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Results for “coordinated optimization”

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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NASA NTRS1989

Real-time neuromorphic algorithms for inverse kinematics of redundant manipulators

The paper presents an efficient neuromorphic formulation to accurately solve the inverse kinematics problem for redundant manipulators. The approach involves a dynamical learning procedure based on a novel formalism in neural network theory: the concept of 'terminal' attractors. Topographically mapped terminal attractors are used to define a neural network whose synaptic elements can rapidly encapture the inverse kinematics transformations, and, subsequently generalize to compute joint-space coordinates required to achieve arbitrary end-effector configurations. Unlike prior neuromorphic implementations, this technique can also systematically exploit redundancy to optimize kinematic criteria, e.g., torque optimization. Simulations on 3-DOF and 7-DOF redundant manipulators, are used to validate the theoretical framework and illustrate its computational efficacy.

Barhen, Jacob↗

NASA NTRS1997

Heterogeneous Combustion of Porous Graphite Particles in Microgravity

Recent theoretical investigations on graphite particle combustion have employed several levels of heterogeneous reaction models, ranging from global to elementary models, to describe the oxidation of carbon to gaseous products. Unlike the counterpart homogeneous reaction models, these heterogeneous reaction models are not well developed because of the difficulties associated with decoupling the physical characteristics of the solid (e.g. surface area taking part in combustion) from the chemical kinetic data. This is certainly true for porous graphite particle combustion, where heterogeneous and homogeneous reactions occur within the pores and play an important role in the overall oxidation process. As a result, there are considerable uncertainties of physical phenomena predicted using different heterogeneous kinetic models available in the literature. A good example, discussed later in this paper, is the predicted critical particle size below which the mass burning rate becomes exponentially small. The main goal of this study is to understand the basic mechanism controlling such rapid changes in burning rates, by developing a model where physical contributions are decoupled from chemical rate constants in a consistent manner. Another important goal of the proposed study is to develop a truly intrinsic, detailed heterogeneous reaction model for porous graphite combustion at high-temperatures, and to derive a systematically reduced heterogeneous reaction model in terms of the elementary reaction rate constants of the detailed model. The validation of chemical kinetic models describing the heterogeneous and homogeneous combustion in and around a spherically symmetric porous graphite particle can be considerably simplified by experimental measurements obtained under microgravity conditions. A vital component of this study is to conduct such supporting experiments on particle burning rate and surface temperature using NASA microgravity facilities, in close coordination with the theoretical effort. The basic understanding obtained and models developed as part of this project will be useful for optimal design of coal combustion devices. These models can also be extended to investigate the role of heterogeneous chemistry on pollutant formation pathways in combustion devices. The theoretical approach developed here, with pore diffusion effects decoupled from the chemical effects, can also be extended to understand the heterogeneous combustion of other porous fuels, for example, combustion of magnesium in a CO2 environment for propulsion in the Martian atmosphere.

Chelliah, Harsha K.↗

DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services

This paper develops a hierarchical control frame-work to aggregate and to manage behind-the-meter distributed energy resources (DERs), which will be ubiquitous in future distribution systems. In the proposed framework, firstly, each controller in the hierarchy determines the flexibility of the DERs such that the obtained flexibility is feasible with respect to its operational purview. For example, the operational purview of a home energy management system may only consider consumer comfort preferences, while that for an aggregator or a grid controller may consider network voltage management as well. Based on the feasible flexibility, optimal setpoints for the DERs is then determined by the hierarchical controllers to help the distribution power network in voltage regulation, coordination issues with existing transmission-level conventional generators, etc. Therefore, the proposed strategy, which is based on model-predictive control, can be effectively utilized by the distribution network to coordinate several DERs to provide grid regulation services. Numerical simulations performed on the IEEE 37-bus test system demonstrate the efficacy of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2002

