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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

In Situ Chemical Imaging of Solid-Electrolyte Interphase Layer Evolution in Li–S Batteries

Parasitic reactions of electrolyte and polysulfide with the Li-anode in lithium sulfur (Li-S) batteries lead to the for-mation of solid electrolyte interphase (SEI) layers, which are the major reason behind severe capacity fading in these systems. Despite numerous studies, the evolution mechanism of the SEI layer and specific roles of polysulfides and oth-er electrolyte components are still unclear. We report an in-situ X-ray photoelectron spectroscopy (XPS) and chemical imaging analysis combined with ab initio molecular dynamics (AIMD) computational modeling to gain fundamental understanding regarding the evolution of SEI layers on Li-anodes within Li-S batteries. A multi-modal approach in-volving AIMD modeling and in-situ XPS characterization uniquely reveals the chemical identity and distribution of active participants in parasitic reactions as well as the SEI layer evolution mechanism. The SEI layer evolution has three major stages: the formation of a primary composite mixture phase involving stable lithium compounds (Li2S, LiF, Li2O etc); and formation of a secondary matrix type phase due to cross interaction between reaction products and elec-trolyte components, which is followed by a highly dynamic mono-anionic polysulfide (i.e. LiS5) fouling process. These new molecular-level insights into the SEI layer evolution on Li- anodes are crucial for delineating effective strategies for the development of Li–S batteries.

25 ENERGY STORAGE↗
DOE OSTI2016

Low-Order Modeling of Internal Heat Transfer in Biomass Particle Pyrolysis

We present a computationally efficient, one-dimensional simulation methodology for biomass particle heating under conditions typical of fast pyrolysis. Our methodology is based on identifying the rate limiting geometric and structural factors for conductive heat transport in biomass particle models with realistic morphology to develop low-order approximations that behave appropriately. Comparisons of transient temperature trends predicted by our one-dimensional method with three-dimensional simulations of woody biomass particles reveal good agreement, if the appropriate equivalent spherical diameter and bulk thermal properties are used. We conclude that, for particle sizes and heating regimes typical of fast pyrolysis, it is possible to simulate biomass particle heating with reasonable accuracy and minimal computational overhead, even when variable size, aspherical shape, anisotropic conductivity, and complex, species-specific internal pore geometry are incorporated.

09 BIOMASS FUELS↗
DOE OSTI2023

Molecular Geometry and Electronic Structure of Copper Corroles

Copper corroles are known for their unique multiconfigurational electronic structures in the ground state, which arise from the transfer of electrons from the π orbitals of the corrole to the d-orbital of copper. While density functional theory (DFT) provides reasonably good molecular geometries, the determination of the ground spin state and the associated energetics is heavily influenced by functional choice, particularly the percentage of the Hartree–Fock exchange. Using extended multireference perturbation theory methods (XMS-CASPT2), the functional choice can be assessed. The molecular geometries and electronic structures of both the unsubstituted and the meso-triphenyl copper corroles were investigated. A minimal active space was employed for structural characterization, while larger active spaces are required to examine the electronic structure. The XMS-CASPT2 investigations conclusively identify the ground electronic state as a multiconfigurational singlet (S o ) with three dominant electronic configurations in its lowest energy and characteristic saddled structure. In contrast, the planar geometry corresponds to the triplet state (T o ), which is approximately 5 kcal/mol higher in energy compared to the S o state for both the bare and substituted copper corroles. Notably, the planarity of the T o geometry is reduced in the substituted corrole compared with that in the unsubstituted one. By analyzing the potential energy surface (PES) between the S o and T o geometries using XMS-CASPT2, the multiconfigurational electronic structure is shown to transition toward a single electron configuration as the saddling angle decreases (i.e., as one approaches the planar geometry). Despite the ability of the functionals to reproduce the minimum energy structures, only the TPSSh-D 3 PES is reasonably close to the XMS-CASPT2 surface. Significant deviations along the PES are observed with other functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Components of the Bond Energy in Polar Diatomic Molecules, Radicals, and Ions Formed by Group-1 and Group-2 Metal Atoms

