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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

High-throughput binding affinity calculations at extreme scales

Background Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment. In many cases, resistance can be linked to genetic changes in target proteins, either pre-existing or evolutionarily selected during treatment. Key to overcoming this challenge is an understanding of the molecular determinants of drug binding. Using multi-stage pipelines of molecular simulations we can gain insights into the binding free energy and the residence time of a ligand, which can inform both stratified and personal treatment regimes and drug development. To support the scalable, adaptive and automated calculation of the binding free energy on high-performance computing resources, we introduce the High-throughput Binding Affinity Calculator (HTBAC). HTBAC uses a building block approach in order to attain both workflow flexibility and performance. Results We demonstrate close to perfect weak scaling to hundreds of concurrent multi-stage binding affinity calculation pipelines. This permits a rapid time-to-solution that is essentially invariant of the calculation protocol, size of candidate ligands and number of ensemble simulations. Conclusions As such, HTBAC advances the state of the art of binding affinity calculations and protocols. HTBAC provides the platform to enable scientists to study a wide range of cancer drugs and candidate ligands in order to support personalized clinical decision making based on genome sequencing and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Mechanism of fusion of pathogenic enveloped viruses with the endosomal membrane

Dengue virus is a devastating human pathogen responsible for millions of infections each year. No antiviral therapies for Dengue currently exist, making effective treatment of the virus challenging. Dengue is taken into the cell through endocytosis. Low-pH mediated structural rearrangements of the envelope protein E leads to the formation of fusogenic E trimers that facilitate membrane fusion with late endosomes. The fusion mechanism is not fully understood, but is a key target for inhibiting the viral infection pathway. An important aspect of fusion is the dependence on endosomal membrane composition, and in particular, the requirement of anionic lipids. This study aims to characterize the biophysical reasons for this dependence. The work includes experimental studies and molecular simulations of the interactions of E with lipid membranes. These approaches revealed the structure of E bound to lipid membranes including the depth of its insertion into the membrane and the average angle with respect to the membrane, the fundamental interactions involved, the dependence of adsorption and anchoring energy on membrane composition, the membrane curvature induced upon insertion, and the correlation of the above with fusion efficiency of virus like particles (VLPs) with liposomes. As a part of this work we developed a new biophysical technique to measure the energy for pulling E out of a membrane, and distinguished anchoring (pull-out) and binding energies for this nonequilibrium system. We also developed a modeling approach combining molecular and continuum approaches to provide the first theoretical estimate of the binding energy. Taken together, this work lays the foundation for developing a systematic fundamental understanding of fusion in enveloped viruses that has been elusive to date.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Potential Foldamers Based on an ortho- Terphenyl Amino Acid

We describe the synthesis and characterization of a new class of oligomers built from a terphenyl-based amino acid. Here, these oligomeric amides are of interest because the adoption of specific conformations could potentially be driven by the coordinated formation of inter-residue hydrogen bonds and aromatic interactions. Although high-resolution structural data have proven inaccessible, circular dichroism and nuclear magnetic resonance studies suggest that the new oligomers fold concomitantly with discrete self-association in chloroform. Molecular simulations find no sign of folding as a monomer, and in fact suggest that hydrogen bond patterning is anti-cooperative, inhibiting longer helices.

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

Importance of Ion Packing on the Dynamics of Ionic Liquids during Micropore Charging

In molecular simulations of the diffusion of EMIM+ and TESI- ions in slit-shaped micropores under conditions similar to those during charging show that in pores that accommodate only a single layer of ions, ions diffuse increasingly faster as the pore becomes charged (with diffusion coefficients even reaching similar to 5 x 10 -9 m 2 /s), unless the pore becomes very highly charged. In pores wide enough to fit more than one layer of ions, ion diffusion is slower than in the bulk and changes modestly as the pore becomes charged. Moreover, analysis of these results revealed that the fast (or slow) diffusion of ions inside a micropore during charging is correlated most strongly with the dense (or loose) ion packing inside the pore. Finally, the molecular details of the ions and the precise width of the pores modify these trends weakly, except when the pore is so narrow that the ion conformation relaxation is strongly constrained by the pore walls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Electrochemical Detection of Single Molecules in Nanogap Electrode Fluidic Devices

