Showing papers in "International Journal of Quantum Chemistry in 2015"

Constructing high-dimensional neural network potentials: A tutorial review

Abstract: A lot of progress has been made in recent years in the development of atomistic potentials using machine learning (ML) techniques. In contrast to most conventional potentials, which are based on physical approximations and simplifications to derive an analytic functional relation between the atomic configuration and the potential-energy, ML potentials rely on simple but very flexible mathematical terms without a direct physical meaning. Instead, in case of ML potentials the topology of the potential-energy surface is “learned” by adjusting a number of parameters with the aim to reproduce a set of reference electronic structure data as accurately as possible. Due to this bias-free construction, they are applicable to a wide range of systems without changes in their functional form, and a very high accuracy close to the underlying first-principles data can be obtained. Neural network potentials (NNPs), which have first been proposed about two decades ago, are an important class of ML potentials. Although the first NNPs have been restricted to small molecules with only a few degrees of freedom, they are now applicable to high-dimensional systems containing thousands of atoms, which enables addressing a variety of problems in chemistry, physics, and materials science. In this tutorial review, the basic ideas of NNPs are presented with a special focus on developing NNPs for high-dimensional condensed systems. A recipe for the construction of these potentials is given and remaining limitations of the method are discussed. © 2015 Wiley Periodicals, Inc.

Gaussian approximation potentials: A brief tutorial introduction

Abstract: We present a swift walk-through of our recent work that uses machine learning to fit interatomic potentials based on quantum mechanical data. We describe our Gaussian approximation potentials (GAP) framework, discuss a variety of descriptors, how to train the model on total energies and derivatives, and the simultaneous use of multiple models of different complexity. We also show a small example using QUIP, the software sandbox implementation of GAP that is available for noncommercial use. © 2015 Wiley Periodicals, Inc.

Crystal structure representations for machine learning models of formation energies

Abstract: We introduce and evaluate a set of feature vector representations of crystal structures for machine learning (ML) models of formation energies of solids. ML models of atomization energies of organi ...

Adaptive machine learning framework to accelerate ab initio molecular dynamics

Abstract: Quantum mechanics-based ab initio molecular dynamics (MD) simulation schemes offer an accurate and direct means to monitor the time evolution of materials. Nevertheless, the expensive and repetitive energy and force computations required in such simulations lead to significant bottlenecks. Here, we lay the foundations for an accelerated ab initio MD approach integrated with a machine learning framework. The proposed algorithm learns from previously visited configurations in a continuous and adaptive manner on-the-fly, and predicts (with chemical accuracy) the energies and atomic forces of a new configuration at a minuscule fraction of the time taken by conventional ab initio methods. Key elements of this new accelerated ab initio MD paradigm include representations of atomic configurations by numerical fingerprints, a learning algorithm to map the fingerprints to the properties, a decision engine that guides the choice of the prediction scheme, and requisite amount of ab initio data. The performance of each aspect of the proposed scheme is critically evaluated for Al in several different chemical environments. This work has enormous implications beyond ab initio MD acceleration. It can also lead to accelerated structure and property prediction schemes, and accurate force fields. V C 2014 Wiley Periodicals, Inc.

Machine learning for quantum mechanics in a nutshell

Abstract: Models that combine quantum mechanics (QM) with machine learning (ML) promise to deliver the accuracy of QM at the speed of ML. This hands-on tutorial introduces the reader to QM/ML models based on kernel learning, an elegant, systematically nonlinear form of ML. Pseudocode and a reference implementation are provided, enabling the reader to reproduce results from recent publications where atomization energies of small organic molecules are predicted using kernel ridge regression. © 2015 Wiley Periodicals, Inc.

Intrinsic reaction coordinate: Calculation, bifurcation, and automated search

Abstract: The intrinsic reaction coordinate (IRC) approach has been used extensively in quantum chemical analysis and prediction of the mechanism of chemical reactions. The IRC gives a unique connection from a given transition structure to local minima of the reactant and product sides. This allows for easy understanding of complicated multistep mechanisms as a set of simple elementary reaction steps. In this article, three topics concerning the IRC approach are discussed. In the first topic, the first ab initio study of the IRC and a recent development of an IRC calculation algorithm for enzyme reactions are introduced. In the second topic, cases are presented in which dynamical trajectories bifurcate and corresponding IRC connections can be inaccurate. In the third topic, a recent development of an automated reaction path search method and its application to systematic construction of IRC networks are described. Finally, combining these three topics, future perspectives are discussed. © 2014 Wiley Periodicals, Inc.