While many transition metal complexes are known to have high multireference character, the multireference character of main-group closed-shell singlet diatomic molecules like BeF, CaO, and MgO has been less studied. Yet, many group-1 and group-2 diatomic molecules do have multireference character, and they provide informative systems for studying multireference character because they are simpler than transition metal compounds. The goal of the present work is to understand these multireference systems better so that, ultimately, we can apply what we learn to more complicated multireference systems and to the design of new exchange-correlation functionals for treating multireference systems more adequately. Fourteen main-group diatomic molecules and one triatomic molecule (including radicals, cations, and anions, as well as neutral closed-shell species) have been studied for this article. Eight of these molecules contain a group-1 element, and six contain a group-2 element. Seven of these molecules are multireference systems, and eight of them are single-reference systems. Fifty-three exchange-correlation functionals of 11 types [local spin-density approximation (LSDA), generalized gradient approximation (GGA), nonseparable gradient approximation (NGA), global-hybrid GGA, meta-GGA, meta-NGA, global-hybrid meta GGA, range-separated hybrid GGA, range-separated hybrid meta-GGA, range-separated hybrid meta-NGA, and DFT augmented with molecular mechanics damped dispersion (DFT-D)] and the Hartree–Fock method have been applied to calculate the bond distance, bond dissociation energy (BDE), and dipole moment of these molecules. All of the calculations are converged to a stable solution by allowing the symmetry of the Slater determinant to be broken. A reliable functional should not only predict an accurate BDE but also predict accurate components of the BDE, so each bond dissociation energy has been decomposed into ionization potential (IP) of the electropositive element, electron affinity of the electronegative bonding partner (EA), atomic excitation energy (EE) to prepare the valence states of the interacting partners, and interaction energy (IE) of the valence-prepared states. Adding Hartree–Fock exchange helps to obtain better results for atomic excitation energy, and this leads to improvements in getting the right answer for the right reason. The following functionals are singled out for reasonably good performance on all three of bond distance, BDE, and dipole moment: B97-1, B97-3, MPW1B95, M05, M06, M06-2X, M08-SO, N12-SX, O3LYP, TPSS, τ-HCTHhyb, and GAM; all but two (TPSS and GAM) of these functionals are hybrid functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations

We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C7H10O2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules.

Dral, Pavlo O.↗
DOE OSTI2019

Approximate Green’s Function Coupled Cluster A Method Employing Effective Dimension Reduction

The Green’s function coupled cluster (GFCC) method, originally proposed in the early 1990s, is a powerful many-body tool for computing and analyzing the electronic structures of molecular structures and periodic systems, especially when electrons are strongly correlated. However, in order for the GFCC method to become an approach that can be routinely used in the electronic structure calculations, more robust linear algebraic techniques and approximations need to be employed to reduce its extremely high computational overhead. In our recent studies, we showed that the GFCC equation can be numerically solved by seeking solutions of multiple linear systems in the frequency regime of interest, which can be easily distributed in a massively parallel environment, and broaden the avenue for more state-of-the-art numerical linear algebraic tools associated with multiple linear systems to be kicked in to this field. In the present pursuit of this practice, we show a successful application of model order reduction (MOR) techniques in the GFCC framework. Briefly speaking, for a frequency regime of interest that requires a high resolution of spectral function, instead of solving GFCC linear equation in the original dimension for every single frequency point, an easily-solvable linear system model with reduced dimension can be built upon projecting the original GFCC linear system into a subspace, from which the interpolation and extrapolation can give a reasonable approximation to the results of the original GFCC linear equations. Here, we show that the subspace can be properly constructed in an iterative manner from the auxiliary vectors of the GFCC linear equations at some select frequencies inside the frequency regime. During the iterations, the quality of the subspace, as well as the linear system model, can be systematically improved. The approach is tested in this work in terms of the efficiency and accuracy of computing spectral functions for some typical molecular systems including carbon monoxide, 1,3-butadiene, benzene, and adenine molecules. As a byproduct, the high quality linear system model is also found to be able to provide high quality initial guess for the existing linear solver to improve the convergence performance.