The purpose of this project was to gain a fundamental understanding of molecular diffusion in nanogap electrodes and the diffusive behavior of single molecules undergoing electron transfer. Electrochemical methods for single molecule detection have remained elusive due to the vanishingly small currents involved in single molecule electron transfer. Electrochemical detection of single molecules undergoing redox cycling would enable detection of single enzymes, proteins, and DNA strands resulting in new and improved ultrasensitive sensing devices impacting Detection At The Limits research challenge (DATL), supporting needs in DHS and DoD. We attempted to integrate orthogonal validation techniques, Total Internal Reflection Fluorescence Microscopy (TIRF), and molecular simulation to clarify (1) the mechanism leading to current build up due to redox cycling and (2) diffusion and adsorption of single molecules undergoing redox reactions. While creation of nanogap electrodes with transparent windows was ultimately successful in this project (along with TIRF demonstration of single molecule imaging), time and methods constraints did not allow final electrochemical measurements to be coupled for simultaneous interrogation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Multifunctional Catalysts for the Tandem Reactions of Oxygenates

Industrially-relevant catalytic reactions rarely consist of a simple sequence of elementary steps. Moreover, kinetic coupling of multiple reactions on a catalyst surface is highly desired for process intensification and improved energy efficiency for large scale chemical transformations. The shifting landscape of hydrocarbon chemical feedstocks in the US also motivates research on the selective conversion of more complex molecules. One desirable type of catalytic reaction is the reduction of carboxylic acids that are produced from biomass feedstocks to their corresponding alcohols. The proposed research explores the fundamental importance of hydrogen spillover on a multifunctional catalyst for carboxylic acid reduction with H 2 composed of metal particles coupled to metal oxide particles. Recent work has demonstrated the excellent performance of supported tungsten oxide clusters for carboxylic acid reduction, but only after they are promoted with a late transition metal such as palladium. Elucidating the active state of the catalyst and the associated reaction mechanism for acid reduction on that active state are the overall goals of the proposed project and successful completion will enable future design of efficient multifunctional catalysts. The critically important role of the metal promoter is hypothesized to be its ability to dissociate H2 and spillover atomic H to the support. Although hydrogen spillover is a well-recognized phenomenon in catalysis, its role in both catalyst activation and catalytic turnover are still unresolved. The study combined materials synthesis, characterization, reactivity testing, and molecular simulations, to explore the effect of hydrogen chemical potential on the formation of the active catalytic sites and on the steady state catalytic reduction of carboxylic acid. Varying the hydrogen chemical potential through modification of the gas conditions, support composition, and metal loading to modulated the structure and catalytic performance of the reducible metal oxide. Dual function catalysts containing supported Pd and WO x species co-located on a non-reducible carrier (silica) and a reducible carrier (titania) were synthesized and characterized by electron microscopy, temperature-programmed reduction, and chemisorption. Spectroscopic methods such as X-ray absorption and UV-vis were also used to evaluate the catalysts, which were used in the reduction of propionic acid to aldehyde and alcohol. Quantum chemical calculations, including ab initio phase diagrams provided molecular insights into the H spillover phenomenon.

09 BIOMASS FUELS↗
DOE OSTI2021

Understanding Solid Electrolyte Interphase Nucleation and Growth on Lithium Metal Surfaces

Experiments and theory are needed to decode the exact structure and distribution of components of a passivation layer formed at the anode surface of Li metal batteries, known as the Solid Electrolyte Interphase (SEI). Due to the inherent dynamic behavior as well as the lithium reactivity, the SEI structure and its growth mechanisms are still unclear. This study uses molecular simulation and computational chemistry tools to investigate the initial nucleation and growth dynamics of LiOH and Li2O that provide us with thermodynamics and structural information about the nucleating clusters of each species. Following the most favorable pathways for the addition of each of the components to a given nascent SEI cluster reveals their preferential nucleation mechanisms and illustrates different degrees of crystallinity and electron density distribution that are useful to understand ionic transport through SEI blocks.

25 ENERGY STORAGE↗
DOE OSTI2014

Comparing simulated emission from molecular clouds using experimental design

We propose a new approach to comparing simulated observations that enables us to determine the significance of the underlying physical effects. We utilize the methodology of experimental design, a subfield of statistical analysis, to establish a framework for comparing simulated position-position-velocity data cubes to each other. We propose three similarity metrics based on methods described in the literature: principal component analysis, the spectral correlation function, and the Cramer multi-variate two-sample similarity statistic. Using these metrics, we intercompare a suite of mock observational data of molecular clouds generated from magnetohydrodynamic simulations with varying physical conditions. Using this framework, we show that all three metrics are sensitive to changing Mach number and temperature in the simulation sets, but cannot detect changes in magnetic field strength and initial velocity spectrum. We highlight the shortcomings of one-factor-at-a-time designs commonly used in astrophysics and propose fractional factorial designs as a means to rigorously examine the effects of changing physical properties while minimizing the investment of computational resources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Different Behaviors of a Substrate in P450 Decarboxylase and Hydroxylase Reveal Reactivity-Enabling Actors

