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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Residual estimation for grid modification in wall-modeled large eddy simulation using unstructured high-order methods

Here, the accuracy and computational cost of a large eddy simulation are highly dependent on the computational grid. Building optimal grids manually from a priori knowledge is not feasible in most practical use cases; instead, solution-adaptive strategies can provide a robust and cost-efficient method to generate a grid with the desired accuracy. We adapt the residual estimation algorithm developed by Toosi and Larsson for Discontinuous Galerkin Spectral Elements Methods (DGSEM) to guide the grid-adaptation process. The core of the method is the computation of the estimated modeling residual using the polynomial basis functions used in DGSEM, and the averaging of the estimated residual over each element. The final method is assessed in multiple channel flow test cases and for the transonic flow over an airfoil, in both cases making use of mortar interfaces between elements with hanging nodes. The method is found to be robust and reliable, and to provide solutions on grids with significantly fewer elements at comparable accuracy compared to when using human-generated grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Constructing Highly Porous Low Iridium Anode Catalysts Via Dealloying for Proton Exchange Membrane Water Electrolyzers

Iridium (Ir) is the most active and durable anode catalyst for the oxygen evolution reaction (OER) for proton exchange membrane water electrolyzers (PEMWEs). However, their large-scale applications are hindered by high costs and scarcity of Ir. Lowering Ir loadings below 1.0 mgcm -2 causes significantly reduced PEMWE performance and durability. Therefore, developing efficient low Ir-based catalysts is critical to widely commercializing PEMWEs. Herein, an approach is presented for designing porous Ir metal aerogel (MA) catalysts via chemically dealloying IrCu alloys. In this study, the unique hierarchical pore structures and multiple channels of the Ir MA catalyst significantly increase electrochemical surface area (ECSA) and enhance OER activity compared to conventional Ir black catalysts, providing an effective solution to design low-Ir catalysts with improved Ir utilization and enhanced stability. An optimized membrane electrode assembly (MEA) with an Ir loading of 0.5 mg Ir cm -2 generated 2.0 A cm -2 at 1.79 V, higher than the Ir black at a loading of 2.0 mg Ir cm -2 (1.63 A cm -2 ). The low-Ir MEA demonstrated an acceptable decay rate of ≈40 µV h -1 during durability tests at 0.5 (>1200 h) and 2.0 A cm -2 (400 h), outperforming the commercial Ir-based MEA (175 µV h -1 at 2.0 mg Ir cm -2 ).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phases of $ \mathcal{N} $ = 2 Sachdev-Ye-Kitaev models

We study N = 2 supersymmetric Sachdev-Ye-Kitaev (SYK) models with com- plex fermions at non-zero background charge. Motivated by multi-charge supersymmetric black holes, we propose a new N = 2 SYK model with multiple U(1) symmetries, integer charges, and a non-vanishing supersymmetric index, realizing features not present in known SYK models. In both models, a conformal solution with a super-Schwarzian mode emerges at low temperatures, signaling the appearance of nearly AdS2/BPS physics. However, in contrast to complex SYK, the fermion scaling dimension depends on the background charge in the conformal limit. For a critical charge, we find a high to low entropy phase transition in which the conformal solution ceases to be valid. This transition has a simple interpretation– the fermion scaling dimension violates the unitarity bound. We offer some comments on a holographic interpretation for supersymmetric black holes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Technical, economic, and load-following capabilities assessment of grid-connected geothermal and geothermal-solar hybrid systems