Peng, Bo↗
DOE OSTI2021

Constitutive Model of Radiation Aging Effects in Filled Silicone Elastomers under Strain

Filled silicone elastomers, an essential component in many technological applications, are often subjected to controlled or unintended radiation for a variety of reasons. Radiation exposure can lead to permanent mechanical and structural changes in the material, which is manifested as altered mechanical response, and in some cases, a permanent set. For unfilled elastomers, network theories developed and refined over decades can explain these effects in terms of chain-scission and cross-link formation and a hypothesis involving independent networks formed at different strain levels of the material. In this work, we expose a filled silicone rubber to gamma radiation while being under finite elongational strain and show that the observed mechanical and structural changes can be quantitatively modeled within the same theoretical framework developed for unfilled elastomers as long as nuances associated with the Mullins effect are accounted for in a consistent manner. In this work, we employ Ogden’s incompressible hyperelastic model within the framework of Tobolsky’s two-network scheme to describe the observed permanent set and mechanical modulus changes as a function of radiation dosage. In the process, we conclude that gamma radiation induces both direct cross-linking at chain crossings (H-links) and main-chain-scission followed by cross-linking (Y-links). We provide an estimate of the ratio of chain-scission to cross-linking rates, which is in reasonable agreement with previous experimental estimate from Charlesby–Pinner analysis. We use density functional theory (DFT)-based quantum mechanical calculations to explore the stability of –Si and –SiO radicals that form upon a radiation-induced chain-scission event, which sheds light on the relative rates of Y-linking and H-linking processes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Internally Referenced DOSY-NMR: A Novel Analytical Method in Revealing the Solution Structure of Lithium-Ion Battery Electrolytes

Here, a novel methodology is reported on the use of internally referenced diffusion-ordered spectroscopy (IR-DOSY) in divulging the solution structure of lithium-ion battery electrolytes. Toluene was utilized as the internal reference for 1 H-DOSY analysis due to its exceptionally low donor number and reasonable solubility in various electrolytes. With the introduction of the internal reference, the solvent coordination ratio of different species in the electrolytes can be easily determined by 1 H-DOSY or 7 Li-DOSY. This new technique was applied to different carbonate electrolytes, and the results were consistent with a Fourier transform infrared (FTIR) analysis. Compared to conventional vibrational spectroscopy, this IR-DOSY technique avoids the complicated deconvolution of the spectrum and allows determination of the solvent coordination ratio of different species in electrolyte systems with two or more organic solvents.

25 ENERGY STORAGE↗
DOE OSTI2025

Theory of Cation Solvation in the Helmholtz Layer of Li-Ion Battery Electrolytes

The solvation environments of Li + in conventional nonaqueous battery electrolytes, such as LiPF 6 in mixtures of ethylene carbaronate (EC) and ethyl methyl carbonate (EMC), are often used to rationalize transport properties and solid electrolyte interphase (SEI) formation. Solvation environments in the compact electrical double layer (EDL) next to the electrode, also known as the Helmholtz layer, determine (partially) what species can react to form the SEI, with bulk solvation environments often being used as a proxy. Here, we develop and test a theory of cation solvation in the Helmholtz layer of nonaqueous Li-ion battery electrolytes. First, we validate the theory against bulk and diffuse EDL atomistic molecular dynamics (MD) simulations of LiPF 6 EC/EMC mixtures as a function of surface charge, where we find the theory can qualitatively capture the solvation environments. Next, we turn to the Helmholtz layer, where we find the main effect of the solvation structures next to the electrode is an apparent reduction in the number of binding sites between Li + and the solvents, again where we find reasonable agreement with our developed theory. Finally, by solving a simplified version of the theory, we find that the probability of Li + binding to each solvent remains equal to the bulk probability, suggesting that the bulk solvation environments are a reasonable place to start when understanding battery electrolytes. Our developed formalism can be parametrized from bulk MD simulations and used to predict the solvation environments in the Helmholtz layer through reducing the number of available coordination sites, which can be used to determine what could react and form the SEI.

