Quantum Mechanics Studies of Fuel Cell Catalysts and Proton Conducting Ceramics with Validation by Experiment

We carried out quantum mechanics (QM) studies aimed at improving the performance of hydrogen fuel cells. This led to predictions of improved materials, some of which were subsequently validated with experiments by our collaborators.

In part I, the challenge was to find a replacement for the Pt cathode that would lead to improved performance for the Oxygen Reduction Reaction (ORR) while remaining stable under operational conditions and decreasing cost. Our design strategy was to find an alloy with composition Pt3M that would lead to surface segregation such that the top layer would be pure Pt, with the second and subsequent layers richer in M. Under operating conditions we expect the surface to have significant O and/or OH chemisorbed on the surface, and hence we searched for M that would remain segregated under these conditions. Using QM we examined surface segregation for 28 Pt₃M alloys, where M is a transition metal. We found that only Pt₃Os and Pt₃Ir showed significant surface segregation when O and OH are chemisorbed on the catalyst surfaces. This result indicates that Pt₃Os and Pt3Ir favor formation of a Pt-skin surface layer structure that would resist the acidic electrolyte corrosion during fuel cell operation environments. We chose to focus on Os because the phase diagram for Pt-Ir indicated that Pt-Ir could not form a homogeneous alloy at lower temperature. To determine the performance for ORR, we used QM to examine all intermediates, reaction pathways, and reaction barriers involved in the processes for which protons from the anode reactions react with O₂ to form H₂O. These QM calculations used our Poisson-Boltzmann implicit solvation model include the effects of the solvent (water with dielectric constant 78 with pH 7 at 298K). We found that the rate determination step (RDS) was the O_ad hydration reaction (O_ad + H₂O_ad -> OH_ad + OH_ad) in both cases, but that the barrier for pure Pt of 0.50 eV is reduced to 0.48 eV for Pt₃Os, which at 80 degrees C would increase the rate by 218%. We collaborated with the Pu-Wei Wu’s group to carry out experiments, where we found that the dealloying process-treated Pt2Os catalyst showed two-fold higher activity at 25 degrees C than pure Pt and that the alloy had 272% improved stability, validating our theoretical predictions.

We also carried out similar QM studies followed by experimental validation for the Os/Pt core-shell catalyst fabricated by the underpotential deposition (UPD) method. The QM results indicated that the RDS for ORR is a compromise between the OOH formation step (0.37 eV for Pt, 0.23 eV for Pt_2ML/Os core-shell) and H₂O formation steps (0.32 eV for Pt, 0.22 eV for Pt_2ML/Os core-shell). We found that Pt_2ML/Os has the highest activity (compared to pure Pt and to the Pt₃Os alloy) because the 0.37 eV barrier decreases to 0.23 eV. To understand what aspects of the core shell structure lead to this improved performance, we considered the effect on ORR of compressing the alloy slab to the dimensions of pure Pt. However this had little effect, with the same RDS barrier 0.37 eV. This shows that the ligand effect (the electronic structure modification resulting from the Os substrate) plays a more important role than the strain effect, and is responsible for the improved activity of the core- shell catalyst. Experimental materials characterization proves the core-shell feature of our catalyst. The electrochemical experiment for Pt_2ML/Os/C showed 3.5 to 5 times better ORR activity at 0.9V (vs. NHE) in 0.1M HClO₄ solution at 25 degrees C as compared to those of commercially available Pt/C. The excellent correlation between experimental half potential and the OH binding energies and RDS barriers validate the feasibility of predicting catalyst activity using QM calculation and a simple Langmuir–Hinshelwood model.