The technical and economic performance as well as the load-following capabilities of grid-connected geothermal hybrid systems were assessed in this work. The analyzed geothermal hybrid configuration is composed of a binary geothermal plant integrated with a concentrating solar-thermal system and underground thermal energy storage (UTES) through a primary heat exchanger. Physics-based models for the hybrid system for plant generation capacities of 1, 25, and 50 MW were developed from validated models for each subsystem. Also, an economic model was developed that accounts for different hybrid system capabilities, solar field sizes, and thermal storage duration. The advantage of the geothermal hybrid system was assessed by comparing the performance with the baseline benchmark geothermal plant with a similar configuration and generation capacity. It was found that hybridizing geothermal plants with concentrating solar and thermal energy storage not only improves the thermal efficiency by up to 8 percentage points when additional heat from the solar-UTES loop rises the evaporator temperatures from 70 to 125 °C, but also enhances the load-following capability for the geothermal plant, which can meet a typical residential load profile with a power rate of change 0.25 kW/s with an absolute error under 13 kW for a 1 MW plant. Other benefits of hybridization include resource preservation and a potential LCOE reduction of up to 56% for a 50 MW geothermal hybrid plant having a 50% solar share, a 1.4 solar multiple, and 24-h storage capacity. The results presented in this work demonstrate that hybridizing geothermal systems transforms them into a flexible and cost-effective solution for addressing the dynamic requirements of modern electric grids.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Intramolecular Electrostatic Effects on O 2 , CO 2 , and Acetate Binding to a Cationic Iron Porphyrin

Noncovalent electrostatic interactions are important in many biological and chemical reactions, especially those that involve charged intermediates. There has been a growing interest in using electrostatic ligand designs—placing charges in the second coordination sphere—to improve molecular reactivity, catalysis, and electrocatalysis. For instance, an iron porphyrin bearing four cationic ortho -trimethylanilinium groups, Fe( o -TMA), has been reported to be an exceptional electrocatalyst for both the carbon dioxide reduction reaction (CO 2 RR) and the oxygen reduction reaction (ORR). These reactions involve many different steps, and it is not evident which steps are affected by the four positive charges, or why. By comparing Fe( o -TMA) with the related iron-tetraphenylporphyrin, this work examines how covalently positioned charged groups affect substrate binding and other key pre-equilibria of both the ORR and CO 2 RR, specifically acetate, dioxygen, and carbon dioxide binding. This study is among the first to directly measure the effects of electrostatics on ligand-binding. The results show that adding electrostatic groups to a catalyst design often results in a complex interplay of multiple effects, including changes in pre-equilibria prior to substrate binding, combinations of through-space and inductive contributions, and effects of ionic strength and solution dielectric. The inverse half-order dependence of binding constant on ionic strength is proposed as a clear marker for an electrostatic effect. Overall, the conclusions provide guidance for the increasingly popular electrostatic ligand designs in catalysis and other reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Automated Controller Hardware-In-The-Loop Testbed for EV Charger Resilience Analysis

This paper focuses on the development of a tool that includes an automated testbed with controls, protection, and communications integrated into a real-time system to provide a platform to generate data sets for failure modes and effects analysis. This tool establishes a value for automation of data generation for different scenarios and addresses the gap of nonexistent field data for different applications and use cases. The features of this tool can further be expanded to include multiple power electronics models, communication protocols, and scaled system architectures. This general framework was evaluated for a DC fast charger system use case to provide quantitative solution for resiliency.

Starke, Michael↗
DOE OSTI2024

Axolotl: a scalable genomics library based on Apache Spark (Axolotl) v1.0.0

Axolotl is a Python library for scalable distributed genome and metagenome data analysis. Existing tools and systems that we rely on are struggling to keep up with the rapid explosion of genomic data. Compounding this issue, developing scalable solutions require a steep learning curve in parallel programming, which presents a barrier to academic researchers. While we do have scalable solutions for specific tasks, we lack comprehensive, end-to-end solutions. It's this gap in our toolkit that we aim to address with Axolotl. The Axolotl library is built for easy parallel processing, efficiently handling multiple tasks or large datasets simultaneously, and scaling up to meet the demands of extensive genomic data analysis.

Wang, Zhong↗
DOE OSTI2021

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration (FY2020 Final Report)