Helmholtz↗
DOE OSTI2017

Core Levels, Band Alignments, and Valence-Band States in CuSbS 2 for Solar Cell Applications

The earth-abundant material CuSbS 2 (CAS) has shown good optical properties as a photovoltaic solar absorber material, but has seen relatively poor solar cell performance. To investigate the reason for this anomaly, the core levels of the constituent elements, surface contaminants, ionization potential, and valence-band spectra are studied by X-ray photoemission spectroscopy. The ionization potential and electron affinity for this material (4.98 and 3.43 eV) are lower than those for other common absorbers, including CuInxGa (1-x) Se 2 (CIGS). Experimentally corroborated density functional theory (DFT) calculations show that the valence band maximum is raised by the lone pair electrons from the antimony cations contributing additional states when compared with indium or gallium cations in CIGS. The resulting conduction band misalignment with CdS is a reason for the poor performance of cells incorporating a CAS/CdS heterojunction, supporting the idea that using a cell design analogous to CIGS is unhelpful. These findings underline the critical importance of considering the electronic structure when selecting cell architectures that optimize open-circuit voltages and cell efficiencies.

14 SOLAR ENERGY↗
DOE OSTI2019

Electrocatalytic Hydrogen Evolution in Neutral pH Solutions: Dual-Phase Synergy

Electrolysis in neutral pH solutions (e.g., wastewater and seawater) presents a transformative way for environmentally friendly, cost-effective hydrogen production. However, one of the biggest challenges is the lack of active, robust hydrogen evolution reaction (HER) catalysts. Herein we present a catalyst with dual active sites of MoP2 and MoP which function synergistically to promote HER in neutral pH solutions. In our microbial electrolysis cell (MEC) which uses neutral pH wastewater as a feedstock, the new catalyst generates an average HER current density of ~157 A m-2Cathode-Surface-Area, higher than Pt/C (~145 A m-2Cathode-Surface-Area), ~5 times higher than the state-of-art platinum-group-metal (PGM)-free catalysts in MECs. The new catalyst also outperforms Pt/C in natural seawater with ~10% higher and more stable HER current density. The fundamental reason for the enhanced HER performance is identified to be the synergy between MoP2 and MoP phases, with MoP2 promoting H2O chemisorption/dissociation and MoP efficiently converting Hads to H2.

Xie, Xiaohong↗
DOE OSTI2024

CACTUS: Chemistry Agent Connecting Tool Usage to Science

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Towards Understanding of Cracking during Drying of Thick Aqueous-Processed LiNi 0.8 Mn 0.1 Co 0.1 O 2 Cathodes

Replacing N-methyl-2-pyrrolidone (NMP) with water for processing of lithium-ion battery (LIB) electrodes has both cost and environmental benefits, which include reduced drying time, lower dryer capital cost, elimination of NMP recovery capital equipment, and no release of volatile organic compounds (VOCs) into the environment. However, aqueous-processed thick cathodes (≳4 mAh/cm 2 ) typically exhibit detrimental cracking during drying that is not observed for the NMP-based counterpart. The reasons for cracking of these water-based thick electrodes are still not well understood due to the complex nature of the colloidal dispersions used in the LIB electrode processing steps. In this work, the contributions of various factors responsible for cracking are discussed. We show that eliminating hydrogen evolution due to corrosion of the aluminum current collector eliminated the majority of the cracks regardless of the coating thickness, identifying the gas evolution as the primary reason for electrode cracking. Some secondary cracks and pinhole-type defects remained after addressing the aluminum current collector corrosion, which are thought to be caused by an inferior binding network formed by carbon black and binder in aqueous-processed cathodes compared to those processed with NMP. The thick aqueous processed cathodes are not able to sufficiently withstand the drying stresses without crack formation. We demonstrate reduction of these secondary defects by either improving the binding network or by reducing the drying stress. The former was achieved by replacing carbon black with vapor grown graphite tubes (VGGTs) that caused a more efficient utilization of the emulsion binder. Here, the latter was achieved by adding a small amount of IPA as a co-solvent that has been shown to reduce capillary stresses.

