods.

Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. We present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn-Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.

Testing Affordable Strategies for the Computational Study of Reactivity in Cysteine Proteases: The Case of SARS-CoV-2 3CL Protease Inhibition

Cysteine proteases are an important target for the development of inhibitors that could be used as drugs to regulate the activity of these kinds of enzymes involved in many diseases, including COVID-19. For this reason, it is important to have methodological tools that allow a detailed study of their activity and inhibition, combining computational efficiency and accuracy. We here explore the performance of different quantum mechanics/molecular mechanics methods to explore the inhibition reaction mechanism of the SARS-CoV-2 3CL protease with a hydroxymethyl ketone derivative. We selected two density functional theory (DFT) functionals (B3LYP and M06-2X), two semiempirical Hamiltonians (AM1d and PM6), and two tight-binding DFT methods (DFTB3 and GFN2-xTB) to explore the free energy landscape associated with this reaction. We show that it is possible to obtain an accurate description combining molecular dynamics simulations performed using tight-binding DFT methods and single-point energy corrections at a higher QM description. The use of a computational strategy that provides reliable results at a reasonable computational cost could assist the in silico screening of possible candidates during the design of new drugs directed against cysteine proteases.

A Computational Study of the Promiscuity of the SAM-Dependent Methyltransferase AtHTMT1.

A two-pronged computational approach was taken to study the promiscuity of the SAM+-dependent methyl transferase AtHTMT1 from thale cress with several nucleophiles (Cl–, Br–, I–, NCO–, NCS–). First, enzyme-free methyl transfer reactions were studied with M05/6-311+G(2d,p) DFT calculations and electrostatic continuum models (PCM/SMD) for various chemical environments. Second, QM/MM MD simulations with semiempirical Hamiltonians (PM7, PM6-D3, AM1, PM6-D3H4) and the AMBER 14SB force field were used to study the enzyme catalyzed reaction in silico. The combination of the DFT and MD results shows that reactant desolvation generally accelerates the reaction, but it cannot explain the selectivity of the enzyme. The critical position of H2O molecules at the reactive site favors the reaction of NCS– over Cl– and Br– in agreement with experiments, but not observed in the quantum calculations for the cytosol. The addition of selected H2O molecules to the N terminus of NCS– greatly increases its reactivity, while H2O molecules attached to Cl– slow the reaction. The partial solvation of the nucleophiles in the reactive pouch holds the key to understanding the reactivity of AtHTMT1.

Electronic Conduction through Monolayer Amorphous Carbon Nanojunctions.

In molecular electronic conduction, exotic lattice morphologies often give rise to exotic behaviors. Among 2D systems, graphene is a notable example. Recently, a stable amorphous version of graphene called monolayer amorphous carbon (MAC) was synthesized. MAC poses a new set of questions regarding the effects of disorder on conduction. In this Letter, we perform an ensemble-level computational analysis of the coherent electronic transmission through MAC nanofragments in search of defining characteristics. Our analysis, relying on a semiempirical Hamiltonian (Pariser-Parr-Pople) and Landauer theory, showed that states near the Fermi energy (EF) in MAC inherit partial characteristics of analogous surface states in graphene nanofragments. Away from EF, current is carried by a set of delocalized states that transition into a subset of insulating interior states at the extreme portions of MAC's energy spectrum. Finally, we also found that quantum interference between frontier orbitals is a common feature among MAC nanofragments.

Role of Basic Surface Groups of Activated Carbon in Chlordecone and β-Hexachlorocyclohexane Adsorption: A Molecular Modelling Study.