A general method to describe intersystem crossing dynamics in trajectory surface hopping

Abstract: Intersystem crossing is a radiationless process that can take place in a molecule irradiated by UV-Vis light, thereby playing an important role in many environmental, biological and technological processes. This paper reviews different methods to describe intersystem crossing dynamics, paying attention to semiclassical trajectory theories, which are especially interesting because they can be applied to large systems with many degrees of freedom. In particular, a general trajectory surface hopping methodology recently developed by the authors, which is able to include nonadiabatic and spin-orbit couplings in excited-state dynamics simulations, is explained in detail. This method, termed SHARC, can in principle include any arbitrary coupling, what makes it generally applicable to photophysical and photochemical problems, also those including explicit laser fields. A step-by-step derivation of the main equations of motion employed in surface hopping based on the fewest-switches method of Tully, adapted for the inclusion of spin-orbit interactions, is provided. Special emphasis is put on describing the different possible choices of the electronic bases in which spin-orbit can be included in surface hopping, highlighting the advantages and inconsistencies of the different approaches. © 2015 Wiley Periodicals, Inc.

Tensor product methods and entanglement optimization for ab initio quantum chemistry

Abstract: The treatment of high-dimensional problems such as the Schrodinger equation can be approached by concepts of tensor product approximation. We present general techniques that can be used for the treatment of high-dimensional optimization tasks and time-dependent equations, and connect them to concepts already used in many-body quantum physics. Based on achievements from the past decade, entanglement-based methods—developed from different perspectives for different purposes in distinct communities already matured to provide a variety of tools—can be combined to attack highly challenging problems in quantum chemistry. The aim of the present paper is to give a pedagogical introduction to the theoretical background of this novel field and demonstrate the underlying benefits through numerical applications on a text book example. Among the various optimization tasks, we will discuss only those which are connected to a controlled manipulation of the entanglement which is in fact the key ingredient of the methods considered in the paper. The selected topics will be covered according to a series of lectures given on the topic “New wavefunction methods and entanglement optimizations in quantum chemistry” at the Workshop on Theoretical Chemistry, February 18–21, 2014, Mariapfarr, Austria. © 2015 Wiley Periodicals, Inc.

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

Abstract: We introduce a fingerprint representation of molecules based on a Fourier series of atomic radial distribution functions. This fingerprint is unique (except for chirality), continuous, and differentiable with respect to atomic coordinates and nuclear charges. It is invariant with respect to translation, rotation, and nuclear permutation, and requires no preconceived knowledge about chemical bonding, topology, or electronic orbitals. As such, it meets many important criteria for a good molecular representation, suggesting its usefulness for machine learning models of molecular properties trained across chemical compound space. To assess the performance of this new descriptor, we have trained machine learning models of molecular enthalpies of atomization for training sets with up to 10 k organic molecules, drawn at random from a published set of 134 k organic molecules with an average atomization enthalpy of over 1770 kcal/mol. We validate the descriptor on all remaining molecules of the 134 k set. For a training set of 10 k molecules, the fingerprint descriptor achieves a mean absolute error of 8.0 kcal/mol. This is slightly worse than the performance attained using the Coulomb matrix, another popular alternative, reaching 6.2 kcal/mol for the same training and test sets. © 2015 Wiley Periodicals, Inc.

Neural network‐based approaches for building high dimensional and quantum dynamics‐friendly potential energy surfaces

Abstract: Development and applications of neural network (NN)-based approaches for representing potential energy surfaces (PES) of bound and reactive molecular systems are reviewed. Specifically, it is shown that when the density of ab initio points is low, NNs-based potentials with multibody or multimode structure are advantageous for representing high-dimensional PESs. Importantly, with an appropriate choice of the neuron activation function, PESs in the sum-of-products form are naturally obtained, thus addressing a bottleneck problem in quantum dynamics. The use of NN committees is also analyzed and it is shown that while they are able to reduce the fitting error, the reduction is limited by the nonrandom nature of the fitting error. The approaches described here are expected to be directly applicable in other areas of science and engineering where a functional form needs to be constructed in an unbiased way from sparse data. © 2014 Wiley Periodicals, Inc.