Science Planning for Multi-Spacecraft Coordinated Observations

Fulfilling the promise of an era of great observatories, NASA now has more than three space-based astronomical telescopes operating in different wavebands. This situation provides astronomers with a unique opportunity to simultaneously observe with multiple observatories. Yet scheduling multiple observatories simultaneously is highly inefficient when compared to single observatory observations. Thus, programs using multiple observatories are limited not due to scientific restrictions, but due to operational inefficiencies. Each year, a number of proposals are accepted by a space-based observatory for conduction of astronomical observations and gathering of science data for the study of galactic events. Since each space-based observatory uses a set of instruments designed to operate in specific energy regions, most such studies are conducted by submitting observation proposals to multiple observatories, with requests to coordinate among themselves. To assure that the proposed observations can be scheduled, each observatory's staff has to check that the observations are valid and meet all the constraints for their own observatory; in addition, they have to verify that the observations satisfy the constraints of the other observatories. Thus, coordinated observations require painstaking manual collaboration among the observatory staff at each observatory. In order to exploit new paradigms for observatory operation, the Goddard Space Flight Center's Advanced Architectures and Automation Branch has developed a prototype tool called the Visual Observation Layout Tool (VOLT). The main objective of VOLT is to provide a visual tool to automate the science planning of coordinated observations for multiple spacecraft, as well as to increase the scheduling probability of observations. However, VOLT is also useful for single observatory planning to optimize observatory control. Three space-based missions are interested in using VOLT (the Hubble Space Telescope, the Chandra X-Ray Observatory, and the Far Ultraviolet Spectroscopic Explorer). The VOLT team members have collaborated with these missions to gather requirements and obtain feedback on their mission planning processes. VOLT has been developed as a cross-platform Java client application for use by scientists and observatory science planning staff to visualize scheduling options and constraints. It also supports a lightweight graphical user interface for remote viewing via a Web front end. Additionally, it uniquely supports the ability to interact with multiple, diverse scheduling packages in order to determine windows of opportunity for observations and visually portray the constraints of each observation request. VOLT enables science data capture scenarios which are currently either impossible, or which require extensive time and manpower to coordinate amongst multiple observatories. it supports early detection of planning conflicts by generating coordinated solutions based on observatory schedulability and constraints. The project development approach has included frequent prototype demonstrations to our interested missions to obtain feedback after each release of the software. We will present an overview of our lessons learned in infusing the VOLT tool into the operations of the missions we have collaborated with and a brief demonstration of the software.

Maks, Lori↗

DOE OSTI2024

Elucidating the Structure of the Eu‐EDTA Complex in Solution at Various Protonation States

Abstract Ethylenediaminetetraacetic acid (EDTA), which has two amine and four carboxylate protonation sites, forms stable complexes with lanthanide ions. This work analyzes the coordination structure, in atomic resolution, of the Eu 3+ ion complexed with EDTA in all its protonation states in aqueous solution. Eu‐EDTA complexes were modeled using classical molecular dynamics (MD) simulations using force field parameters optimized with ab initio molecular dynamics (AIMD) simulations. Structures from the MD simulations were used to predict extended X‐ray absorption fine structure (EXAFS) spectra and compared with EXAFS measurements of the Eu 3+ aqua ion and Eu‐EDTA complexes at pH 3 and 11. This work details how Eu‐EDTA complex coordination structures change with increasing protonation of the EDTA ligand in the complex, from the tightly bound unprotonated complex to the unbinding of the fully protonated EDTA ligand from the Eu 3+ ion as both become solvated by water. Agreement between predicted and measured EXAFS spectra supports the findings from simulation.

Chemistry↗

DOE OSTI2014

Shedding Light on the Photochemistry of Coinage-Metal Phosphorescent Materials: A Time-Resolved Laue Diffraction Study of an Ag I -Cu I Tetranuclear Complex

The triplet excited state of a new crystalline form of a tetranuclear coordination d 10 –d 10 -type complex, Ag 2 Cu 2 L 4 (L = 2-diphenylphosphino-3-methylindole ligand), containing Ag I and Cu I metal centers has been explored using the Laue pump–probe technique with ≈80 ps time resolution. The relatively short lifetime of 1 μs is accompanied by significant photoinduced structural changes, as large as the Ag1···Cu2 distance shortening by 0.59(3) Å. The results show a pronounced strengthening of the argentophilic interactions and formation of new Ag···Cu bonds on excitation. Theoretical calculations indicate that the structural changes are due to a ligand-to-metal charge transfer (LMCT) strengthening the Ag···Ag interaction, mainly occurring from the methylindole ligands to the silver metal centers. QM/MM optimizations of the ground and excited states of the complex support the experimental results. Comparison with isolated molecule optimizations demonstrates the restricting effect of the crystalline matrix on photoinduced distortions. The work represents the first time-resolved Laue diffraction study of a heteronuclear coordination complex and provides new information on the nature of photoresponse of coinage metal complexes, which have been the subject of extensive studies.