Biological routes to the production of fuels from renewable feedstocks hold significant promise in our efforts towards a sustainable future. The fatty acid decarboxylase enzyme (OleT JE ) is a cytochrome P450 enzyme that converts long and medium chain fatty acids to terminal alkenes and shares significant similarities in terms of structure, substrate scope and mechanism with the hydroxylase cytochrome P450 (P450 BSβ ). Recent reports have demonstrated that catalytic pathways in these enzymes bifurcate when the heme is in its iron-hydroxo (compound II) state. In spite of significant similarities, the fundamental underpinnings of their different characteristic wild-type reactivities remain ambiguous. In this work, we develop point charges, modified parameters and report molecular simulations of this crucial intermediate step. Water occupancies and substrate mobility at the active site are observed to be vital differentiating aspects between the two enzymes in the compound II state and corroborate recent experimental hypotheses. Apart from increased substrate mobility in the hydroxylase, which could have implications for enabling the rebound mechanism for hydroxylation, OleT JE is characterized by much stronger binding of the substrate carboxylate group to the active site arginine, implicating it as an important enabling actor for decarboxylation.

09 BIOMASS FUELS↗
DOE OSTI2019

Extracting collective motions underlying nucleosome dynamics via nonlinear manifold learning

The identification of effective collective variables remains a challenge in molecular simulations of complex systems. Here, we use a nonlinear manifold learning technique known as the diffusion map to extract key dynamical motions from a complex biomolecular system known as the nucleosome: a DNA-protein complex consisting of a DNA segment wrapped around a disc-shaped group of eight histone proteins. We show that without any a priori information, diffusion maps can identify and extract meaningful collective variables that characterize the motion of the nucleosome complex. We find excellent agreement between the collective variables identified by the diffusion map and those obtained manually using a free energy-based analysis. Notably, diffusion maps are shown to also identify subtle features of nucleosome dynamics that did not appear in those manually specified collective variables. For example, diffusion maps identify the importance of looped conformations in which DNA bulges away from the histone complex that are important for the motion of DNA around the nucleosome. As a result, this work demonstrates that diffusion maps can be a promising tool for analyzing very large molecular systems and for identifying their characteristic slow modes.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The Gearbox of the Bacterial Flagellar Motor Switch

Switching of flagellar motor rotation sense dictates bacterial chemotaxis. Multi-subunit FliM-FliG rotor rings couple signal protein binding in FliM with reversal of a distant FliG C-terminal (FliGC) helix involved in stator contacts. Subunit dynamics were examined in conformer ensembles generated by molecular simulations from the X-ray structures. Principal component analysis extracted collective motions. Interfacial loop immobilization by complex formation coupled elastic fluctuations of the FliM middle (FliMM) and FliG middle (FliGM) domains. Coevolved mutations captured interfacial dynamics as well as contacts. FliGM rotation was amplified via two central hinges to the FliGC helix. Intrinsic flexibility, reported by the FliGMC ensembles, reconciled conformers with opposite FliGC helix orientations. FliG domain stacking deformed the inter-domain linker and reduced flexibility; but conformational changes were not triggered by engineered linker deletions that cause a rotation-locked phenotype. These facts suggest that binary rotation states arise from conformational selection by stacking interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Production of β-ketoadipic acid from glucose in Pseudomonas putida KT2440 for use in performance-advantaged nylons

Biomass-derived chemicals can offer unique chemical functionality relative to petroleum-derived building blocks. To this end, here we report that β-ketoadipic acid (βKA), a C6 diacid with a β-ketone group, can be used as a performance-advantaged replacement for adipic acid in a nylon-6,6 analog. Building on our previous efforts to produce shikimate-derived products from carbohydrates, Pseudomonas putida KT2440 is engineered to produce βKA from glucose, achieving a 26 g/L titer. Following purification, βKA imparts an increase of 69 degrees C above the nylon-6,6 glass transition temperature and 20% reduced water permeability, equivalent to nylon-6,10. Molecular simulations predict that the enhanced thermal properties result from rigidity introduced by the β-ketone. Process analysis predicts that βKA can be produced for US$1.94/kg from sugars, requiring 63% less energy and emitting 43% less greenhouse gases than fossil-based adipic acid. Overall, this study illustrates the potential for βKA to serve as a useful building block for bio-based polymers.

