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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

AbacusSummit Cleaned Halo Catalogs

This is a data release from the AbacusSummit suite of cosmological N-body simulations. It contains dark matter halo catalogs and particle samples from those halos. The halo catalogs have been augmented (cleaned) using halo merger tree information. Descriptions of AbacusSummit, the cleaned halo catalogs, and instructions for manipulating these catalogs can be found at the following URL: abacussummit.readthedocs.io/ The halo catalog cleaning is structured as a set of auxiliary files that are ingested by the reader code at runtime. But this release contains both the original catalogs and the auxiliary files, thus forming a self-contained dataset. The files in this release are aggregated by redshift. We define sets of simulations (like all c000 sims or all hugebase sims), and then store one redshift from all simulations per tarball. This is designed to support the use-case where a user wants to analyze multiple simulations at a certain redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Symmetry-specific orientational order parameters for complex structures

A comprehensive framework of characterizing complex self-assembled structures with a set of orientational order parameters is presented. It is especially relevant in the context of using anisotropic building blocks with various symmetries. Two classes of tensor order parameters are associated with polyhedral nematic and bond orientational order. For the latter, a variation of classical bond order parameters (BOPs) is introduced, which takes advantage of the symmetry of constituent particles and/or expected crystalline phases. These symmetrized BOPs can be averaged over an entire system or assigned locally to an individual bond. By combining that with the bond percolation procedure, one is able to identify coherent domains within a self-assembled structure. As a demonstration of the proposed framework, we apply it to a simulated hybrid system that combines isotropic and patchy particles with octahedral symmetry. In conclusion, not only does the methodology allow one to identify individual crystalline domains but also it detects coherent clusters of a peculiar compact amorphous structure that is not space-filling and lacks any long-range order.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Tunable Nanostructures from Inverse Surfactants

Hierarchical materials in the natural world are often made through the self-assembly of amphiphilic molecules. Achieving similar structural complexity in synthetic materials requires understanding how various molecular parameters affect assembly behavior. In recent years, inverse surfactants─molecules with hydrophobic head groups and hydrophilic macromolecular tails─have been shown to self-assemble into supramolecular assemblies in aqueous solutions that show promise for a number of applications, including drug delivery. Here, we build an understanding of the morphological phase diagram of inverse surfactants using insights from scattering experiments, computer simulations, and statistical mechanics. The scattering and simulation results reveal that changing the headgroup size is an important molecular knob in controlling morphological transitions. The molecular size ratio of the hydrophobic group to the hydrophilic group emerges as a crucial dimensionless quantity in our theory and plays a determining role in setting the micelle structure and the transition from mesoscale to macroscale aggregates. Our minimal theory is able to qualitatively explain the key features of the morphological phase diagram, including the prevalence of fiber-like structures in comparison to spherical and planar micelles. Together, these findings provide a more complete picture of the molecular dependencies of assemblies of inverse surfactants, which we hope may aid in the de novo design of supramolecular structures.

Christakopoulos, Panagiotis [ORNL] (ORCID:00090004↗
DOE OSTI2022

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Subduction, Underplating, and Return Flow Recorded in the Cycladic Blueschist Unit Exposed on Syros, Greece

Exhumed high-pressure/low-temperature (HP/LT) metamorphic rocks provide insights into deep (~20–70 km) subduction interface dynamics. On Syros Island (Cyclades, Greece), the Cycladic Blueschist Unit preserves blueschist-to-eclogite facies oceanic- and continental-affinity rocks that record the structural and thermal evolution linked to Eocene subduction. Despite decades of research, the metamorphic and deformation history (P-T-D) and timing of subduction and exhumation are matters of ongoing discussion. We suggest that Syros comprises three coherent tectonic slices and that each slice underwent subduction, underplating, and syn-subduction return flow along similar P-T trajectories, but at progressively younger times. Subduction and exhumation are distinguished by lineations and ductile fold axis orientations, and are kinematically consistent with previous studies that document top-to-the-S-SW shear (prograde-to-peak subduction), top-to-the-NE shear (blueschist facies exhumation), and then E-W coaxial stretching (greenschist facies exhumation). Amphibole zonations record cooling during decompression, indicating return flow above a cold slab. Multi-mineral Rb-Sr isochrons and compiled metamorphic geochronology show that the three slices record distinct stages of peak subduction (53–52, ~50, and 45 Ma) that young with structural depth. Retrograde blueschist and greenschist facies fabrics span ~50–40 and ~43–20 Ma, respectively, and also young with structural depth. Synthesized data sets support a revised tectonic framework for Syros, involving subduction of structurally distinct coherent slices and simultaneous return flow of previously accreted tectonic slices in the subduction channel shear zone. Distributed, ductile, dominantly coaxial return flow in an Eocene-Oligocene subduction channel proceeded at rates of ~1.5–5 mm/yr and accommodated ~80% of the total exhumation of this HP/LT complex.