25 ENERGY STORAGE↗
DOE OSTI2014

Structural changes and thermal stability of charged LiNi x Mn y Co z O 2 cathode materials studied by combined in situ time-resolved XRD and mass spectroscopy

Thermal stability of charged LiNi x Mn y Co z O 2 (NMC, with x + y + z = 1, x:y:z = 4:3:3 (NMC433), 5:3:2 (NMC532), 6:2:2 (NMC622), and 8:1:1 (NMC811)) cathode materials is systematically studied using combined in situ time- resolved X-ray diffraction and mass spectroscopy (TR-XRD/MS) techniques upon heating up to 600 °C. The TR-XRD/MS results indicate that the content of Ni, Co, and Mn significantly affects both the structural changes and the oxygen release features during heating: the more Ni and less Co and Mn, the lower the onset temperature of the phase transition (i.e., thermal decomposition) and the larger amount of oxygen release. Interestingly, the NMC532 seems to be the optimized composition to maintain a reasonably good thermal stability, comparable to the low-nickel-content materials (e.g., NMC333 and NMC433), while having a high capacity close to the high-nickel-content materials (e.g., NMC811 and NMC622). The origin of the thermal decomposition of NMC cathode materials was elucidated by the changes in the oxidation states of each transition metal (TM) cations (i.e., Ni, Co, and Mn) and their site preferences during thermal decomposition. It is revealed that Mn ions mainly occupy the 3a octahedral sites of a layered structure (R3¯m) but Co ions prefer to migrate to the 8a tetrahedral sites of a spinel structure (Fd3¯m) during the thermal decomposition. Such element-dependent cation migration plays a very important role in the thermal stability of NMC cathode materials. The reasonably good thermal stability and high capacity characteristics of the NMC532 composition is originated from the well-balanced ratio of nickel content to manganese and cobalt contents. As a result, this systematic study provides insight into the rational design of NMC-based cathode materials with a desired balance between thermal stability and high energy density.

25 ENERGY STORAGE↗
DOE OSTI2010

The Structures of the C185S and C185A Mutants of Sulfite Oxidase Reveal Rearrangement of the Active Site

Sulfite oxidase (SO) catalyzes the physiologically critical conversion of sulfite to sulfate. Enzymatic activity is dependent on the presence of the metal molybdenum complexed with a pyranopterin-dithiolene cofactor termed molybdopterin. Comparison of the amino acid sequences of SOs from a variety of sources has identified a single conserved Cys residue essential for catalytic activity. The crystal structure of chicken liver sulfite oxidase indicated that this residue, Cys185 in chicken SO, coordinates the Mo atom in the active site. To improve our understanding of the role of this residue in the catalytic mechanism of sulfite oxidase, serine and alanine variants at position 185 of recombinant chicken SO were generated. Spectroscopic and kinetic studies indicate that neither variant is capable of sulfite oxidation. The crystal structure of the C185S variant was determined to 1.9 {angstrom} resolution and to 2.4 {angstrom} resolution in the presence of sulfite, and the C185A variant to 2.8 {angstrom} resolution. The structures of the C185S and C185A variants revealed that neither the Ser or Ala side chains appeared to closely interact with the Mo atom and that a third oxo group replaced the usual cysteine sulfur ligand at the Mo center, confirming earlier extended X-ray absorption fine structure spectroscopy (EXAFS) work on the human C207S mutant. An unexpected result was that in the C185S variant, in the absence of sulfite, the active site residue Tyr322 became disordered as did the loop region flanking it. In the C185S variant crystallized in the presence of sulfite, the Tyr322 residue relocalized to the active site. The C185A variant structure also indicated the presence of a third oxygen ligand; however, Tyr322 remained in the active site. EXAFS studies of the Mo coordination environment indicate the Mo atom is in the oxidized Mo{sup VI} state in both the C185S and C185A variants of chicken SO and show the expected trioxodithiolene active site. Density functional theory calculations of the trioxo form of the cofactor reasonably reproducd the Mo=O distances of the complex; however, the calculated Mo-S distances were slightly longer than either crystallographic or EXAFS measurements. Taken together, these results indicate that the active sites of the C185S and C185A variants are essentially catalytically inactive, the crystal structures of C185S and C185A variants contain a fully oxidized, trioxo form of the cofactor, and Tyr322 can undergo a conformational change that is relevant to the reaction mechanism. Additional DFT calculations demonstrated that such methods can reasonably reproduce the geometry and bond lengths of the active site.

