High-level Theory Research Articles

Prediction of properties from first principles with quantitative accuracy: six representative ice phases

Based on a high-level MP2 theory with the fragment approach, the crystal structure, vibration spectra and phase transitions of six representative ice phases (II, VI, VII, VIII, IX, and XV) are predicted.

Exploring free energy profile of petroleum thermal cracking mechanisms.

Understanding the mechanisms of petroleum thermal cracking is critical to develop more efficient and eco-friendly petroleum cracking processes. Asphaltenes are the main component of petroleum subjected to cracking processes. Thermal cracking mechanisms of petroleum were explored by computational methods using 1,2-diphenylethane (DPE) as a model molecule in this study. The overall mechanisms were divided into four steps including initiation, H-transfer reaction, H-ipso reaction, and termination represented by seven reactions. We carried out extensive quantum chemistry calculations at high levels of theory to accurately explore the minimum energy pathways as the mechanisms of the proposed reactions. The reaction energy and barriers in terms of enthalpy and free energy and their temperature dependence were calculated in the vacuum and in both polar and nonpolar solvents using the polarizable continuum model (PCM) method. The temperature dependence of the target reaction barriers are characterized in different environments and provides computational guidance for future development for petroleum thermal cracking. As the first reported systematic investigation of petroleum cracking mechanisms, this study provided a comprehensive theoretical description of petroleum cracking processes with valuable information about temperature and solvent dependence. Graphical abstract.

Topological Analysis of Electron Density in Large Biomolecular Systems.

A great step toward describing the structure of the molecular electron was made in the era of quantum chemical methods. Methods play a very important role in the prediction of molecular properties and in the description of the reactivity of compounds, which cannot be overestimated. There are many works, books, and articles on quantum methods, their applications, and comparisons. At the same time, quantum methods of a high level of theory, which give the most accurate results, are time-consuming, which makes them almost impossible to describe large complex molecular systems, such as macromolecules, enzymes, supramolecular compounds, crystal fragments, and so on. To propose an approach that allows real-time estimation of electron density in large systems, such as macromolecules, nanosystems, proteins. AlteQ approach was applied to the tolopogical analysis of electron density for "substrate - cytochrome" complexes. The approach is based on the use of Slater's type atomic contributions. Parameters of the atomic contributions were found using high resolution X-ray diffraction data for organic and inorganic molecules. Relationships of the parameters with atomic number, ionization potentials and electronegativities were determined. The sufficient quality of the molecular electron structure representation was shown under comparison of AlteQ predicted and observed electron densities. AlteQ algorithm was applied for evaluation of electron structure of "CYP3A4 - substrate" complexes modeled using BiS/MC restricted docking procedure. Topological analysis (similar to Atoms In Molecules (AIM) theory suggested by Richard F.W. Bader) of the AlteQ molecular electron density was carried out for each complex. The determination of (3,-1) bond, (3,+1) ring, (3,+3) cage critical points of electron density in the intermolecular "CYP3A4 - substrate" space was performed. Different characteristics such as electron density, Laplacian eigen values, etc. at the critical points were computed. Relationship of pKM (KM is Michaelis constant) with the maximal value of the second Laplacian eigen value of electron density at the critical points and energy of complex formation computed using MM3 force field was determined. It was shown that significant number of (3,-1) bond critical points are located in the intermolecular space between the enzyme site and groups of substrate atoms eliminating during metabolism processes.

The Relation between Husserl’s Phenomenological Account of Imaginative Empathy and High-level Simulation, and How to Solve the Problem of the Generalizability of Empathy

This article provides an overview of Edmund Husserl’s lesser known account of high-level imaginative empathy. The author discusses Husserl’s solution to what we might call the ‘generalizability problem’; if empathy is conceived as a relation whereby the understanding I have of my own mind allows me to understand your mind (as some versions of simulation theory and Husserl contend), then how does empathy account for potential differences between us? The author also discusses some features that make empathy more generalizable than might be initially thought, as well as its limits. A second major aim is to use this exegesis of Husserl to show a variety of overlaps between his theory and high-level simulation theory. The author also shows how Husserl’s phenomenological theory provides a compelling response to critiques of high-level simulation from authors that utilize a hybrid cognitive science/phenomenological approach (i.e. Gallagher and Zahavi).