58 GEOSCIENCES↗
DOE OSTI2023

Neutral gas pressure dependence of ion–ion mutual neutralization rate constants using Landau–Zener theory coupled with trajectory simulations

In this computational study, we describe a self-consistent trajectory simulation approach to capture the effect of neutral gas pressure on ion–ion mutual neutralization (MN) reactions. The electron transfer probability estimated using Landau–Zener (LZ) transition state theory is incorporated into classical trajectory simulations to elicit predictions of MN cross sections in vacuum and rate constants at finite neutral gas pressures. Electronic structure calculations with multireference configuration interaction and large correlation consistent basis sets are used to derive inputs to the LZ theory. The key advance of our trajectory simulation approach is the inclusion of the effect of ion-neutral interactions on MN using a Langevin representation of the effect of background gas on ion transport. For H + – H – and Li + – H(D) – , our approach quantitatively agrees with measured speed-dependent cross sections for up to ~10 5 m/s. For the ion pair Ne + – Cl – , our predictions of the MN rate constant at ~1 Torr are a factor of ~2 to 3 higher than the experimentally measured value. Similarly, for Xe + – F – in the pressure range of ~20 000–80 000 Pa, our predictions of the MN rate constant are ~20% lower but are in excellent qualitative agreement with experimental data. Here, the paradigm of using trajectory simulations to self-consistently capture the effect of gas pressure on MN reactions advanced here provides avenues for the inclusion of additional nonclassical effects in future work.

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

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗
DOE OSTI2024

The role of ion-scale micro-turbulence in pedestal width of the DIII-D wide-pedestal QH mode

The low-edge rotation, intrinsically ELM-free, and improved confinement wide-pedestal quiescent H-mode (QH-mode), discovered in DIII-D tokamak, has pedestal widths exceeding the EPED-kinetic-ballooning mode (KBM) model scaling typically by at least 25%. Ion-scale ($k_yp_s$ < 1) microturbulence and its role in setting the pedestal structure is investigated using the radially local δ$f$ gyrokinetic code CGYRO. The electromagnetic trapped electron mode (TEM) is unstable at the pedestal top, while plasma beta (β$_e$) is ∼60% below the KBM onset threshold and the electron temperature gradient mode is found to be unstable in the peak gradient region. Nonlinear simulation reveals that the ion-scale turbulence could produce electron energy flux consistent with the flux inferred from power balance at the pedestal top, with a reasonable variation of the local shearing rate; and the local neoclassical transport from NEO is dominant over the simulated turbulent transport in the ion energy flux channel. The simulated ion-scale turbulence produces much lower electron energy flux than inferred from experiment in the pedestal peak gradient region. A correction to the EPED-KBM pedestal width scaling is obtained based on the two-dimensional scan of pedestal top plasma beta (β$_e$) and normalized electron density and temperature scale lengths,${a}$/${L_n}_e$, ${a}$/${L_T}_n$using CGYRO linear simulations. Mode transitions among TEM, micro-tearing mode, ion-temperature gradient mode and KBM, are observed in the 2D scan at the pedestal top. A fixed normalized growth rate for these drift-type modes is taken to determine the pedestal width scaling, which shows good consistency with the QH experimental database on pedestal heights and widths. The onset of KBM instabilities and the local E × B shear suppression criterion set the lower and upper limit for the pedestal width of standard QH-mode, wide-pedestal QH-mode and type-I ELMy H mode. A potentially higher and wider pedestal is expected from the new scaling of pedestal width. This work presents an improved understanding of the ion-scale micro-turbulence of wide-pedestal QH-mode and sheds light on a promising scenario for future reactors, including ITER and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Position Papers for the ASCR Workshop on Reimagining Codesign