The influence of nitrogen-containing surface groups (SGs) onto activated carbon (AC) over the adsorption of chlordecone (CLD) and β-hexachlorocyclohexane (β-HCH) was characterized by a molecular modelling study, considering pH (single protonated SGs) and hydration effect (up to three water molecules). The interactions of both pollutants with amines and pyridine as basic SGs of AC were studied, applying the multiple minima hypersurface (MMH) methodology and using PM7 semiempirical Hamiltonian. Representative structures from MMH were reoptimized using the M06-2X density functional theory. The quantum theory of atoms in molecules (QTAIM) was used to characterize the interaction types in order understanding the adsorption process. A favorable association of both pesticides with the amines and pyridine SGs onto AC was observed at all pH ranges, both in the absence and presence of water molecules. However, a greater association of both pollutants with the primary amine was found under an acidic pH condition. QTAIM results show that the interactions of CLD and β-HCH with the SGs onto AC are governed by Cl···C interactions of chlorine atoms of both pesticides with the graphitic surface. Electrostatic interactions (H-bonds) were observed when water molecules were added to the systems. A physisorption mechanism is suggested for CLD and β-HCH adsorption on nitrogen-containing SGs of AC.

On the inclusion of one double within CIS and TDDFT.

We present an improved approach for generating a set of optimized frontier orbitals (HOMO and LUMO) that minimizes the energy of one double configuration. We further benchmark the effect of including such a double within a rigorous configuration interaction singles or a parameterized semi-empirical time-dependent density functional theory Hamiltonian for a set of test cases. Although we cannot quite achieve quantitative accuracy, the algorithm is quite robust and routinely delivers an enormous qualitative improvement to standard single-reference electronic structure calculations.

New Approach for Correcting Noncovalent Interactions in Semiempirical Quantum Mechanical Methods: The Importance of Multiple-Orientation Sampling.

A new approach is presented to improve the performance of semiempirical quantum mechanical (SQM) methods in the description of noncovalent interactions. To show the strategy, the PM6 Hamiltonian was selected, although, in general, the procedure can be applied to other semiempirical Hamiltonians and to different methodologies. A set of small molecules were selected as representative of various functional groups, and intermolecular potential energy curves (IPECs) were evaluated for the most relevant orientations of interacting molecular pairs. Then, analytical corrections to PM6 were derived from fits to B3LYP-D3/def2-TZVP reference–PM6 interaction energy differences. IPECs provided by the B3LYP-D3/def2-TZVP combination of the electronic structure method and basis set were chosen as the reference because they are in excellent agreement with CCSD(T)/aug-cc-pVTZ curves for the studied systems. The resulting method, called PM6-FGC (from functional group corrections), significantly improves the performance of PM6 and shows the importance of including a sufficient number of orientations of the interacting molecules in the reference data set in order to obtain well-balanced descriptions.

QM/MM Study of the Enzymatic Biodegradation Mechanism of Polyethylene Terephthalate.

The environmental problems derived from the generalized plastic consumption and disposal could find a friendly solution in enzymatic biodegradation. Recently, two hydrolases from Ideonella sakaiensis 201-F6 and the metagenome-derived leaf-branch compost cutinase (LCC), more specially the improved ICCG variant, have revealed degradation activity toward poly ethylene terephthalate (PET). In the present study, the reaction mechanism of this polymer breakage is studied at an atomic level by multiscale QM/MM molecular dynamics simulations, using semiempirical and DFT Hamiltonians to describe the QM region. The obtained free energy surfaces confirmed a characteristic four-step path for both systems, with activation energies in agreement with the experimental observations. Structural analysis of the evolution of the active site along the reaction progress and the study of electrostatic effects generated by the proteins reveal the similarity in the behavior of the active site of these two enzymes. The origin of the apparent better performance of the LCC-ICCG protein over PETase must be due to its capabilities of working at higher temperature and its intrinsic relationship with the crystallinity grade of the polymer. Our results may be useful for the development of more efficient enzymes in the biodegradation of PET.

From QCEIMS to QCxMS: A Tool to Routinely Calculate CID Mass Spectra Using Molecular Dynamics.