Density matrix renormalization group for ab initio calculations and associated dynamic correlation methods: A review of theory and applications

Abstract: The recent advent of the density matrix renormalization group (DMRG) theory has delivered a new capability to compute multireference (MR) wave function with large configuration space, which far exceeds the limitation of conventional approaches. Here, we provide an overview of our recent work on the developments of ab initio DMRG methods in the context of the active space approaches and their applications to MR chemical systems. © 2014 Wiley Periodicals, Inc.

The Bravyi-Kitaev transformation: Properties and applications

Abstract: Quantum chemistry is an important area of application for quantum computation. In particular, quantum algorithms applied to the electronic structure problem promise exact, efficient methods for determination of the electronic energy of atoms and molecules. The Bravyi–Kitaev transformation is a method of mapping the occupation state of a fermionic system onto qubits. This transformation maps the Hamiltonian of n interacting fermions to an O(log⁡n)-local Hamiltonian of n qubits. This is an improvement in locality over the Jordan–Wigner transformation, which results in an O(n)-local qubit Hamiltonian. We present the Bravyi–Kitaev transformation in detail, introducing the sets of qubits which must be acted on to change occupancy and parity of states in the occupation number basis. We give recursive definitions of these sets and of the transformation and inverse transformation matrices, which relate the occupation number basis and the Bravyi–Kitaev basis. We then compare the use of the Jordan–Wigner and Bravyi–Kitaev Hamiltonians for the quantum simulation of methane using the STO-6G basis. © 2015 Wiley Periodicals, Inc.

Understanding kernel ridge regression: Common behaviors from simple functions to density functionals

Abstract: Accurate approximations to density functionals have recently been obtained via machine learning (ML). By applying ML to a simple function of one variable without any random sampling, we extract the qualitative dependence of errors on hyperparameters. We find universal features of the behavior in extreme limits, including both very small and very large length scales, and the noise-free limit. We show how such features arise in ML models of density functionals. © 2015 Wiley Periodicals, Inc.

Generalized Vibrational Perturbation Theory for Rotovibrational Energies of Linear, Symmetric and Asymmetric Tops: Theory, Approximations, and Automated Approaches to Deal with Medium-to-Large Molecular Systems.

Abstract: Models going beyond the rigid-rotor and the harmonic oscillator levels are mandatory for providing accurate theoretical predictions for several spectroscopic properties. Different strategies have been devised for this purpose. Among them, the treatment by perturbation theory of the molecular Hamiltonian after its expansion in power series of products of vibrational and rotational operators, also referred to as vibrational perturbation theory (VPT), is particularly appealing for its computational efficiency to treat medium-to-large systems. Moreover, generalized (GVPT) strategies combining the use of perturbative and variational formalisms can be adopted to further improve the accuracy of the results, with the first approach used for weakly coupled terms, and the second one to handle tightly coupled ones. In this context, the GVPT formulation for asymmetric, symmetric, and linear tops is revisited and fully generalized to both minima and first-order saddle points of the molecular potential energy surface. The computational strategies and approximations that can be adopted in dealing with GVPT computations are pointed out, with a particular attention devoted to the treatment of symmetry and degeneracies. A number of tests and applications are discussed, to show the possibilities of the developments, as regards both the variety of treatable systems and eligible methods. © 2015 Wiley Periodicals, Inc.

Shannon information entropy for a hyperbolic double‐well potential

Abstract: We use the ansatz method to obtain the symmetric and antisymmetric solutions of a hyperbolic double-well potential by solving the Heun differential equation. The Shannon entropy is studied. The position Sx and momentum Sp information entropies for the low-lying two states N = 1, 2 are calculated. Some interesting features of the information entropy densities ρs(x) and ρs(p) as well as the probability density ρ(x) are demonstrated. We find that ρ(x) is equal or greater than 1 at positions x∼±1.2d for the allowed potential-depth values of U0 = 595.84 (symmetric case) and U0 = 1092.8 (antisymmetric case). This arises from the fact that most of the density is less than 1, the curve has to rise higher than 1 to have a total area of 1 as required for all probability distributions. We find that the position information entropy Sx decreases with the potential strength but the momentum entropy Sp is contrary to the Sx. The Bialynicki-Birula–Mycielski inequality is also tested and found to hold for these cases. © 2015 Wiley Periodicals, Inc.