On behalf of the Advanced Scientific Computing Research (ASCR) program in the US Department of Energy (DOE) Office of Science, we are organizing a Workshop on Reimagining Codesign (ReCoDe). Codesign is the process of jointly designing interoperating components of a computing system—in particular: applications, algorithms, system software, programming models, and the hardware on which they run. The goal is to maximize the overall performance, efficiency, and other desirable qualities of the system as a whole. Codesign is a standard methodology in the embedded-systems community, where space, power, and cost constraints are commonly pitted against execution speed for a tightly constrained feature set. Over the last decade, the DOE has invested in codesign efforts to foster the development of exascale computing systems for broad classes of scientific and engineering applications. The ReCoDe workshop hopes to explore how scientific applications of interest to the DOE can be accelerated through close interactions with hardware designers and software-stack developers, in which all components adapt to each other’s requirements and constraints. We want to answer the question of what are the key tools and methodologies for accomplishing codesign in today’s computing landscape, and what will be the highest impact targets for meeting DOE’s emerging mission requirements. This workshop aims to bring together DOE, industry, and academia to identify opportunities to build on past codesign successes and identify new areas that are either emerging or that may need reimagining for the future. We want to continue to find opportunities that can be pursued as a joint effort and continue to break down the traditional customer/vendor dichotomy with true partnerships. From this work, DOE will benefit from increased application performance relative to what stock hardware or existing general-purpose roadmaps can provide, and vendors will benefit from expanding their hardware’s capabilities to address needs they might have not otherwise anticipated and thereby create more widespread interest in their products. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees—from DOE, industry, and academia—will produce a report for ASCR that summarizes the findings made during the workshop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Predicting Mössbauer Parameters of Nonheme Diiron Complexes with Density Functional Theory

Mössbauer spectroscopy provides significant insights into the electronic structure and environment of the metal centers. In this work, we investigate the electronic structures of a set of nonheme diiron complexes by evaluating two key parameters pertaining to Mössbauer spectroscopy, namely, the isomer shift (δ) and quadrupole splitting (|ΔE Q |), using different levels of density functional theory (DFT). The diiron systems investigated here span diverse oxidation states, bridging motifs, and spin coupling patterns, which present a challenging case for theoretical predictions. We demonstrate that the combination of B97-D3/def2-TZVP is an efficient approach in modeling both the δ and |ΔEQ| values with high accuracy for the representative nonheme diiron complexes. We also show that δ is accurately predicted irrespective of the choice of approximate density functional while the |ΔE Q | is sensitive to the level of theory employed. Further investigation shows that the present methodology assessed using synthetic nonheme diiron complexes could be extended to nonheme diiron enzyme active sites, featuring both ferromagnetic and antiferromagnetic coupling between the iron centers.

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

The seventh blind test of crystal structure prediction: structure generation methods

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures.

Chemistry↗
DOE OSTI2021

Capturing the legacy of the U.S.-China EcoPartnerships program

Under the Ten Year Framework for Cooperation on Energy and Environment between the Governments of the United States and China, the two countries implemented a highly successful U.S.-China EcoPartnerships program . The program helped to grow 45 U.S.-China subnational partnerships and accelerate breakthroughs in technology and policy to achieve shared goals in clean air, clean water, and waste reduction. Following the culmination of the U.S.-China EcoPartnerships program in January 2021, this article captures the legacy of this impressive program by providing insights into its unique structure; the diverse set of projects that comprised U.S.-China EcoPartnerships; its commercial and environmental impacts; and the lessons that can be applied to future bilateral and multilateral subnational environmental programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Inferring precocial Chinook Salmon production through single‐parentage assignments

Abstract Objective Parentage analysis is a routine methodology in fisheries research, but study systems exist where it is impractical to sample both parents. The ability to reliably assign offspring to a single parent is beneficial in these situations. We applied single‐parentage assignments to a naturally spawning population of Chinook Salmon Oncorhynchus tshawytscha to quantify production of anadromous returns by unsampled precocial males. Methods We used an approach that focused on two important aspects of parentage analyses: (1) addressing the presence of family structure within the set of sampled parents and (2) controlling for false‐positive and false‐negative assignments. Result Results indicated that 30% of reproductively successful males were precocial males, which produced 20% of the returning anadromous offspring. Conclusion This study provides a framework for applying single‐parent assignments in a salmonid study system while explicitly addressing sources of assignment errors.