Jarzembska, Katarzyna N.↗

DOE OSTI2015

QTAIM studies of [Li(DMSO){sub n}]{sup +} and [Al(DMSO){sub n}]{sup 3+}

Geometry optimization of [Li(DMSO){sub n}]{sup +} and [Al(DMSO){sub n}]{sup 3+} complexes with n = 1 - 6 in DMSO (dimethyl sulfoxide, (CH{sub 3}){sub 2}SO) solutions is performed using DFT treatment with B3LYP hybrid functional and cc-pVDZ basis sets. Solvent effects are approximated within Integral Equation Formalism Polarisable Continuum Model. Electron structure of individual model systems is investigated in terms of Quantum Theory of Atoms-in-Molecule topological analysis of electron density. Metal-DMSO bonding through oxygen atom is preferred. The most probable coordination numbers n = 4 for Li{sup +} and n = 6 for Al{sup 3+} complexes with DMSO are concluded.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2012

Optimal Routing and Control of Multiple Agents Moving in a Transportation Network and Subject to an Arrival Schedule and Separation Constraints

We address the problem of navigating a set of moving agents, e.g. automated guided vehicles, through a transportation network so as to bring each agent to its destination at a specified time. Each pair of agents is required to be separated by a minimal distance, generally agent-dependent, at all times. The speed range, initial position, required destination, and required time of arrival at destination for each agent are assumed provided. The movement of each agent is governed by a controlled differential equation (state equation). The problem consists in choosing for each agent a path and a control strategy so as to meet the constraints and reach the destination at the required time. This problem arises in various fields of transportation, including Air Traffic Management and train coordination, and in robotics. The main contribution of the paper is a model that allows to recast this problem as a decoupled collection of problems in classical optimal control and is easily generalized to the case when inertia cannot be neglected. Some qualitative insight into solution behavior is obtained using the Pontryagin Maximum Principle. Sample numerical solutions are computed using a numerical optimal control solver.

Sadovsky, A. V.↗

DOE OSTI2018

Intermediate temperature fuel cells via an ion-pair coordinated polymer electrolyte

Fuel cells are attractive devices that convert chemical energy into electricity through the direct electrochemical reaction of hydrogen and oxygen. Intermediate temperature fuel cells operated at 200–300°C can simplify water and thermal managements, enable the use of non-precious or low-loading precious metal catalysts and provide insensitivity toward fuel and air impurities such as carbon monoxide. However, the performance of current intermediate temperature fuel cells is poor due to a lack of highly-conductive membrane electrolytes and optimal electrodes designed for these fuel cells. We demonstrate high-performing intermediate temperature fuel cells that use SnP 2 O 7 –polymer composite membranes and a quaternary ammonium-biphosphate ion-pair coordinated polymer electrolyte in the electrodes. The peak power density of the fuel cell under H 2 and O 2 reached 870 mW cm -2 at 240°C with minimal performance loss under exposure to 25% carbon monoxide.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2016

Achieving Reversible H2/H+ Interconversion at Room Temperature with Enzyme-Inspired Molecular Complexes: A Mechanistic Study

Inspired by the contribution of the protein scaffold to the efficiency with which enzymes function, we report the first molecular complex that is reversible for electrocatalytic H2 production/oxidation at room temperature in methanol. [Ni(PCy2NPhe2)2]2+ (CyPhe; PR2NR’2 = 1,5-diaza-3,7-diphosphacyclooctane, Cy=cyclohexyl, Phe=phenylalanine), shows reversible behavior in acidic methanol with peripheral phenylalanine groups providing key contributions to the catalytic behavior. The importance of the aromatic rings is implicated in achieving reversibility, based on the lack of reversibility of similar complexes, [Ni(PCy2NAmino Acid2)2]2+, containing arginine (CyArg) or glycine (CyGly). A complex with an added OH group on the ring, (CyTyr; Tyr=Tyrosine), also shows similar behavior. NMR studies reveal a significantly slower rate of chair-boat isomerization for the CyPhe relative to other derivatives, suggesting that the aromatic groups provide structural control by interacting with each other, an observation supported by molecular dynamics studies. NMR studies also show extremely fast proton movement, with a proton pathway from the Ni-H through the pendant amine to the –COOH group. Further, studies of acomplex without the –COOH group, [Ni(PCy2NTym2)2]2+ (CyTym; Tym=Tyramine), are not reversible and have slow proton movement from the pendant amine, demonstrating the essential nature of the –COOH group in achieving reversibility. Finally, methanol is demonstrated to play a critical contributing role. The influence of multiple factors on reversibility for this synthetic catalyst is a demonstration of the intricate interplay between the first, second, and outer coordination spheres and resembles the complexity observed in metalloenzymes.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2017