09 BIOMASS FUELS↗
DOE OSTI2022

Homogeneous ice nucleation in an ab initio machine-learning model of water

Molecular simulations have provided valuable insight into the microscopic mechanisms underlying homogeneous ice nucleation. While empirical models have been used extensively to study this phenomenon, simulations based on first-principles calculations have so far proven prohibitively expensive. Here, we circumvent this difficulty by using an efficient machine-learning model trained on density-functional theory energies and forces. We compute nucleation rates at atmospheric pressure, over a broad range of supercoolings, using the seeding technique and systems of up to hundreds of thousands of atoms simulated with ab initio accuracy. The key quantity provided by the seeding technique is the size of the critical cluster (i.e., a size such that the cluster has equal probabilities of growing or melting at the given supersaturation), which is used together with the equations of classical nucleation theory to compute nucleation rates. We find that nucleation rates for our model at moderate supercoolings are in good agreement with experimental measurements within the error of our calculation. We also study the impact of properties such as the thermodynamic driving force, interfacial free energy, and stacking disorder on the calculated rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Molecular dynamics and simulations study on the vibrational and electronic solvatochromism of benzophenone

Solvent plays a key role in diverse physico-chemical and biological processes. Therefore, understanding solute-solvent interactions at the molecular level of detail is of utmost importance. A comprehensive solvatochromic analysis of benzophenone (Bzp) was carried out in various solvents using Raman and electronic spectroscopy, in conjunction with Density Functional Theory (DFT) calculations of supramolecular solute-solvent clusters generated using classical Molecular Dynamics Simulations (c-MDSs). The >C=O stretching frequency undergoes a bathochromic shift with solvent polarity. Interestingly, in protic solvents this peak appears as a doublet: c-MDS and ad hoc explicit solvent ab initio calculations suggest that the lower and higher frequency peaks are associated with the hydrogen bonded and dangling carbonyl group of Bzp, respectively. Additionally, the dangling carbonyl in methanol (MeOH) solvent is 4 cm{sup −1} blue-shifted relative to acetonitrile solvent, despite their similar dipolarity/polarizability. This suggests that the cybotactic region of the dangling carbonyl group in MeOH is very different from its bulk solvent structure. Therefore, we propose that this blue-shift of the dangling carbonyl originates in the hydrophobic solvation shell around it resulting from extended hydrogen bonding network of the protic solvents. Furthermore, the 1{sup 1}nπ{sup ∗} (band I) and 1{sup 1}ππ{sup ∗} (band II) electronic transitions show a hypsochromic and bathochromic shift, respectively. In particular, these shifts in protic solvents are due to differences in their excited state-hydrogen bonding mechanisms. Additionally, a linear relationship is obtained for band I and the >C=O stretching frequency (cm{sup −1}), which suggests that the different excitation wavelengths in band I correspond to different solvation states. Therefore, we hypothesize that the variation in excitation wavelengths in band I could arise from different solvation states leading to varying solvation dynamics. This will have implications for ultrafast processes associated with electron-transfer, charge transfer, and also the photophysical aspects of excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Quantification of the REE 3+ aqua ions and chloride species in aqueous fluids by in situ Raman spectroscopy using perturbations of the water band

Acidic NaCl-rich aqueous fluids play a crucial role in forming hydrothermal rare earth elements (REE) mineral deposits. Aqueous REE mobility is mostly controlled by the stabilities of REE 3+ and REE chloride species. Our current knowledge of REE speciation is based on solubility data, thermodynamic models and in situ spectroscopic measurements, sometimes coupled with molecular simulations. Here, in this study, we investigate Nd and Yb speciation in pH2 Cl-bearing solutions at 25 °C and 0.1 MPa with variable Cl/REE ratios using Raman Spectroscopy in solutions with 0.1 to 0.6 mol/kg NdCl 3 or YbCl 3 and 0.2 to 3.2 mol/kg NaCl. Due to the challenges in resolving the REE-Cl band, we developed a new method using the water vibrational mode and multivariate curve resolution (MCR) analysis. The Raman spectra for the vibrational band of water (2700 to 3900 cm –1 ) were collected at 25 °C and fitted by three Gaussian sub-peaks, then quantified using MCR analysis to de-convolute the water band into bulk H 2 O and the perturbations caused by of Cl – , REE 3+ , and REE chloride species. REE speciation based on the perturbations of the water band indicates that REE 3+ aqua ions dominate acidic solutions at 25 °C, but up to ~20 mol% YbCl 2+ forms at high YbCl 3 concentrations. The new method is promising for quantifying in situ speciation of the REE 3+ aqua ions and REE chloride species in aqueous fluids while providing information on the hydration of ions. This method improves our molecular level understanding of REE aqueous species stability and their role in REE mobilization during fluid-rock interaction.

58 GEOSCIENCES↗