Mathew D. Halls

Automated Transition State Search and Its Application to Diverse Types of Organic Reactions

Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.

Surface etching, chemical modification and characterization of silicon nitride and silicon oxide--selective functionalization of Si3N4 and SiO2.

The ability to selectively chemically functionalize silicon nitride (Si3N4) or silicon dioxide (SiO2) surfaces after cleaning would open interesting technological applications. In order to achieve this goal, the chemical composition of surfaces needs to be carefully characterized so that target chemical reactions can proceed on only one surface at a time. While wet-chemically cleaned silicon dioxide surfaces have been shown to be terminated with surficial Si-OH sites, chemical composition of the HF-etched silicon nitride surfaces is more controversial. In this work, we removed the native oxide under various aqueous HF-etching conditions and studied the chemical nature of the resulting Si3N4 surfaces using infrared absorption spectroscopy (IRAS), x-ray photoelectron spectroscopy (XPS), low energy ion scattering (LEIS), and contact angle measurements. We find that HF-etched silicon nitride surfaces are terminated by surficial Si-F and Si-OH bonds, with slightly subsurface Si-OH, Si-O-Si, and Si-NH2 groups. The concentration of surficial Si-F sites is not dependent on HF concentration, but the distribution of oxygen and Si-NH2 displays a weak dependence. The Si-OH groups of the etched nitride surface are shown to react in a similar manner to the Si-OH sites on SiO2, and therefore no selectivity was found. Chemical selectivity was, however, demonstrated by first reacting the -NH2 groups on the etched nitride surface with aldehyde molecules, which do not react with the Si-OH sites on a SiO2 surface, and then using trichloro-organosilanes for selective reaction only on the SiO2 surface (no reactivity on the aldehyde-terminated Si3N4 surface).

Virtual screening of electron acceptor materials for organic photovoltaic applications

Virtual screening involves the generation of structure libraries, automated analysis to predict properties related to application performance and subsequent screening to identify lead systems and estimate critical structure–property limits across a targeted chemical design space. This approach holds great promise for informing experimental discovery and development efforts for next-generation materials, such as organic semiconductors. In this work, the virtual screening approach is illustrated for nitrogen-substituted pentacene molecules to identify systems for development as electron acceptor materials for use in organic photovoltaic (OPV) devices. A structure library of tetra-azapentacenes (TAPs) was generated by substituting four nitrogens for CH at 12 sites on the pentacene molecular framework. Molecular properties (e.g. ELUMO, Eg and μ) were computed for each candidate structure using hybrid DFT at the B3LYP/6-311G** level of theory. The resulting TAPs library was then analyzed with respect to intrinsic properties associated with OPV acceptor performance. Marcus reorganization energies for charge transport for the most favorable TAP candidates were then calculated to further determine suitability as OPV electron acceptors. The synthesis, characterization and OPV device testing of TAP materials is underway, guided by these results.

Highly efficient implementation of pseudospectral time-dependent density-functional theory for the calculation of excitation energies of large molecules.

We have developed and implemented pseudospectral time‐dependent density‐functional theory (TDDFT) in the quantum mechanics package Jaguar to calculate restricted singlet and restricted triplet, as well as unrestricted excitation energies with either full linear response (FLR) or the Tamm–Dancoff approximation (TDA) with the pseudospectral length scales, pseudospectral atomic corrections, and pseudospectral multigrid strategy included in the implementations to improve the chemical accuracy and to speed the pseudospectral calculations. The calculations based on pseudospectral time‐dependent density‐functional theory with full linear response (PS‐FLR‐TDDFT) and within the Tamm–Dancoff approximation (PS‐TDA‐TDDFT) for G2 set molecules using B3LYP/6‐31G** show mean and maximum absolute deviations of 0.0015 eV and 0.0081 eV, 0.0007 eV and 0.0064 eV, 0.0004 eV and 0.0022 eV for restricted singlet excitation energies, restricted triplet excitation energies, and unrestricted excitation energies, respectively; compared with the results calculated from the conventional spectral method. The application of PS‐FLR‐TDDFT to OLED molecules and organic dyes, as well as the comparisons for results calculated from PS‐FLR‐TDDFT and best estimations demonstrate that the accuracy of both PS‐FLR‐TDDFT and PS‐TDA‐TDDFT. Calculations for a set of medium‐sized molecules, including Cn fullerenes and nanotubes, using the B3LYP functional and 6‐31G** basis set show PS‐TDA‐TDDFT provides 19‐ to 34‐fold speedups for Cn fullerenes with 450–1470 basis functions, 11‐ to 32‐fold speedups for nanotubes with 660–3180 basis functions, and 9‐ to 16‐fold speedups for organic molecules with 540–1340 basis functions compared to fully analytic calculations without sacrificing chemical accuracy. The calculations on a set of larger molecules, including the antibiotic drug Ramoplanin, the 46‐residue crambin protein, fullerenes up to C540 and nanotubes up to 14×(6,6), using the B3LYP functional and 6‐31G** basis set with up to 8100 basis functions show that PS‐FLR‐TDDFT CPU time scales as N2.05 with the number of basis functions.