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I -- National Study

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Thanks to advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India's RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU's anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD $920 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment - from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India's 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India’s Electric Grid, Vol. 1. National Study

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Using advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India’s RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (Berkeley Lab), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU’s anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD 980 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment—from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India’s 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Improved Sensitivity Relations in State Constrained Optimal Control

Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because it is validated for a stronger set of necessary conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Conservation Voltage Reduction (CVR) via Two-Timescale Control in Unbalanced Power Distribution Systems

Voltage control devices are employed in power distribution systems to reduce the power consumption by operating the system closer to the lower acceptable voltage limits; this technique is called conservation voltage reduction (CVR). The different modes of operation for system’s legacy devices (with binary control) and new devices (e.g. smart inverters with continuous control) coupled with variable photovoltaic (PV) generation results in voltage fluctuations which makes it challenging to achieve CVR objective. This paper presents a two-timescale control of feeder’s voltage control devices to achieve CVR that includes (1)a centralized controller operating in a slower time-scale to coordinate voltage control devices across the feeder and (2) local controllers operating in a faster timescale to mitigate voltage fluctuations due to PV variability. The centralized controller utilizes a three-phase optimal power flow model to obtain the decision variables for both legacy devices and smart inverters. The local controllers operate smart inverters to minimize voltage fluctuations and restore nodal voltages to their reference values by adjusting the reactive power support. The proposed approach is validated using the IEEE-123 bus (medium-size) and R3-12.47-2 (large-size) feeders. It is demonstrated that the proposed approach is effective in achieving the CVR objective for unbalanced distribution systems.

optimal control, distributed generation, fluctuati↗

DOE OSTI2024

Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning

The deep operator network (DeepONet) has shown remarkable potential in solving partial differential equations (PDEs) by mapping between infinite-dimensional function spaces using labeled datasets. However, in scenarios lacking labeled data, the physics-informed DeepONet (PI-DeepONet) approach, which utilizes the residual loss of the governing PDE to optimize the network parameters, faces significant computational challenges, particularly due to the curse of dimensionality. This limitation has hindered its application to high-dimensional problems, making even standard 3D spatial with 1D temporal problems computationally prohibitive. Additionally, the computational requirement increases exponentially with the discretization density of the domain. Here, to address these challenges and enhance scalability for high-dimensional PDEs, we introduce the Separable physics-informed DeepONet (Sep-PI-DeepONet). This framework employs a factorization technique, utilizing sub-networks for individual one-dimensional coordinates, thereby reducing the number of forward passes and the size of the Jacobian matrix required for gradient computations. By incorporating forward-mode automatic differentiation (AD), we further optimize computational efficiency, achieving linear scaling of computational cost with discretization density and dimensionality, making our approach highly suitable for high-dimensional PDEs. We demonstrate the effectiveness of Sep-PI-DeepONet through three benchmark PDE models: the viscous Burgers’ equation, Biot’s consolidation theory, and a parameterized heat equation. Our framework maintains accuracy comparable to the conventional PI-DeepONet while reducing training time by two orders of magnitude. Notably, for the heat equation solved as a 4D problem, the conventional PI-DeepONet was computationally infeasible (estimated 289.35 h), while the Sep-PI-DeepONet completed training in just 2.5 h. These results underscore the potential of Sep-PI-DeepONet in efficiently solving complex, high-dimensional PDEs, marking a significant advancement in physics-informed machine learning.