36 MATERIALS SCIENCE↗
DOE OSTI2011

A Survey of Aspartate Phenylalanine and Glutamate Phenylalanine Interactions in the Protein Data Bank: Searching for Anion Pairs

Protein structures are stabilized using noncovalent interactions. In addition to the traditional noncovalent interactions, newer types of interactions are thought to be present in proteins. One such interaction, an anion pair, in which the positively charged edge of an aromatic ring interacts with an anion, forming a favorable anion quadrupole interaction, has been previously proposed [Jackson, M. R., et al. (2007) J. Phys. Chem. B111, 8242 8249]. To study the role of anion interactions in stabilizing protein structure, we analyzed pairwise interactions between phenylalanine (Phe) and the anionic amino acids, aspartate (Asp) and glutamate (Glu). Particular emphasis was focused on identification of Phe Asp or Glu pairs separated by less than 7 in the high-resolution, nonredundant Protein Data Bank. Simplifying Phe to benzene and Asp or Glu to formate molecules facilitated in silico analysis of the pairs. Kitaura Morokuma energy calculations were performed on roughly 19000 benzene formate pairs and the resulting energies analyzed as a function of distance and angle. Edgewise interactions typically produced strongly stabilizing interaction energies (2 to 7.3 kcal/mol), while interactions involving the ring face resulted in weakly stabilizing to repulsive interaction energies. The strongest, most stabilizing interactions were identified as preferentially occurring in buried residues. Anion pairs are found throughout protein structures, in helices as well as strands. Numerous pairs also had nearby cation interactions as well as potential stacking. While more than 1000 structures did not contain an anion pair, the 3134 remaining structures contained approximately 2.6 anion pairs per protein, suggesting it is a reasonably common motif that could contribute to the overall structural stability of a protein.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Crystallizing Membrane Proteins in Lipidic Mesophases. A Host Lipid Screen

The default lipid for the bulk of the crystallogenesis studies performed to date using the cubic mesophase method is monoolein. There is no good reason, however, why this 18-carbon, cis-monounsaturated monoacylglycerol should be the preferred lipid for all target membrane proteins. The latter come from an array of biomembrane types with varying properties that include hydrophobic thickness, intrinsic curvature, lateral pressure profile, lipid and protein makeup, and compositional asymmetry. Thus, it seems reasonable that screening for crystallizability based on the identity of the lipid creating the hosting mesophase would be worthwhile. For this, monoacylglycerols with differing acyl chain characteristics, such as length and olefinic bond position, must be available. A lipid synthesis and purification program is in place in the author's laboratory to serve this need. In the current study with the outer membrane sugar transporter, OprB, we demonstrate the utility of host lipid screening as a means for generating diffraction-quality crystals. Host lipid screening is likely to prove a generally useful strategy for mesophase-based crystallization of membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