General trends in structure, stability and role of interactions in the complexes of acetone and thioacetone with carbon dioxide and water

Geometrical structure, stability of complexes of acetone/thioacetone with CO2 and/or H2O are thoroughly studied, and the role of intermolecular interactions are determined at the high level of theory. Obtained results propose that the minima of acetone⋯1,2CO2 are mainly stabilized by C⋯O tetrel bond, while in case of thioacetone, the structures are balanced by not only C⋯O tetrel bond, but also C⋯S one and hydrogen bonds. For the rest of investigated systems with the presence of H2O, OH⋯O/S hydrogen bond along with an additional contribution of other weak interactions determine on complex stabilization. The complexes of CO2 and/or H2O with acetone are more stable than those with thioacetone, and the larger positive cooperativity is considerably enhanced with an addition of H2O as compared to CO2 molecule in the acetone/thioacetone⋯CO2/H2O binary complexes. The electrostatic energy is found to be the main term overcoming dispersion and induction components contributing to strength of complexes.

Explanatory stories of human perception and behavior in buildings

This paper is motivated by a perceived disconnect between standards and guidelines for supporting building design and operation professionals on the one hand and contemporary fundamental research findings in pertinent human sciences. In other words, the plethora of recent highly detailed studies do not appear to have been crystalized into versatile explanatory theories accessible to practice-oriented professionals in the building delivery process. In fact, to locate instances of high-level and intuitively comprehensible explanatory models of human perception and behavior, one may need to revert back to intellectual traditions originated as far back as in late nineteenth century. A review of a number of such explanatory models suggests that they display, despite their differences in levels of detail and degrees of sophistication, a few recurrent motifs. To revisit these models is rewarding not only from the historical point of view. Their conceptual transparency has arguably the potential to inspire the development of a new generation of accessible high-level explanatory theories of human perception and behavior.

Chiroptical Symmetry Analysis of Trianglimines: A Case Study

It is well established that chiroptical responses, based on the unique reaction to circularly polarized light by chiral non-racemic systems, are sensitive to the stereochemistry of the featuring systems. This behavior has promoted the use of chiroptical spectroscopies as a mandatory tool in the structure determination of molecules for decades. Recently, the higher sensitivity of chiroptical techniques compared to the conventional UV/Vis absorption and fluorescence spectroscopies or electrochemistry has awakened much interest in the development of chiroptical everyday applications. While chiroptical responses could be predicted by ab initio calculations, large systems calculated at a high level of theory may have an important computational cost; therefore, more intuitive methods are desired to design systems with tailored chiroptical responses. In this regard, the exciton chirality method has been often used in conformationally stable systems incorporating at least two independent chromophores. Taking this method into consideration, in our previous work, we described the chiroptical symmetry analysis (CSA) based on symmetry selection rules. To explore the scope of the CSA, herein we perform the chiroptical symmetry analysis of diverse trianglimines and draw general conclusions to assist on the design of chiroptical systems with high symmetry.

The performance of explicitly correlated wavefunctions [CCSD(T)-F12b] in the computation of anharmonic vibrational frequencies

CCSD(T)-F12b/cc-pVTZ-F12 anharmonic vibrational frequencies match experiment or higher-level theory to within an average of 10.3 cm−1 for a sample set of 11 molecules. This is further reduced below 7.0 cm−1 when extreme differences are removed from the data set. CCSD(T)-F12b/cc-pVTZ-F12 and CCSD(T)-F12b/cc-pVDZ-F12 frequencies differ on average by 4.8 cm−1. The CCSD(T)-F12b frequencies require orders of magnitude less computer time than higher-order theory and cc-pVDZ-F12 less than cc-pVTZ-F12, especially as the number of atoms increases. Hence, utilization of these levels of theory may provide accurate vibrational frequencies for larger molecules provided that the core-electron correlation is not significant.

Suppressed-Doppler slit jet infrared spectroscopy of astrochemically relevant cations: ν1 and ν4 NH stretching modes in NH3D+

A suppressed-Doppler (Δν = 180 MHz) infrared spectrum of monodeuterated ammonium ions (NH3D+) has been obtained for the ν1 (symmetric) and ν4 (degenerate) N-H stretch bands via direct absorption high resolution IR laser spectroscopy in a planar slit jet discharge expansion. The ion is efficiently generated by H3 + protonation of NH2D in a discharge mixture of H2/NH2D, with the resulting expansion rapidly cooling the molecular ions into low rotational states. The first high-resolution infrared spectrum of ν1 is reported, as well as many previously unobserved transitions in the ν4 rovibrational manifold. Simultaneous observation of both ν1 and ν4 permits elucidation of both the vibrational ground and excited state properties of the ion, including rigorous benchmarking of band origins against high-level anharmonic ab initio theory as well as determination of the ν1:ν4 intensity ratio for comparison with bond-dipole model predictions. Ground-state combination differences from this work and earlier studies permit the rotational constants of NH3D+ to be determined to unprecedented accuracy, the results of which support previous laboratory and astronomical assignment of the 10-00 pure rotational transition and should aid future searches for other rotational transitions as well.