R2R processing is used to manufacture a wide range of products for various applications which span many industrial business sectors. The overall R2R methodology has been in use for decades and this continuous technique traditionally involves deposition of material(s) onto moving webs, carriers or other continuous belt-fed or conveyor-based processes that enable successive steps to build a final version which serves to support the deposited materials. Established methods that typify R2R processing include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating, and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes for energy storage, and barrier and membrane materials. Due to innovation in materials and process equipment, high-quality yet very low-cost multilayer technologies have the potential to be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, the means must be available to enable manufacture of these products in a cost-competitive manner that is affordable. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches. However, more early-stage research is needed to solve the challenge of linking the materials (particles, polymers, solvents, additives) used in ink and slurry formulations and the coating and drying processes to the ultimate performance of the final R2R product, especially for a process that uses multiple layers of deposition to achieve the end product. To solve the problems associated with these challenges, the R2R Collaboration is executing a research program with outcomes that will ultimately link modeling, processing, metrology and defect detection tools, thereby directly relating the properties of constituent particles and processing conditions to the performance of final devices. This collaborative approach was designed to foster identification and development of materials and processes related to R2R for clean-energy materials development. Using computational and experimental capabilities by acknowledged subject matter experts within the supported National Laboratory system, this project leverages the capabilities and expertise at each of five National Laboratories to further the development of multilayer technologies that will enable high-volume, cost-competitive platforms. A typical R2R process has three steps: (1) mixing of particles and various constituents in a slurry, (2) coating of the ink/slurry mixture on a substrate, and (3) drying/curing and processing of the coating. Final performance of devices made via R2R processes is dependent on the active materials (e.g., electrochemical particles in battery or fuel cell electrodes) and the device structure that stems from the governing component interactions within the various steps. However, a fundamental understanding of the underlying mechanisms and phenomena is still lacking, which is why industrial-scale R2R process development and manufacturing is still largely empirical in nature. The FY 2019 through FY 2021 program addresses aspects of the following two targets from the AMO Multi-Year Program Plan: (1) Target 8.1 Develop technologies to reduce the cost per manufactured throughput of continuous R2R manufacturing processes. (A) Increasing throughput of R2R processes by 5 times for batteries (to 50 square feet per minute (50 ft 2 /min)) and capacitors and 10 times for printed electronics and the manufacture of other substrates and MEs used in support of these products. (B) Developing resolution capabilities to enable registration and alignment that will detect, align, and co-deposit multiple layers of coatings and print < 1-micron (1 µm) features using continuous process scalable for commercial production. (C) Developing scalable and reliable R2R processes for solution deposition of ultra-thin (<10 nm) films for active and passive materials. (D) Develop in-line multilayer coating technology on thin films with yields greater than 95%. (2) Target 8.2 Develop in-line instrumentation tools that will evaluate the quality of single and multilayer materials in-process. (A) Developing in-line QC technologies and methodologies for real-time identification of defects and expected product properties “in-use/application” during continuous processing at all size-scales with a focus on the “micro” and “nano” scale traces, lines, and devices, i.e., <1 μm at 300 ft./min for R2R processing in air and <10 nm at 20 ft./min for vacuum (B) Developing technologies to increase the measurement frequency of surface rheology without significant cost increases with a goal of a 10-nanometer in-line profilometry at a production rate of 100,000 square millimeters per minute (100,000 mm 2 /min).

42 ENGINEERING↗
DOE OSTI2023

Final Design for Thermal/Epithermal eXperiments (TEX) with Chloride Absorbers to Provide Validation Benchmarks for Y-12 Electrorefining Facility

