Quantum Chemistry in Nanoscale Environments: Insights on Surface-Enhanced Raman Scattering and Organic Photovoltaics

The understanding of molecular effects in nanoscale environments is becoming increasingly relevant for various emerging fields. These include spectroscopy for molecular identification as well as in finding molecules for energy harvesting. Theoretical quantum chemistry has been increasingly useful to address these phenomena to yield an understanding of these effects. In the first part of this dissertation, we study the chemical effect of surface-enhanced Raman scattering (SERS). We use quantum chemistry simulations to study the metal-molecule interactions present in these systems. We find that the excitations that provide a chemical enhancement contain a mixed contribution from the metal and the molecule. Moreover, using atomistic studies we propose an additional source of enhancement, where a transition metal dopant surface could provide an additional enhancement. We also develop methods to study the electrostatic effects of molecules in metallic environments. We study the importance of image-charge effects, as well as field-bias to molecules interacting with perfect conductors. The atomistic modeling and the electrostatic approximation enable us to study the effects of the metal interacting with the molecule in a complementary fashion, which provides a better understanding of the complex effects present in SERS. In the second part of this dissertation, we present the Harvard Clean Energy project, a high-throughput approach for a large-scale computational screening and design of organic photovoltaic materials. We create molecular libraries to search for candidates structures and use quantum chemistry, machine learning and cheminformatics methods to characterize these systems and find structure-property relations. The scale of this study requires an equally large computational resource. We rely on distributed volunteer computing to obtain these properties. In the third part of this dissertation we present our work related to the acceleration of electronic structure methods using graphics processing units. This hardware represents a change of paradigm with respect to the typical CPU device architectures. We accelerate the resolution-of-the-identity Moller-Plesset second-order perturbation theory algorithm using graphics cards. We also provide detailed tools to address memory and single-precision issues that these cards often present

Creating a GUI for Zori, a Quantum Monte Carlo Program

Rappture is a new GUI development kit that enables developers to build I/O interfaces for specific applications. In this article, the authors describe the Rappture toolkit's use in generating a GUI for the Zori computer code

Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units

Graphical processing units are now being used with dramatic effect to accelerate quantum chemistry calculations. However, early work exposed challenges involving memory bottlenecks and insufficient numerical precision. This research effort addresses those issues, proposing two new tools for accelerating matrix multiplications of arbitrary size where single-precision accuracy is not enough.Chemistry and Chemical Biolog

Anion Stabilization in Electrostatic Environments

Excess charge stabilization of molecules in metallic environments is of particular importance for fields such as molecular electronics and surface chemistry. We study the energetics of benzene and its anion between two metallic plates. We observe that orientational effects are important at small inter-plate separation. This leads to benzene oriented perpendicular to the gates being more stable than the parallel case due to induced dipole effects. We find that the benzene anion, known for being unstable in the gas-phase, is stabilized by the plates at zero bias and an inter-plate distance of 21 Å. We also observe the effect of benzene under a voltage bias generated by the plates; under a negative bias, the anion becomes destabilized. We use the electron localization function to analyze the changes in electron density due to the bias. These findings suggest that image effects such as those present in nanoscale devices, are able to stabilize excess charge and should be important to consider when modeling molecular transport junctions and charge-transfer effects.Chemistry and Chemical Biolog

Electronic Structure Calculations in Arbitrary Electrostatic Environment

Modeling of electronic structure of molecules in electrostatic environments is of considerable relevance for surface-enhanced spectroscopy and molecular electronics. We have developed and implemented a novel approach to the molecular electronic structure in arbitrary electrostatic environments that is compatible with standard quantum chemical methods and can be applied to medium-sized and large molecules. The scheme denoted CheESE (chemistry in electrostatic environments) is based on the description of molecular electronic structure subject to a boundary condition on the system/environment interface. Thus, it is particularly suited to study molecules on metallic surfaces. The proposed model is capable of describing both electrostatic effects near nanostructured metallic surfaces and image-charge effects. We present an implementation of the CheESE model as a library module and show example applications to neutral and negatively charged molecules.Chemistry and Chemical Biolog

Accelerating Resolution-of-the-Identity Second Order Møller-Plesset Quantum Chemistry Calculations with Graphical Processing Units