High-throughput quantum chemistry and virtual screening for OLED material components

Computational structure enumeration, analysis using an automated simulation workflow and filtering of large chemical structure libraries to identify lead systems, has become a central paradigm in drug discovery research. Transferring this paradigm to challenges in materials science is now possible due to advances in the speed of computational resources and the efficiency and stability of chemical simulation packages. State-of-the-art software tools that have been developed for drug discovery can be applied to efficiently explore the chemical design space to identify solutions for problems such as organic light-emitting diode material components. In this work, virtual screening for OLED materials based on intrinsic quantum mechanical properties is illustrated. Also, a new approach to more reliably identify candidate systems is introduced that is based on the chemical reaction energetics of defect pathways for OLED materials.

Accelerated discovery of OLED materials through atomic-scale simulation

Organic light-emitting diode (OLED) devices are under widespread investigation to displace or complement inorganic optoelectronic devices for solid-state lighting and active displays. The materials in these devices are selected or designed according to their intrinsic and extrinsic electronic properties with concern for efficient charge injection and transport, and desired stability and light emission characteristics. The chemical design space for OLED materials is enormous and there is need for the development of computational approaches to help identify the most promising solutions for experimental development. In this work we will present examples of simulation approaches available to efficiently screen libraries of potential OLED materials; including first-principles prediction of key intrinsic properties, and classical simulation of amorphous morphology and stability. Also, an alternative to exhaustive computational screening is introduced based on a biomimetic evolutionary framework; evolving the molecular structure in the calculated OLED property design space.

Atomic layer deposition of dopants for recoil implantation in finFET sidewalls

The doping of finFET sidewalls is studied using glancing angle, energetic ion beam recoil mixing of dopant-rich layers made by atomic layer deposited (ALD) films on vertical Si(100) surfaces. Density Function Theory (DTF) calculations show that surface conditions for initiating ALD with BF3 and PF3 dopants favor hydroxyl-Si surface termination. Monte Carlo calculations of the recoil-delivered-B highlights the process control advantages of grazing angle incidence energetic ion beams, as long as the deposited dopant layers are well controlled in thickness and composition, as one expects from ALD methods.

In silico evaluation of highly efficient organic light-emitting materials

Design and development of highly efficient organic and organometallic dopants is one of the central challenges in the organic light-emitting diodes (OLEDs) technology. Recent advances in the computational materials science have made it possible to apply computer-aided evaluation and screening framework directly to the design space of organic lightemitting diodes (OLEDs). In this work, we will showcase two major components of the latest in silico framework for development of organometallic phosphorescent dopants – (1) rapid screening of dopants by machine-learned quantum mechanical models and (2) phosphorescence lifetime predictions with spin-orbit coupled calculations (SOC-TDDFT). The combined work of virtual screening and evaluation would significantly widen the design space for highly efficient phosphorescent dopants with unbiased measures to evaluate performance of the materials from first principles.

Optical simulations for fractional fluorine terminated coatings on nanoimprint lithography masks

Simulations of the optical intensity within Nano Imprint Lithography (NIL) mask features have been made for patterned quartz masks having ultrathin film coatings with different indices of refraction. Fractionally fluorine terminated surfaces, previously proposed for improving the yield of NIL processes, are briefly reviewed. Optical intensity solutions within the feature were obtained using Panoramictech Maxwell solver software for variances in the optical constants of the coating films, aspect ratio, feature size, and wavelength.. The coated masks have conformal surface, higher index of refraction under-layer coating and a fractional terminated fluorine hydrocarbon (FHC) monomolecular layer. The values of optical constants for the FHC layers are unknown, so a range of ad-hoc values were simulated. Optical constants for quartz mask and Al2O3, TiO2 and Si under-layer films are taken from the literature. Wavelengths were varied from 193nm to 365nm. The question of photo-dissociation of the FHC layer for higher energy photons is addressed from first principles, with the result that the F-terminated layers are stable at higher wavelengths. Preliminary simulations for features filled with resist over various substrates are dependent on the antireflection character of the underlying film system. The optical intensity is generally increased within the simulated mask feature when coated with a higher index/FHC films relative to the uncoated reference quartz mask for ~5nm physical feature sizes.

Fluorine coatings for nanoimprint lithography masks

A structure and method for coating Nano Imprint Lithography (NIL) masks is described. The approach uses conformal ALD layering methods and sequential monomolecular depositions. The processes describe chemically bonded, high density, smooth coatings having fractional fluorine terminations. Various molecular precursor mixtures or various reactive surface site chemical functionalization schemes allow the attainment of controlled percentages of fractional F-terminations. The percentage of fluorine terminations is adjustable and controllable from 0% to 100%. Chemistries are described that result in coating layers of the order of ~1nm. These fractional F-terminated coatings may be useful for the reduction and minimization of defects in advanced imprint lithography processes.