In part II, we used QM calculations to study methane stream reforming on a Ni-alloy catalyst surfaces for solid oxide fuel cell (SOFC) application. SOFC has wide fuel adaptability but the coking and sulfur poisoning will reduce its stability. Experimental results suggested that the Ni4Fe alloy improves both its activity and stability compared to pure Ni. To understand the atomistic origin of this, we carried out QM calculations on surface segregation and found that the most stable configuration for Ni₄Fe has a Fe atom distribution of (0%, 50%, 25%, 25%, 0%) starting at the bottom layer. We calculated that the binding of C atoms on the Ni4Fe surface is 142.9 Kcal/mol, which is about 10 Kcal/mol weaker compared to the pure Ni surface. This weaker C binding energy is expected to make coke formation less favorable, explaining why Ni₄Fe has better coking resistance. This result confirms the experimental observation. The reaction energy barriers for CHx decomposition and C binding on various alloy surface, Ni₄X (X=Fe, Co, Mn, and Mo), showed Ni₄Fe, Ni₄Co, and Fe₄Mn all have better coking resistance than pure Ni, but that only Ni₄Fe and Fe₄Mn have (slightly) improved activity compared to pure Ni.

In part III, we used QM to examine the proton transport in doped perovskite-ceramics. Here we used a 2x2x2 supercell of perovskite with composition Ba₈X₇M₁(OH)₁O₂₃ where X=Ce or Zr and M=Y, Gd, or Dy. Thus in each case a 4⁺ X is replace by a 3⁺ M plus a proton on one O. Here we predicted the barriers for proton diffusion allowing both includes intra-octahedron and inter-octahedra proton transfer. Without any restriction, we only observed the inter-octahedra proton transfer with similar energy barrier as previous computational work but 0.2 eV higher than experimental result for Y doped zirconate. For one restriction in our calculations is that the O_donor-O_acceptor atoms were kept at fixed distances, we found that the barrier difference between cerates/zirconates with various dopants are only 0.02~0.03 eV. To fully address performance one would need to examine proton transfer at grain boundaries, which will require larger scale ReaxFF reactive dynamics for systems with millions of atoms. The QM calculations used here will be used to train the ReaxFF force field.

Protein structure refinement algorithms

Protein structure prediction has remained a major challenge in structural biology for more than half a century. Accelerated and cost efficient sequencing technologies have allowed researchers to sequence new organisms and discover new protein sequences. Novel protein structure prediction technologies will allow researchers to study the structure of proteins and to determine their roles in the underlying biology processes and develop novel therapeutics.

Difficulty of the problem stems from two folds: (a) describing the energy landscape that corresponds to the protein structure, commonly referred to as force field problem; and (b) sampling of the energy landscape, trying to find the lowest energy configuration that is hypothesized to be the native state of the structure in solution. The two problems are interweaved and they have to be solved simultaneously. This thesis is composed of three major contributions. In the first chapter we describe a novel high-resolution protein structure refinement algorithm called GRID. In the second chapter we present REMCGRID, an algorithm for generation of low energy decoy sets. In the third chapter, we present a machine learning approach to ranking decoys by incorporating coarse-grain features of protein structures.

Structure Prediction of G-Protein Coupled Receptors

G-protein coupled receptors (GPCRs) form a large family of proteins and are very important drug targets. They are membrane proteins, which makes computational prediction of their structure challenging. Homology modeling is further complicated by low sequence similarly of the GPCR superfamily.

In this dissertation, we analyze the conserved inter-helical contacts of recently solved crystal structures, and we develop a unified sequence-structural alignment of the GPCR superfamily. We use this method to align 817 human GPCRs, 399 of which are nonolfactory. This alignment can be used to generate high quality homology models for the 817 GPCRs.

To refine the provided GPCR homology models we developed the Trihelix sampling method. We use a multi-scale approach to simplify the problem by treating the transmembrane helices as rigid bodies. In contrast to Monte Carlo structure prediction methods, the Trihelix method does a complete local sampling using discretized coordinates for the transmembrane helices. We validate the method on existing structures and apply it to predict the structure of the lactate receptor, HCAR1. For this receptor, we also build extracellular loops by taking into account constraints from three disulfide bonds. Docking of lactate and 3,5-dihydroxybenzoic acid shows likely involvement of three Arg residues on different transmembrane helices in binding a single ligand molecule.