The modification of a general purpose code for quantum mechanical calculations of molecular properties (Q-Chem) to use a graphical processing unit (GPU) is reported. A 4.3x speedup of the resolution-of-the-identity second-order Møller−Plesset perturbation theory (RI-MP2) execution time is observed in single point energy calculations of linear alkanes. The code modification is accomplished using the compute unified basic linear algebra subprograms (CUBLAS) library for an NVIDIA Quadro FX 5600 graphics card. Furthermore, speedups of other matrix algebra based electronic structure calculations are anticipated as a result of using a similar approach.Chemistry and Chemical Biolog

Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units and a Mixed Precision Matrix Multiplication Library

Two new tools for the acceleration of computational chemistry codes using graphical processing units (GPUs) are presented. First, we propose a general black-box approach for the efficient GPU acceleration of matrix−matrix multiplications where the matrix size is too large for the whole computation to be held in the GPU’s onboard memory. Second, we show how to improve the accuracy of matrix multiplications when using only single-precision GPU devices by proposing a heterogeneous computing model, whereby single- and double-precision operations are evaluated in a mixed fashion on the GPU and central processing unit, respectively. The utility of the library is illustrated for quantum chemistry with application to the acceleration of resolution-of-the-identity second-order Møller−Plesset perturbation theory calculations for molecules, which we were previously unable to treat. In particular, for the 168-atom valinomycin molecule in a cc-pVDZ basis set, we observed speedups of 13.8, 7.8, and 10.1 times for single-, double- and mixed-precision general matrix multiply (SGEMM, DGEMM, and MGEMM), respectively. The corresponding errors in the correlation energy were reduced from −10.0 to −1.2 kcal mol$^{-1}$ for SGEMM and MGEMM, respectively, while higher accuracy can be easily achieved with a different choice of cutoff parameter.Chemistry and Chemical Biolog

Accelerated Computational Discovery of High-Performance Materials for Organic Photovoltaics by Means of Cheminformatics

In this perspective we explore the use of strategies from drug discovery, pattern recognition, and machine learning in the context of computational materials science. We focus our discussion on the development of donor materials for organic photovoltaics by means of a cheminformatics approach. These methods enable the development of models based on molecular descriptors that can be correlated to the important characteristics of the materials. Particularly, we formulate empirical models, parametrized using a training set of donor polymers with available experimental data, for the important current–voltage and efficiency characteristics of candidate molecules. The descriptors are readily computed which allows us to rapidly assess key quantities related to the performance of organic photovoltaics for many candidate molecules. As part of the Harvard Clean Energy Project, we use this approach to quickly obtain an initial ranking of its molecular library with 2.6 million candidate compounds. Our method reveals molecular motifs of particular interest, such as the benzothiadiazole and thienopyrrole moieties, which are present in the most promising set of molecules.Chemistry and Chemical Biolog

Quantum Chemical Approach to Estimating the Thermodynamics of Metabolic Reactions

Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfer reactions and for reactions not including multiply charged anions. The errors in standard Gibbs reaction energy estimates are correlated with the charges of the participating molecules. The quantum chemical approach is amenable to systematic improvements and holds potential for providing thermodynamic data for all of metabolism.Chemistry and Chemical Biolog

Time-Dependent Density Functional Theory of Open Quantum Systems in the Linear-Response Regime

Time-Dependent Density Functional Theory (TDDFT) has recently been extended to describe many-body open quantum systems (OQS) evolving under non-unitary dynamics according to a quantum master equation. In the master equation approach, electronic excitation spectra are broadened and shifted due to relaxation and dephasing of the electronic degrees of freedom by the surrounding environment. In this paper, we develop a formulation of TDDFT linear-response theory (LR-TDDFT) for many-body electronic systems evolving under a master equation, yielding broadened excitation spectra. This is done by mapping an interacting open quantum system onto a non-interacting open Kohn-Sham system yielding the correct non-equilibrium density evolution. A pseudo-eigenvalue equation analogous to the Casida equations of usual LR-TDDFT is derived for the Redfield master equation, yielding complex energies and Lamb shifts. As a simple demonstration, we calculate the spectrum of a C$^{2+}$ atom in an optical resonator interacting with a bath of photons. The performance of an adiabatic exchange-correlation kernel is analyzed and a first-order frequency-dependent correction to the bare Kohn-Sham linewidth based on Gorling-Levy perturbation theory is calculated.Comment: 18 pages, 4 figure