Uranium electrorefining operations at Y-12 require validation for chlorine absorption and reflection. Plutonium chloride solution operations at Los Alamos National Laboratory require chlorine absorption validation. The growing need for chlorine validation is evident to the wider criticality safety community, with multiple attendees at the recent TEX 2.0 meeting at Lawrence Livermore National Laboratory (May 2023) requesting validation for chlorine (Idaho National Laboratory (INL), Institute de radioprotection et de surete nucleaire (IRSN), Savannah River Nuclear Site (SRNS), LANL, and Y-12). Los Alamos National Laboratory has recently performed, and benchmarked, an experiment titled Chlorine Worth Study (CWS) for the internal operations at the lab, but due to the difficulties in precisely characterizing the material compositions of the chlorine absorbers it is advantageous to perform a complimentary study with a different chlorine-based absorber material. Furthermore, having a uranium-based vs plutonium-based experiment provides a separate and important validation basis for criticality safety and nuclear data evaluation. The original final design report for the study of chlorine absorption using the TEX-HEU experimental base was presented in 2022, but used the same chlorine-bearing materials that were found to be difficult to characterize in the LANL benchmark. A complete redesign of the experiment has been performed looking at alternative absorber materials in various forms to produce an experiment that is fully characterizable. This report presents five novel chlorine experiments using the TEX-HEU test bed which provides direct comparison to the Y-12 and INL/Terrapower application needs, utilizing sodium chloride (NaCl) absorber plates. The absorber plates will consist of granulated NaCl (≥99.5% pure), which will be fully encapsulated in aluminum tins, providing a simple but effective chlorine-based absorber material that can be completely characterized. Of the five configurations presented in this report, it is expected that two or three configurations will be down selected for the actual experiment, with the other configurations being alternates. Three of the configurations are in the standard configuration, where the absorber is placed directly on the HEU fuel plates, and two in the sandwich configuration, where the absorber is surrounded by polyethylene moderators to force additional neutron thermalization prior to reaching the absorber. There are two thicknesses of NaCl absorber plates: 3/16” and 1/4” active thicknesses (i.e. not including the encapsulation). Both variations of the absorbers have an active absorber radius of 6” and a total radius of 7.5” to match the diameter of the HEU plates, with the outer 1.5” being aluminum encapsulation. The high-density polyethylene (HDPE) moderators are of the thicknesses: 27/16”, 7/4”, 1/8”, 11/16”, and 3/4”. The final configurations have six (one sandwich and one standard configuration), eight (one sandwich and one standard configuration), and 18 total fuel layers (standard configuration). The standard and sandwich configurations were designed such that the differences in moderator thicknesses are 1” HDPE, which were already procured for the original CED-2. The proposed configurations were precisely tuned to closely match the sensitivity profiles and neutron spectra of the Y-12 upset cases and were also compared to the INL/Terrapower upset cases. The assessment of experimental uncertainties of the non-absorber components was predicted to be 0.00114 Δk eff . The assessment of uncertainties resulting from the absorbers was predicted to be 0.00029 Δk eff . This results in a total uncertainty of 0.00118 Δk eff . Many of the largest uncertainties, namely the moderator densities, may be reduced with precision dimensional inspection of the components. The 1” HDPE moderators as well as the HDPE reflectors from the original CED-2 were incorporated in the final designs presented here. Additional HDPE moderator plates must be fabricated to complete the configurations. NaCl absorber plates will by fabricated at LLNL. The total additional cost is expected to be $\$$54,250 for the remaining components. Precise inspection, including dimensional, mass, density, and impurity, is recommended for all components. LLNL estimates that these costs are around $\$$12,000. It is expected, based on previous TEX-HEU experiments, that three weeks of experimental facility time is needed to complete the experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Portable fiber optic sensor for rare earth elements and other critical metals using photoluminescence methods

Rare earth elements and other metals are vital to a range of technologies that are used in the energy and defense sectors. However, monopolistic market conditions have caused significant concern over the stability of the critical metal supply chain, and this has spurred extensive efforts in many nations to produce these metals domestically, both from conventional sources such as mining and well as from unconventional sources such as coal and its utilization byproducts. Slow and expensive characterization methods pose a significant barrier for both metals prospecting and process monitoring. A promising solution to this challenge is the development of highly sensitive luminescent sensors for metals, which can offer low costs, portability, and sensitivity. Anionic zinc adeninate metal-organic frameworks (BioMOFs) are known to distinguishing and detect part-per-billion levels of terbium, europium, samarium, and dysprosium in water by sensitizing the narrow, element-specific emission bands from these lanthanides. Here, a BioMOF material is immobilized onto a large diameter, solarization-resistant fiber optic tip integrated with a portable, low-cost spectrometer for rare earth element sensing. Immobilizing the sensing material on fiber instead of dispersing the sensing material in solution offers several advantages: it facilitates solvent removal, which enhances luminescent signal from the sensitized lanthanides, and it also allows the BioMOF to be recycled for multiple uses. The sensing system was deployed on a simulated process stream and exhibited qualitative agreement with inductively-coupled plasma mass spectrometry for terbium and europium detection, highlighting the potential for the sensing system to be deployed for real-world applications. By using different sensing materials, the same portable sensor may be deployed to detect other energy relevant metals such as cobalt, providing a cost-effective and sensitive platform for critical metal characterization.