QCTFF: on the construction of a novel protein force field

Abstract: In this perspective, we explain the strategy behind QCTFF, the current name for a novel atomistic protein force field. The atoms are constructed using Quantum Chemical Topology (QCT). These topological atoms determine how a system's energy is partitioned. We give a brief account of the results hitherto obtained, and a glimpse of unpublished results. Combining this QCT partitioning with the universal quantum expression of energy, leads to four types of fundamental energy contributions. The first of these is intra-atomic and the remaining three interatomic: (i) atomic self-energy, (ii) Coulomb energy, (iii) exchange energy, and (iv) correlation energy. All structural and dynamic effects emerge from the interplay of these contributions. The machine learning method kriging captures well how they change in response to a change in nuclear configuration. Second, the Coulomb energy is represented by a converging multipolar series expansion when the nuclei are sufficiently far apart. © 2015 The Authors International Journal of Quantum Chemistry Published by Wiley Periodicals, Inc.

Pristine and BN doped graphyne derivatives for UV light protection

Abstract: This report aims to explore the possibility of using graphyne derivatives as UV-light protector. Boron (B) and nitrogen (N) atoms are systematically substituted into the structures, and we find that BN-substituted analogs exhibit distinct characteristics compared with their parent two-dimensional structure. Due to the presence of BN at different sites, the optical band gap is tuned from infrared to UV via visible region depending on substitution sites. These findings will lead the way to utilize these BN doped structures in various optoelectronic applications such as in hybrid solar cell, electroluminescence cell, light emitting cell, and as selective electromagnetic radiation absorber. The origin of this tunable optical response and band gap is explained in the light of partial density of states analysis and electron density distribution. The presence of strong absorption peak in UV region indicates that these materials may be used as an excellent candidate for UV light protection. © 2015 Wiley Periodicals, Inc.

Orbital entanglement in quantum chemistry

Abstract: The basic concepts of orbital entanglement and its application to chemistry are briefly reviewed. The calculation of orbital entanglement measures from correlated wavefunctions is discussed in terms of reduced n-particle density matrices. Possible simplifications in their evaluation are highlighted in case of seniority-zero wavefunctions. Specifically, orbital entanglement allows us to dissect electron correlation effects in its strong and weak contributions, to determine bond orders, to assess the quality and stability of active space calculations, to monitor chemical reactions, and to identify points along the reaction coordinate where electronic wavefunctions change drastically. Thus, orbital entanglement represents a useful and intuitive tool to interpret complex electronic wavefunctions and to facilitate a qualitative understanding of electronic structure and how it changes in chemical processes. © 2014 Wiley Periodicals, Inc.

Geometric phases in quantum information

Abstract: The rise of quantum information science has opened up a new venue for applications of the geometric phase (GP), as well as triggered new insights into its physical, mathematical, and conceptual nat ...

Application of quantum calculations in the chemical industry—An overview

Abstract: The field of quantum chemistry experienced huge progress in the past two decades. The drivers for this have been the availability of more and more powerful computer hardware, the development and implementation of improved methods with a better balanced compromise between accuracy and efficiency, as well as pioneering work how these methods are successfully applied to real-world problems. Thus, quantum calculations, in particular via density functional theory, became an essential tool in many branches of chemical research. This article tries to give an overview how quantum chemical modeling is used in chemical industry, which is done by reviewing papers written by authors from chemical companies. Various topics of particular industrial relevance are introduced together with strategies how to address them via quantum calculations. Examples are the computation of reaction thermodynamics and kinetics as the key ingredients to understand and predict chemical reactivity, but also solvation models as well as methods to describe electronically excited states. © 2014 Wiley Periodicals, Inc.

Quantum‐classical path integral: A rigorous approach to condensed phase dynamics

Abstract: A rigorous methodology that combines a fully quantum mechanical treatment of a small system with a classical trajectory description of a large number of degrees of freedom is discussed in connection with the mechanism of decoherence. The need for mean field approximations in traditional quantum-classical calculations is removed by abandoning the delocalized wavefunction description of the quantum particle in favor of Feynman's formulation, which is based on local paths. The effects of the environment enter the quantum-classical path integral (QCPI) expression in terms of phase factors along classical trajectories, whose number grows exponentially with the number of time steps. It is argued that memory loss allows termination of trajectory branching and that the main contribution to decoherence arises from a single classical trajectory (from each sampled initial condition). Exploiting these ideas allows a dramatic reduction in the required number of trajectories, making QCPI calculations feasible. © 2015 Wiley Periodicals, Inc.