Protein structure prediction relies on accurate force fields. We next present an effort to improve the quality of charge assignment for large atomic models. In particular, we introduce the formalism of the polarizable charge equilibration scheme (PQEQ) and we describe its implementation in the molecular simulation package Lammps. PQEQ allows fast on the fly charge assignment even for reactive force fields.

Ferromagnetic Resonance Force Microscopy

A new approach to magnetic resonance was introduced in 1992 based upon detection of spin-induced forces by J. Sidles [1]. This technique, now called magnetic resonance force microscopy (MRFM), was first demonstrated that same year via electron paramagnetic resonance (EPR) by D. Rugar et al. [2]. This new method combines principles of magnetic resonance with those of scanned probe technology to detect spin resonance through mechanical, rather than inductive, means. In this thesis the development and use of ferromagnetic resonance force microscopy (FMRFM) is described. This variant of MRFM, which allows investigation of ferromagnetic samples, was first demonstrated in 1996 by Z. Zhang et al. [3]. FMRFM enables characterization of (a) the dynamic magnetic properties of microscale magnetic devices, and (b) the spatial dependence of ferromagnetic resonance within a sample. Both are impossible with conventional ferromagnetic resonance techniques.

Ferromagnetically coupled systems, however, pose unique challenges for force detection. In this thesis the attainable spatial resolution - and the underlying physical mechanisms that determine it - are established. We analyze the dependence of the magnetostatic modes upon sample dimensions using a series of microscale yttrium iron garnet (YIG) samples. Mapping of mode amplitudes within these sample is attained with an unprecedented spatial resolution of 15μm. The modes, never before analyzed on this scale, fit simple models developed in this thesis for samples of micron dimensions. The application of stronger gradient fields induces localized perturbation of the ferromagnetic resonance modes. The first demonstrations of this effect are presented in this study, and a simple theoretical model is developed to explain our observations. The results indicate that the characteristics of the locally-detected ferromagnetic modes are still largely determined by the external fields and dimensions of the entire sample, rather than by the localized interaction volume (i.e., the locale most strongly affected by the local gradient field). Establishing this is a crucial first step toward understanding FMRFM in the high gradient field limit where the dispersion relations become locally determined. In this high gradient field regime, FMRFM imaging becomes analogous with that of EPR MRFM.

FMRFM has also been employed to characterize magnetic multilayers, similar to those utilized in giant magnetoresistance (GMR) devices, on a lateral scale 40 x 40μm. This is orders of magnitude smaller than possible via conventional methods. Anisotropy energies, thickness, and interface qualities of individual layers have been resolved.

This initial work clearly demonstrates the immense and unique potential that FMRFM offers for characterizing advanced magnetic nanostructures and magnetic devices.

Plasma loop and strapping field dynamics: reproducing solar eruptions in the laboratory

Coronal mass ejections (CMEs) are dramatic eruptions of large, plasma structures from the Sun. These eruptions are important because they can harm astronauts, damage electrical infrastructure, and cause auroras. A mysterious feature of these eruptions is that plasma-filled solar flux tubes first evolve slowly, but then suddenly erupt. One model, torus instability, predicts an explosive-like transition from slow expansion to fast acceleration, if the spatial decay of the ambient magnetic field exceeds a threshold.

We create arched, plasma filled, magnetic flux ropes similar to CMEs. Small, independently-powered auxiliary coils placed inside the vacuum chamber produce magnetic fields above the decay threshold that are strong enough to act on the plasma. When the strapping field is not too strong and not too weak, expansion force build up while the flux rope is in the strapping field region. When the flux rope moves to a critical height, the plasma accelerates quickly, corresponding to the observed slow-rise to fast-acceleration of most solar eruptions. This behavior is in agreement with the predictions of torus instability.

Historically, eruptions have been separated into gradual CMEs and impulsive CMEs, depending on the acceleration profile. Recent numerical studies question this separation. One study varies the strapping field profile to produce gradual eruptions and impulsive eruptions, while another study varies the temporal profile of the voltage applied to the flux tube footpoints to produce the two eruption types. Our experiment reproduced these different eruptions by changing the strapping field magnitude, and the temporal profile of the current trace. This suggests that the same physics underlies both types of CME and that the separation between impulsive and gradual classes of eruption is artificial.