Neural operator↗

DOE OSTI2021

Hidden transformations in entropy-stabilized oxides

We report entropy-stabilized oxides (ESO) display a reversible entropy-driven phase transformation that can be leveraged to produce a continuum of metastable phase states, allowing for property optimization and novel functionalities. X-ray absorption spectroscopy reveals that entropic stabilization extends to the electronic structure (valence state and cation coordination) in sintered (Co,Cu,Mg,Ni,Zn)O, manifesting as a tunable lattice distortion in the entropy-stabilized phase. Co, Cu, and Zn ions reversibly transform from six-fold to four-fold coordinated structures and from low to high valence states due to the competition between electronic structures that are equilibrium and enthalpy-driven or metastable and entropy-driven. The segregation of a Cu-rich tenorite phase and a Co-rich spinel phase influences the electronic structure evolution. ESOs can adjust their electronic structures through heat treatment, providing a powerful tool for developing functional properties. These results indicate that the definition of entropy stabilization should include entropy-stabilized electronic structures, providing motivation to reassess previously studied HEO materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

X-ray Scattering and Coarse-Grained Simulations for Clustering and Interactions of Monoclonal Antibodies at High Concentrations

Attractive protein-protein interactions (PPI) in concentrated monoclonal antibody (mAb) solutions may lead to reversible oligomers (clusters) that impact colloidal stability and viscosity. Herein, the PPI are tuned for two mAbs via the addition of arginine (Arg), NaCl, or ZnSO 4 as characterized by the structure factor ( S eff (q)) with small angle x-ray scattering (SAXS). The SAXS data are fit with molecular dynamics simulations by placing a physically relevant short-ranged attractive interaction on selected beads in coarse-grained 12 bead models of the mAb shape. The optimized 12-bead models are then used to differentiate key microstructural properties, including center of mass radial distribution functions ( g COM (r)), coordination numbers and cluster size distributions (CSD). The addition of co-solutes results in more attractive Seff(q) relative to the no co-solute control for all systems tested, with the most attractive systems showing an upturn at low q . Only the All1 model with an attractive site in each Fab and Fc region (possessing Fab-Fab, Fab-Fc and Fc-Fc interactions) can reproduce this upturn, and the corresponding CSDs show the presence of larger clusters compared to the control. In general, for models with similar net attractions, i.e., second osmotic virial coefficients, the size of the clusters increases as the attraction is concentrated on a smaller number of evenly distributed beads. Here, the cluster size distributions from simulations are used to improve the understanding and prediction of experimental viscosities. The ability to discriminate between models with bead interactions at particular Fab and Fc bead sites from SAXS simulations, and to provide real space properties (CSD and g COM (r)), will be of interest in engineering protein sequence and formulating protein solutions for weak PPI to minimize aggregation and viscosities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Assessing Substitution Effects on Surface Chemistry by in Situ Ambient Pressure X-ray Photoelectron Spectroscopy on Perovskite Thin Films, BaCe x Zr 0.9– x Y 0.1 O 2.95 ( x = 0; 0.2; 0.9)

Performance of proton-solid oxide fuel cells (H+-SOFC) is governed by ion transport through solid/gas interfaces. Major breakthroughs are then intrinsically linked to a detailed understanding of how parameters tailoring bulk proton conductivity affect surface chemistry in situ, at an early stage. In this work, we studied proton and oxygen transport at the interface between H+-SOFC electrolyte BaCexZr0.9–xY0.1O2.95 (x = 0; 0.2; 0.9) thin films and the gas (100 mTorr of H2O and O2) by using synchrotron-based ambient pressure X-ray photoelectron spectroscopy at operating temperature (>400 °C). We developed highly textured BaCexZr0.9–xY0.1O2.95 epitaxial thin films, which exhibit high level of in-plane proton conductivity, that is, up to 0.08 S cm–1 at 500 °C for x = 0.9. Upon applying 100 mTorr water partial pressure above 300 °C, major changes are observed only in the O 1s and Y 3d core level spectra, with a clear Zr/Ce ratio dependency. OH– formation is favored by Ce content while initiated near Y. Hydration is also associated with surface secondary phase growth comprising oxygen-under-coordinated yttrium and/or yttrium hydroxide. With BaCe0.2Zr0.7Y0.1O2.95, high levels of ionic conductivities and chemical stability are obtained as a result of the optimized surface reaction kinetics, with low activation energy barrier for proton transport while restraining formation of OH–/SO42– adsorb species.

bio-inspired, energy storage (including batteries ↗