Mass spectrometry (MS) is a powerful tool in chemical research and substance identification. For the computational modeling of electron ionization MS, we have developed the quantum-chemical electron ionization mass spectra (QCEIMS) program. Here, we present an extension of QCEIMS to calculate collision-induced dissociation (CID) spectra. The more general applicability is accounted for by the new name QCxMS, where "x" refers to EI or CID. To this end, fragmentation and rearrangement reactions are computed "on-the-fly" in Born-Oppenheimer molecular dynamics (MD) simulations with the semiempirical GFN2-xTB Hamiltonian, which provides an efficient quantum mechanical description of all elements up to Z = 86 (Rn). Through the explicit modeling of multicollision processes between precursor ions and neutral gas atoms as well as temperature-induced decomposition reactions, QCxMS provides detailed insight into the collision kinetics and fragmentation pathways. In combination with the CREST program to determine the preferential protonation sites, QCxMS becomes the first standalone MD-based program that can predict mass spectra based solely on molecular structures as input. We demonstrate this for six organic molecules with masses ranging from 159 to 296 Da, for which QCxMS yields CID spectra in reasonable agreement with experiments.

Molecular Structure Effects on the Aggregation Motif of Porphyrins: Computational Insights

AbstractThe latest advancements in semiempirical Hamiltonians have inspired new confidence for the supramolecular computational predictivity. The advanced accuracy of newly developed semiempirical methods is offered for computations of what can provide a valuable database of molecular tuning recommendations for the synthesis of new supramolecular materials. In this work the very versatile and impactful porphyrin is employed for examination of the first basic chemical tuning factors that may drive specific aggregation motifs. The 1D motifs are examined as a function of peripheral substituent steric bulk. Subsequently, a 1D‐wire versus a 3D‐square motif is investigated as a function of the metal–ligand effect. For the first time, an interesting effect of misprediction of semiempirical computations is encountered for a small class of these aggregates and is briefly examined with a conformational search analysis. These findings encourage further in silico work which is greatly required for diminishing the current discovery bottleneck in supramolecular chemistry.

Photoisomerization dynamics of spiropyran: A surface-hopping investigation

In the present work, we performed a computational investigation of the photoisomerization of spiro[1,3-dihydroindole-2,2'-chromene] [spiropyran (SP)] to merocyanine. The electronic energies and wavefunctions were obtained from configuration interaction calculations, using the floating occupation molecular orbital method, in a semiempirical framework. The parameters of the semiempirical Hamiltonian were re-optimized to reproduce ab initio literature data for SP. In our dynamics simulations, we considered, besides S0, the excited states S1, S2, and S3, which are very close in energy in the Franck-Condon region. We obtained a singlet lifetime of 0.67 ps, in line with the experimental results. We found the photoisomerization quantum yield to depend on the electronic state initially populated.

Cu (II), Zn (II), and Ce (III) metal complexes as antimicrobial pigments for surface coating and flexographic ink

Metal complexes, which were prepared from the reaction of an N‐salicylidene(4‐aminotoluene‐3‐sulfonic acid) Schiff base ligand (H2L) with Cu (II), Zn (II), and Ce (III), were characterized and confirmed by elemental analysis, molar conductance measurement, melting point, Fourier transform infrared (FT‐IR) spectroscopy, proton nuclear magnetic resonance (1H NMR), electronic spectra, magnetic susceptibility, thermal analysis, and qualitative and quantitative antimicrobial studies. The geometry of the compounds was optimized using the semiempirical PM3 Hamiltonian with Restricted Hartree–Fock (RHF) and root‐mean‐square (RMS) gradient of 0.05 kcal/mol. The ligand and its metal complexes were physically incorporated into a water‐based paint and flexographic ink formulation to study their antimicrobial properties and performances as metal‐complex pigments. The results of their performance tests further enhanced their applications as pigments. The mechanical resistance of the prepared paint and ink was also studied to evaluate the possible drawbacks that were associated with the addition of the prepared pigments. Compared with the blank sample, the studies indicated that the physical incorporation of Cu complexes slightly enhanced the mechanical properties of the painted films (the gloss values, hardness, and adhesion) and printed paper (gloss, color strength [density], and abrasion resistance) according to the American Society for Testing and Materials (ASTM). Further, regarding the antimicrobial test, the obtained results can be represented according to the following activity order: the prepared ligand > Zn complex > Ce complex > Cu complex before or after the incorporations of the paint and ink.