Steele, Craig A.↗
DOE OSTI2022

Detailing cloud property feedbacks with a regime-based decomposition

Here, we report diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

58 GEOSCIENCES↗
DOE OSTI2020

The Energy Modeling Forum (EMF)-30 Study on Short-Lived Climate Forcers: Introduction and Overview

The Energy Modeling Forum (EMF)-30 inter-comparison study on short-lived climate forcers (SLCFs) focuses on black carbon (BC) and methane, two of the most important warming SLCFs. The potential impact on climate change of methane and BC-focused emission reductions in the transport and residential sectors were quantified using nine integrated assessment models and a simple climate model. These SLCF reductions reduced global temperatures by 0.18–0.26 °C in 2050 across the models for central climate parameters, with methane being the dominant contributor. The incremental impact of SLCF-focused reductions is much smaller when combined with a broader climate policy. Individual modeling groups examined the health benefits of air pollutant reductions, climate policy co-benefits, and quantified market impacts from air pollutant damages. Model structure and set-up impact on results are discussed along with areas for future work.

Smith, Steven J.↗
DOE OSTI2022

Strain-Induced asymmetry and on-site dynamics of silicon defects in graphene

In the last decade, the atomically-focused electron beams utilized in scanning transmission electron microscopes (STEMs) have been shown to induce a broad set of local structural transformations in materials, opening pathways for directing material synthesis and modification atom-by-atom. The mechanisms underlying these transformations remain largely unknown, due to the intractability of modeling the myriad of reaction pathways that can be accessed through high-energy electron scattering. The information on materials’ structure and dynamics that can be extracted from STEM images is similarly left underexplored. Here, we report the observation of anomalous on-site dynamics of individual silicon impurity atoms in graphene during STEM imaging. Density functional theory-based structural optimizations of anisotropically-strained molecular nanographenes reveal two distinct (but nearly degenerate) stable structures for four-fold coordinated silicon impurities, where interconversion between the two structures manifests slight changes of the silicon position within the lattice site. Implications for defect-based strain engineering in graphene are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Apolipoprotein A-I modulates HDL particle size in the absence of apolipoprotein A-II

Human high-density lipoproteins (HDLs) are a complex mixture of structurally related nanoparticles that perform distinct physiological functions. We previously showed that human HDL containing apolipoprotein A-I (APOA1) but not apolipoprotein A-II (APOA2), designated LpA-I, is composed primarily of two discretely sized populations. Here, we isolated these particles directly from human plasma by antibody affinity chromatography, separated them by high-resolution size-exclusion chromatography and performed a deep molecular characterization of each species. The large and small LpA-I populations were spherical with mean diameters of 109 Å and 91 Å, respectively. Unexpectedly, isotope dilution MS/MS with [ 15 N]-APOA1 in concert with quantitation of particle concentration by calibrated ion mobility analysis demonstrated that the large particles contained fewer APOA1 molecules than the small particles; the stoichiometries were 3.0 and 3.7 molecules of APOA1 per particle, respectively. MS/MS experiments showed that the protein cargo of large LpA-I particles was more diverse. Human HDL and isolated particles containing both APOA1 and APOA2 exhibit a much wider range and variation of particle sizes than LpA-I, indicating that APOA2 is likely the major contributor to HDL size heterogeneity. We propose a ratchet model based on the trefoil structure of APOA1 whereby the helical cage maintaining particle structure has two “settings”—large and small—that accounts for these findings. This understanding of the determinants of HDL particle size and protein cargo distribution serves as a basis for determining the roles of HDL subpopulations in metabolism and disease states.

59 BASIC BIOLOGICAL SCIENCES↗