Methods To Improve the Calculations of Solvation Model Density Solvation Free Energies and Associated Aqueous pKa Values: Comparison between Choosing an Optimal Theoretical Level, Solute Cavity Scaling, and Using Explicit Solvent Molecules.

Many approaches have been used to improve the accuracy of implicit solvent models including solute cavity scaling, introducing explicit solvent molecules, and changing the level of theory for the solvation calculations. Here, we compare these strategies using a large test set of aqueous pKa values for amines, nucleobases, carboxylic acids, thiols, peptide carbon acids, alcohols, and anilines for the specific case of solvation model density (SMD) within the framework of a thermodynamic cycle in which the gas-phase component is consistently calculated via the accurate CBS-QB3 method. We show that the choice of theoretical level for solvation energies should be based on the original parameterization of the solvent model, with separate levels of theory for the solvation energies of neutrals, anions, or cations, outperforming the best compromise level of theory. However, when explicit solvent molecules are introduced, a higher level of theory is needed to describe the solute-solvent interactions. For the systems studied here, explicit solvation improved the results for acids (and hence anions) but not for bases, for which results deteriorated. Importantly, we find that solute cavity scaling does not significantly improve the SMD results for the CHNO compounds tested when the correct theoretical level is employed and explicit solvent effects are correctly treated.

First-principles study of the structural and electronic properties of bulk ZnS and small ZnnSn nanoclusters in the framework of the DFT+U method

We investigate the structural and electronic properties of bulk ZnS in zinc blende as well as in wurtzite phase, and ${\mathrm{Zn}}_{n}{\mathrm{S}}_{n}$ nanoclusters by using the Hubbard model $(\mathrm{DFT}+U)$. It provides an on-site Coulomb correction to mitigate some of the commonly known limitations of traditional DFT-GGA method such as the underestimation of band gap and inaccurate description of electronic band structure. Especially for the nanoclusters, the traditional DFT method cannot reproduce all properties accurately that are observed in the experiments. Within the framework of $\mathrm{DFT}+U$ method, our model is first able to predict various properties of bulk ZnS (zinc blende and wurtzite) as well as in nanoclusters with high accuracy. We empirically determined the Hubbard correction parameters ${U}_{d}$ and ${U}_{p}$ for $\mathrm{Zn}\text{\ensuremath{-}}3d$ and $\mathrm{S}\text{\ensuremath{-}}3p$ states, respectively, that could reproduce the measured values of band gaps, $d$-band positions, $p$-states bandwidths, lattice parameters, etc. with a reasonable agreement. It was found that our model can be compared very well with more accurate hybrid functionals at only a fraction of the computational cost. Further, the selected pair of ${U}_{d}$ and ${U}_{p}$ values are used to investigate the structural and electronic properties of ZnS nanoclusters and results agree well with the higher levels of theory.

Blind Search for Complex Chemical Pathways Using Harmonic Linear Discriminant Analysis.

Disentangling the mechanistic details of a chemical reaction pathway is a hard problem that often requires a considerable amount of chemical intuition and a component of luck. Experiments struggle in observing short-life metastable intermediates, while computer simulations often rely upon a good initial guess. In this work, we propose a method that, from the simulations of a reactant and a product state, searches for reaction mechanisms connecting the two by exploring the configuration space through metadynamics, a well-known enhanced molecular dynamics method. The key quantity underlying this search is based on the use of an approach called harmonic linear discriminant analysis which allows a systematic construction of collective variables. Given the reactant and product states, we choose a set of descriptors capable of discriminating between the two states. In order to not prejudge the results, generic descriptors are introduced. The fluctuations of the descriptors in the two states are used to construct collective variables. We use metadynamics in an exploratory mode to discover the intermediates and the transition states that lead from reactant to product. The search is at first conducted at a low theory level. The calculation is then refined, and the energy of the intermediates and transition states discovered during metadynamics is computed again using a higher level of theory. The method's aim is to offer a simple reaction mechanism search procedure that helps in saving time and is able to find unexpected mechanisms that defy well established chemical paradigms. We apply it to two reactions, showing that a high level of complexity can be hidden even in seemingly trivial and small systems. The method can be applied to larger systems, such as reactions in solution or catalysis.