Field and Laboratory Studies of Atmospheric Organic Aerosol

This thesis is the culmination of field and laboratory studies aimed at assessing processes that affect the composition and distribution of atmospheric organic aerosol. An emphasis is placed on measurements conducted using compact and high-resolution Aerodyne Aerosol Mass Spectrometers (AMS). The first three chapters summarize results from aircraft campaigns designed to evaluate anthropogenic and biogenic impacts on marine aerosol and clouds off the coast of California. Subsequent chapters describe laboratory studies intended to evaluate gas and particle-phase mechanisms of organic aerosol oxidation.

The 2013 Nucleation in California Experiment (NiCE) was a campaign designed to study environments impacted by nucleated and/or freshly formed aerosol particles. Terrestrial biogenic aerosol with > 85% organic mass was observed to reside in the free troposphere above marine stratocumulus. This biogenic organic aerosol (BOA) originated from the Northwestern United States and was transported to the marine atmosphere during periodic cloud-clearing events. Spectra recorded by a cloud condensation nuclei counter demonstrated that BOA is CCN active. BOA enhancements at latitudes north of San Francisco, CA coincided with enhanced cloud water concentrations of organic species such as acetate and formate.

Airborne measurements conducted during the 2011 Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) were aimed at evaluating the contribution of ship emissions to the properties of marine aerosol and clouds off the coast of central California. In one study, analysis of organic aerosol mass spectra during periods of enhanced shipping activity yielded unique tracers indicative of cloud-processed ship emissions (m/z 42 and 99). The variation of their organic fraction (f₄₂ and f₉₉) was found to coincide with periods of heavy (f₄₂ > 0.15; f₉₉ > 0.04), moderate (0.05 < f₄₂ < 0.15; 0.01 < f₉₉ < 0.04), and negligible (f₄₂ < 0.05; f₉₉ < 0.01) ship influence. Application of these conditions to all measurements conducted during E-PEACE demonstrated that a large fraction of cloud droplet (72%) and dry aerosol mass (12%) sampled in the California coastal study region was heavily or moderately influenced by ship emissions. Another study investigated the chemical and physical evolution of a controlled organic plume emitted from the R/V Point Sur. Under sunny conditions, nucleated particles composed of oxidized organic compounds contributed nearly an order of magnitude more cloud condensation nuclei (CCN) than less oxidized particles formed under cloudy conditions. The processing time necessary for particles to become CCN active was short ( < 1 hr) compared to the time needed for particles to become hygroscopic at sub-saturated humidity ( > 4 hr).

Laboratory chamber experiments were also conducted to evaluate particle-phase processes influencing aerosol phase and composition. In one study, ammonium sulfate seed was coated with a layer of secondary organic aerosol (SOA) from toluene oxidation followed by a layer of SOA from α-pinene oxidation. The system exhibited different evaporative properties than ammonium sulfate seed initially coated with α-pinene SOA followed by a layer of toluene SOA. This behavior is consistent with a shell-and-core model and suggests limited mixing among different SOA types. Another study investigated the reactive uptake of isoprene epoxy diols (IEPOX) onto non-acidified aerosol. It was demonstrated that particle acidity has limited influence on organic aerosol formation onto ammonium sulfate seed, and that the chemical system is limited by the availability of nucleophiles such as sulfate.

Flow tube experiments were conducted to examine the role of iron in the reactive uptake and chemical oxidation of glycolaldehyde. Aerosol particles doped with iron and hydrogen peroxide were mixed with gas-phase glycolaldehyde and photochemically aged in a custom-built flow reactor. Compared to particles free of iron, iron-doped aerosols significantly enhanced the oxygen to carbon (O/C) ratio of accumulated organic mass. The primary oxidation mechanism is suggested to be a combination of Fenton and photo-Fenton reactions which enhance particle-phase OH radical concentrations.