Crawford, Scott↗
DOE OSTI2023

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗
DOE OSTI2024

"Source Term Modeling for Advanced Gas Micro-Reactors"

Maintaining the safety of the public, environment, and operating personnel is the most important factor in designing, operating, maintaining, and decommissioning nuclear reactors. In recent years, there has been a growing interest in the development of micro-reactors employing TRi-structural ISOtropic (TRISO)-coated particle fuel. In gas reactors, TRISO fuel plays an important role in the safety case for high temperature reactors because of the fission product retention properties of the fuel. This ability enables the use of a functional containment strategy for the reactor where multiple barriers are used to prevent fission product release to the environment. Part of the safety analysis of these advanced reactors is the assessment of radionuclide releases under normal and accident conditions through the multiple credited safety barriers. Using conservative assumptions, a mechanistic analysis can be performed to quantify these releases that combines the probabilistic assessment of failure with analytic solutions to radionuclide transport equations. Source term modeling for TRISO fuel has been performed for previous reactor designs; however, these models are outdated, in many cases proprietary, and need updates to be applied to the current state of TRISO fuel technology and alternative gas reactor core configurations [1]. Currently, the only publicly available source term assessment for gas reactors is an expert-based Monte Carlo simulation based on the effectiveness of the fuel kernel, coating layers, and graphite block in a modular high temperature gas reactor [2]. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that could be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. The release is calculated by the diffusion of the key safety important fission products through the kernel, silicon carbide (SiC), graphite for both intact and defective TRISO particles based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system to remove fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. The model then can calculate the fission product release for any transient temperature profile and fission product releases can then be used to assess radiological dose to the workers and the public using conventional dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy (DOE) Advanced Gas Reactor (AGR) TRISO fuel development program. The model is coded in python with inputs and outputs in excel spreadsheets, as well as python plotting utilities to aid in the interpretation of the results. References: [1] INL, NGNP Mechanistic Source Term White Paper, INL-10-17997, July 2010. [2] David A. Petti, Richard R. Hobbins, Peter Lowry, Hans Gougar, “Representative Source Terms and The Influence of Reactor Attributes on Functional Containment in Modular High Temperature Gas-cooled Reactors,” Nuclear Technology, Vol. 184, p. 181-197, Nov. 2013.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Resilient Node Cluster Analysis Tool (ReNCAT) v. 2.1

SAND2021-6533 O The Resilient Node Cluster Analysis Tool (ReNCAT) identifies portions of a power distribution network that can be isolated into microgrids in order to supply services to a community during disruptive events. Candidate microgrid configurations are evaluated using a burden metric, a measure of the relative effort community members must expend to acquire services required for their well-being. Results present multiple candidate configurations, each with a different balance of cost and burden. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Melander, Darryl↗
DOE OSTI2025

Framework to select robust energy retrofit measures for residential communities

Residential building energy retrofits are essential for enhancing environmental sustainability and reducing energy costs. The selection of retrofit measures is influenced by factors such as building systems, occupant behavior, government policy, weather variability, and climate change, all of which can significantly impact energy performance. Compared to retrofitting individual homes, evaluating and selecting optimal retrofit solutions for an entire community is challenging due to diverse residential compositions and variability present. Therefore, engineering robustness is crucial for ensuring consistent energy performance and resilience across different conditions. In this context, robustness refers to the ability of a retrofit measure to maintain its functionality and remain an optimal choice despite external disturbances or changes in inputs and conditions. This study presents a framework for evaluating the robustness of multiple retrofit measures across various building systems, occupant behaviors, and environmental scenarios at the community level. The framework comprises five key steps: scenario model development, integration of the National Residential Efficiency Measures database, energy performance simulation, cost-benefit aggregation, and retrofit solution selection. Each step enhances the framework’s robustness by incorporating the diversity of building characteristics, occupant behaviors, environmental conditions, retrofit options, and evaluation criteria. The framework’s effectiveness is demonstrated through a case study in southern Michigan in the United States, which includes 63 one-story single-family houses, 121 two-story single-family houses, and 8 townhouses. The study identifies furnace retrofits as the most robust solution for the entire community, consistently achieving source energy reductions of 4.7 %–8.0 % and payback period of 10–20 years across various scenarios. These findings are consistent with previous research, indicating the framework’s potential for broader applications in optimizing community-scale residential energy retrofits.