Minimal coherence among varied theory of mind measures in childhood and adulthood

Theory of mind—or the understanding that others have mental states that can differ from one’s own and reality—is currently measured across the lifespan by a wide array of tasks. These tasks vary across dimensions including modality, complexity, affective content, and whether responses are explicit or implicit. As a result, theoretical and meta-analytic work has begun to question whether such varied approaches to theory of mind should be categorized as capturing a single construct. To directly address the coherence of theory of mind, and to determine whether that coherence changes across development, we administered a diverse set of theory of mind measures to three different samples: preschoolers, school-aged children, and adults. All tasks showed wide variability in performance, indicating that children and adults often have inconsistent and partial mastery of theory of mind concepts. Further, for all ages studied, the selected theory of mind tasks showed minimal correlations with each other. That is, having high levels of theory of mind on one task did not predict performance on another task designed to measure the same underlying ability. In addition to showing the importance of more carefully designing and selecting theory of mind measures, these findings also suggest that understanding others’ internal states may be a multidimensional process that interacts with other abilities, a process which may not occur in a single conceptual framework. Future research should systematically investigate task coherence via large-scale and longitudinal efforts to determine how we come to understand the minds of others.

Message-passing neural networks for high-throughput polymer screening.

Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data, machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based neural network architectures have emerged in recent years as the most successful approach for predictions based on molecular structure and have consistently achieved the best performance on benchmark quantum chemical datasets. However, these models have typically required optimized 3D structural information for the molecule to achieve the highest accuracy. These 3D geometries are costly to compute for high levels of theory, limiting the applicability and practicality of machine learning methods in high-throughput screening applications. In this study, we present a new database of candidate molecules for organic photovoltaic applications, comprising approximately 91 000 unique chemical structures. Compared to existing datasets, this dataset contains substantially larger molecules (up to 200 atoms) as well as extrapolated properties for long polymer chains. We show that message-passing neural networks trained with and without 3D structural information for these molecules achieve similar accuracy, comparable to state-of-the-art methods on existing benchmark datasets. These results therefore emphasize that for larger molecules with practical applications, near-optimal prediction results can be obtained without using optimized 3D geometry as an input. We further show that learned molecular representations can be leveraged to reduce the training data required to transfer predictions to a new density functional theory functional.

Exploring Reaction Energy Profiles Using the Molecules-in-Molecules Fragmentation-Based Approach.

The Molecules-in-Molecules (MIM) fragmentation-based approach has been successfully used in previous studies to obtain the energies, optimized geometries, and spectroscopic properties of large molecular systems. The present work delineates a protocol to study the potential energy profiles for multistep chemical reactions using the MIM methodology. In a complex multistep chemical reaction, the fragmentation scheme needs to be changed as the reacting species transition into a new reaction step, resulting in a discontinuity in the potential energy curve of the reaction. In our approach, the fragmentation scheme for a particular step in a reaction is chosen on the basis of the nature of the bonding changes associated with that step. Thus, the reactant, transition state, and product are treated consistently throughout the reaction step, leading to an accurate energy barrier for that step. The discontinuity now occurs in describing the energies of reaction intermediates at the transition point between two reaction steps that are treated by two different fragmentation schemes. To address this issue, we propose a systematic procedure for obtaining continuous potential energy curves that are least shifted from their initial positions. The corrected MIM potential energy curves are continuous with activation energies preserved. Following this approach, energy profiles of complex reactions involving large molecular species can be obtained at high levels of theory with a reasonable computational cost.

Quantum chemical calculations of the thermochemistry of tantalum oxyhydroxide species

AbstractTantalum pentoxide and water vapor are predicted to react at elevated temperatures to form TaO(OH)3(g), TaO2(OH)(g), and Ta(OH)5(g). The thermochemistry of these species is calculated with quantum chemistry methods. Geometries and vibrational frequencies are determined from B3LYP DFT methods. Energetics are calculated from high levels of theory—CCSD(T) and larger basis sets for Ta, O, and H. We report the enthalpies of formation at 0 K and 298.15 K, entropy at 298.15 K, and heat capacity. These quantities are used to calculate vapor pressures at 1400‐1800 K and 50% water vapor. TaO(OH)3(g) is found to be the dominant species. The calculated vapor pressure of TaO(OH)3(g) is converted to a vapor flux and compared to previous experimental flux measurements from a flat plate in a slowly flowing H2O/Ar gas and also vapor flux from a steam jet experiment. These “open system” experiments result in lower fluxes that are within 1.12‐17X of the calculated equilibrium fluxes. This suggests that the experimental measurements are near equilibrium or have a small kinetic barrier.