XMVB 2.0: A new version of Xiamen valence bond program

Abstract: Xiamen valence bond (XMVB), which is an ab initio nonorthogonal valence bond program, has been progressively developed and refined during the last 25 years. As the release of XMVB 1.0 in 2004, a number of significant enhancements and improvements have been made to the program. As a consequence, a new version, XMVB 2.0, has been released and will be described in this article. In XMVB 2.0, the nonorthogonal orbital-based reduced density matrix approach for the valence bond (VB) theory is implemented, based on the second quantization scheme for nonorthogonal orbitals. The present article also describes the recently developed algorithms for orbital optimization in the VB self-consist field (VBSCF) method, in which the internal contraction of wave function is used for computing energy gradients. Moreover, several newly implemented ab initio VB methods, such as VBSCF(CAS), internally contracted VB second-order perturbation theory (icVBPT2), VB polarizable continuum model, VB effective fragment potential (VBECP), and density-functional-based VB, are briefly reviewed in this article. Finally, test calculations of several planar arenes, in which up to 18 active electrons are involved, are performed with XMVB 2.0. © 2014 Wiley Periodicals, Inc.

Position and momentum information‐theoretic measures of the pseudoharmonic potential

Abstract: In this study, the information-theoretic measures in both the position and momentum spaces for the pseudoharmonic potential using Fisher information, Shannon entropy, Renyi entropy, Tsallis entropy, and Onicescu information energy are investigated analytically and numerically. The results obtained are applied to some diatomic molecules. The Renyi and Tsallis entropies are analytically obtained in position space using Srivastava–Niukkanen linearization formula in terms of the Lauricella hypergeometric function. Also, they are obtained in the momentum space in terms of the multivariate Bell polynomials of Combinatorics. We observed that the Fisher information increases with n in both the position and momentum spaces, but decreases with l for all the diatomic molecules considered. The Shannon entropy also increases with increasing n in the position space and decreases with increasing l. The variations of the Renyi and Tsallis entropies with l are also discussed. The exact and numerical values of the Onicescu information energy are also obtained, after which the ratio of information-theoretic impetuses to lengths for Fisher, Shannon, and Renyi are obtained. © 2015 Wiley Periodicals, Inc.

LSQC: Low scaling quantum chemistry program

Abstract: A low scaling quantum chemistry program, called LSQC, is described in this article. This version includes two linear scaling methods, generalized energy-based fragmentation (GEBF) approach and cluster-in-molecule (CIM) approach. In the GEBF approach, a variety of electron structure methods (including ab initio and density functional theory) are available for the calculations of ground-state energies, geometry optimizations, vibrational spectra, and other molecular properties for large systems. In the CIM approach, the electron correlation energies of large systems can be approximately obtained at the second-order Moller−Plesset perturbation theory and couple cluster levels. In this article, the details and the capabilities of the LSQC program are presented. © 2014 Wiley Periodicals, Inc.

Recent advances in the linearized semiclassical initial value representation/classical Wigner model for the thermal correlation function

Abstract: This article focuses on most recent advances in the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner model that includes quantum effects with classical trajectories and recovers exact thermal correlation functions (of even nonlinear operators, that is, nonlinear functions of position or momentum operators) in the classical, high temperature, and harmonic limits. Two methods for implementing the LSC-IVR/classical Wigner which are in principle feasible to be combined with general force fields or even ab initio electronic structure methods have been reviewed. One is the local Gaussian approximation with the imaginary time path integral approach, the other is the quantum thermal bath method. The article emphasizes on the theory and the algorithms for implementation, while it also covers recent applications and limitations of the LSC-IVR/classical Wigner. © 2015 Wiley Periodicals, Inc.

Shannon entropy and many‐electron correlations: Theoretical concepts, numerical results, and Collins conjecture

Abstract: In this article, I will discuss the overlap between the concept of Shannon entropy and the concept of electronic correlation. Quantum Monte Carlo numerical results for the uniform electron gas are also presented; these latter on the one hand enhance the hypothesis of a direct link between the two concepts but on the other hand leave a series of open questions which may be used to trace a roadmap for the future research in the field.