Shu, Lei↗
DOE OSTI2021

Interactions of Wind Energy Project Siting, Wind Resource Potential, and the Evolution of the U.S. Power System

The interactions of wind energy project siting, resource potential, and power system evolution are critical to understand given interest in high renewable energy systems, particularly as wind costs have fallen and grid operators implement solutions to manage variable generation. This study applies an integrative approach that combines spatially-explicit resource potential analysis with high spatial resolution U.S. electricity system modeling. Multiple wind supply curves, representing variations in siting regimes that account for interactions with built infrastructure, regulatory, physical, and social land use factors, are evaluated to determine how siting could influence prospective wind development. Different siting regimes lead to variations in future wind capacity, with the greatest impacts observed under scenarios with high demand for clean energy. With the tightest emissions limit modeled, 2050 onshore wind capacity varied by +7% (49 GW) in the least-restrictive siting regime to a decrease of 37% (270 GW) under the most-constrained case. More-stringent siting restrictions lead to higher electricity prices and emissions that should be weighed with local impacts. Under restrictive siting regimes, wind deployment is also sensitive to transmission availability and wind plant design. Overall, the findings highlight the importance of local land use considerations in regional and national power system planning.

17 WIND ENERGY↗
DOE OSTI2022

Frozen storage of proteins: Use of mannitol to generate a homogenous freeze-concentrate

Therapeutic proteins may be subjected to several freeze–thaw cycles throughout manufacturing and storage. The protein solution composition and the freezing conditions may lead to incomplete ice crystallization in the frozen state. This can also result in freeze-concentrate heterogeneity characterized by multiple glass transition temperatures and protein destabilization. The overall objective was to investigate the potential advantages of including a crystallizing excipient (mannitol) along with a sugar (sucrose or trehalose) for frozen storage. Here, this study showed that the addition of mannitol, a readily crystallizing excipient, facilitated ice crystallization. Inclusion of an isothermal hold during cooling (annealing) maximized the mannitol crystallization and resulted in a homogenous freeze-concentrate of a constant composition characterized by a single glass transition temperature. The role of freezing rate and annealing on both mannitol and ice crystallization were discerned using high intensity synchrotron radiation. The addition of sucrose or trehalose, at an appropriate concentration, stabilized the protein. The mannitol to sugar ratio (3:1 or 1:1, 5 % w/v) was optimized to selectively cause maximal crystallization of mannitol while retaining the sugar amorphous. Human serum albumin (1 mg/mL) in these optimized and annealed compositions did not show any meaningful aggregation, even after multiple freeze–thaw cycles. Thus, in addition to a sugar as a stabilizer, the use of a crystallizing excipient coupled with an annealing step can provide an avenue for frozen storage of proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evidence-based target setting informs blue carbon strategies for nationally determined contributions

The magnitude and pace of global climate change demand ambitious and effective implementation of nationally determined contributions (NDCs). Nature-based solutions present an efficient approach to achieving mitigation, adaptation and resilience goals. Yet few nations have quantified the diverse benefits of nature-based solutions to evaluate and select ecosystem targets for their NDCs. Here we report on Belize’s pursuit of innovative, evidence-based target setting by accounting for multiple benefits of blue carbon strategies. Through quantification of carbon storage and sequestration and optimization of co-benefits, we explore time-bound targets and prioritize locations for mangrove protection and restoration. We find increases in carbon benefits with larger mangrove investments, while fisheries, tourism and coastal risk-reduction co-benefits grow initially and then plateau. We identify locations, currently lacking protected status, where prioritizing blue carbon strategies would provide the greatest delivery of co-benefits to communities. These findings informed Belize’s updated NDCs to include an additional 12,000 ha of mangrove protection and 4,000 ha of mangrove restoration, respectively, by 2030. Our study serves as an example for the more than 150 other countries that have the opportunity to enhance greenhouse gas sequestration and climate adaptation by incorporating blue carbon strategies that provide multiple societal benefits into their NDCs.

54 ENVIRONMENTAL SCIENCES↗