Conscious perception in patients with prefrontal damage

We are conscious and verbally report some of the information reaching our senses, although a big amount of information is processed unconsciously. There is no agreement about the neural correlates of consciousness, with low-level theories proposing that neural processing on primary sensory brain regions is the most important neural correlate of consciousness, while high-level theories propose that activity within the fronto-parietal network is the key component of conscious processing (Block, 2009). Contrary to the proposal of high-level theories, patients with prefrontal lobe damage do not present clinical symptoms associated to consciousness deficits. In the present study, we explored the conscious perception of near-threshold stimuli in a group of patients with right prefrontal damage and a group of matched healthy controls. Results demonstrated that perceptual contrast to perceive the near-threshold targets was related to damage to the right dorsolateral prefrontal cortex, and with reduced integrity of the ventral branch of the right superior longitudinal fascicule (SLF III). These results suggest a causal role of the prefrontal lobe in conscious processing.

Machine-Learned Fragment-Based Energies for Crystal Structure Prediction.

Crystal structure prediction involves a search of a complex configurational space for local minima corresponding to stable crystal structures, which can be performed efficiently using atom-atom force fields for the assessment of intermolecular interactions. However, for challenging systems, the limitations in the accuracy of force fields prevent a reliable assessment of the relative thermodynamic stability of potential structures, while the cost of fully quantum mechanical approaches can limit applications of the methods. We present a method to rapidly improve force field lattice energies by correcting two-body interactions with a higher level of theory in a fragment-based approach and predicting these corrections with machine learning. Corrected lattice energies with commonly used density functionals and second order perturbation theory (MP2) all significantly improve the ranking of experimentally known polymorphs where the rigid molecule model is applicable. The relative lattice energies of known polymorphs are also found to systematically improve with the fragment corrections. Predicting two-body interactions with atom-centered symmetry functions in a Gaussian process is found to give highly accurate results using as little as 10-20% of the data for training, reducing the cost of the energy correction by up to an order of magnitude. The machine learning approach opens up the possibility of more widespread use of fragment-based methods in crystal structure prediction, whose increased accuracy at a low computational cost will benefit applications in areas such as polymorph screening and computer-guided materials discovery.

High-level language competencies and Theory of Mind in a group of children with Klinefelter syndrome.

Klinefelter syndrome (KS) is a genetic anomaly involving the presence of one or more supernumerary X chromosomes in male individuals. In the cognitive profile of these individuals, strengths are found in nonverbal abilities, whereas weaknesses are observed in executive function, language, and academic performance. Our study is based on a comparison between eight children diagnosed with KS (47,XXY) (age range: 9-13 years; IQ range: 80-123), with no delay in language development, and eight typically developing (TD) controls. We explored a range of high-level language competencies and Theory of Mind (ToM) in addition to basic language competency. High-level language competencies were assessed by a battery that measures pragmatic language skills and a metaphor comprehension test (MCT). To assess ToM, we administered the corresponding subtest of the NEPSY II. Basic language competence was assessed by the NEPSY II Comprehension of Instructions subtest. Although basic language performance did not differentiate the individuals with KS from the TD controls, relevant differences appeared in some of the high-level language competencies as well as in the ToM task. All tasks in which the individuals with KS performed less well were characterized by complex inferential processes. Some possible clinical and educational implications are discussed.

The Importance of Peroxy Radical Hydrogen-Shift Reactions in Atmospheric Isoprene Oxidation.

With an annual emission of about 500 Tg, isoprene is an important molecule in the atmosphere. While much of its chemistry is well constrained by either experiment or theory, the rates of many of the unimolecular peroxy radical hydrogen-shift (H-shift) reactions remain speculative. Using a high-level multiconformer transition state theory (MC-TST) approach, we determine recommended temperature dependent reaction rate coefficients for a number of the H-shift reactions in the isoprene oxidation mechanism. We find that most of the (1,4, 1,5, and 1,6) aldehydic and (1,5 and 1,6) α-hydroxy H-shifts have rate constants at 298.15 K in the range 10-2 to 1 s-1, which make them competitive with bimolecular reactions in the atmosphere under typical atmospheric conditions. In addition, we find that the rate coefficients of different diastereomers can differ by up to 3 orders of magnitude, illustrating the importance of chirality. Implementation of our calculated reaction rate coefficients into the most recent GEOS-Chem model for isoprene oxidation shows that at least 30% of all isoprene molecules emitted to the atmosphere undergo a minimum of one peroxy radical hydrogen-shift reaction during their complete oxidation to CO2 and deposited species. This highlights the importance of peroxy radical H-shifts reactions in atmospheric oxidation.