Fisher and Shannon information in orbital-free density functional theory

Abstract: The Euler equation of the orbital-free density functional theory is formulated with the specific Shannon and Fisher information. One of the new forms contains only the specific Shannon information. In spherically symmetric systems, the Euler equation can be formalized with the specific Fisher information only. Both the Fisher information and the length of the local wave vector are descriptors of the spherically symmetric Coulomb systems. © 2014 Wiley Periodicals, Inc.

NTChem: A high‐performance software package for quantum molecular simulation

Abstract: In this Software News, the authors introduce NTChem, a new comprehensive software package developed in Japan, for ab initio quantum chemistry calculations. It includes various high-performance computational methods and functions for quantum molecular simulations. Furthermore, it is designed for high-performance calculations on a computer with numerous compute nodes. Therefore, it makes optimum use of the K computer's processing power. This Software News specifically examines the parallel performance of NTChem on the K computer. © 2014 Wiley Periodicals, Inc.

Theoretical investigations of the perylene electronic structure: Monomer, dimers, and excimers

Abstract: The structural and electronic properties of perylene molecule, dimers, and excimers have been computationally studied. The present work represents the first systematic study of perylene molecule and dimer forms by means of long-range corrected time-dependent density functional theory (TDDFT) approaches. Initially, the study explores the photophysical properties of the molecular species. Vertical transitions to many excited singlet states have been computed and rationalized with different exchange-correlation functionals. Differences between excitation energies are discussed and compared to the absorption spectrum of perylene in gas phase and diluted solution. De-excitation energy from the relaxed geometry of the lowest excited singlet is in good agreement with the experimental fluorescence emission. Optimization of several coplanar forms of the perylene pair prove that, contrary to generalized gradient approximation (GGA) and hybrid exchange-correlation functionals, corrected TDDFT is able to bind the perylene dimer in the ground state. Excitation energies from different dimer conformers point to dimer formation prior to photoexcitation. The fully relaxed excimer geometry belongs to the perfectly eclipsed conformation with D2h symmetry. The excimer equilibrium intermolecular distance is shorter than the separation found for the ground state, which is an indication of stronger interchromophore interaction in the excimer state. Excimer de-excitation energy is in rather good agreement with the excimer band of perylene in concentrated solution. The study also scans the energy profiles of the ground and lowest excited states along several geometrical distortions. The nature of the interactions responsible for the excimer stabilization is explored in terms of excitonic and charge resonance contributions. © 2015 Wiley Periodicals, Inc.

Biphenyl: A stress tensor and vector‐based perspective explored within the quantum theory of atoms in molecules

Abstract: We use quantum theory of atoms in molecules (QTAIM) and the stress tensor topological approaches to explain the effects of the torsion φ of the C-C bond linking the two phenyl rings of the biphenyl molecule on a bond-by-bond basis using both a scalar and vector-based analysis. Using the total local energy density H(rb), we show the favorable conditions for the formation of the controversial H–H bonding interactions for a planar biphenyl geometry. This bond-by-bond QTAIM analysis is found to be agreement with an earlier alternative QTAIM atom-by-atom approach that indicated that the H–H bonding interaction provided a locally stabilizing effect that is overwhelmed by the destabilizing role of the C-C bond. This leads to a global destabilization of the planar biphenyl conformation compared with the twisted global minimum. In addition, the H(rb) analysis showed that only the central torsional C-C bond indicated a minimum for a torsion φ value coinciding with that of the conventional global energy minimum. The H–H bonding interactions are found to be topologically unstable for any torsion of the central C-C bond away from the planar biphenyl geometry. Conversely, we demonstrate that for 0.0° < φ < 39.95° there is a resultant increase in the topological stability of the C nuclei comprising the central torsional C-C bond. Evidence is found of the effect of the H–H bonding interactions on the torsion φ of the central C-C bond of the biphenyl molecule in the form of the QTAIM response β of the total electronic charge density ρ(rb). Using a vector-based treatment of QTAIM we confirm the presence of the sharing of chemical character between adjacent bonds. In addition, we present a QTAIM interpretation of hyperconjugation and conjugation effects, the former was quantified as larger in agreement with molecular orbital (MO) theory. The stress tensor and the QTAIM H atomic basin path set areas are independently found to be new tools relevant for the incommensurate gas to solid phase transition occurring in biphenyl for a value of the torsion reaction coordinate φ ≈ 5°. © 2015 Wiley Periodicals, Inc.