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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Visualizing plant cell wall changes proves the superiority of hydrochloric acid over sulfuric acid catalyzed γ-valerolactone pretreatment

Thermochemical pretreatment is one of the key steps to process lignocellulosic biomass for production of biofuels and biomaterials. γ-valerolactone (GVL) has been used as a green and renewable solvent to efficiently dissolve lignin under acidic conditions and enhance subsequent enzyme digestibility. Further improvement is still required to lower the pretreatment temperature in order to reduce sugar degradation and irreversible lignin condensation, as well as the capital cost. In this study, we compared the use of HCl and H 2 SO 4 as catalysts during GVL pretreatment, and found the performance of GVL-HCl at 100 °C was comparable to that of GVL-H 2 SO 4 at 120 °C in terms of xylan and lignin removal and enzyme digestibility. We further monitored the lignin removal and cellulose accessibility in the cell walls at different pretreatment time points by imaging the changes in lignin auto-fluorescence and in CtCBM3-GFP binding with confocal laser scanning microscopy (CLSM), respectively. We found GVL-HCl pretreatment at a relative low temperature (100 °C) could rapidly remove lignin in the compound middle lamella and cell corner areas, which concurred with the increase of CtCBM3-GFP binding in these areas. Real-time imaging of cell wall degradation by cellulases further revealed that the secondary cell walls could be digested from both cell lumen and CML sides, and eventually fully deconstructed within 24 h. Furthermore, our results provide new insight into the effects of chloride anions on plant cell wall structure during GVL pretreatment, and offer potential routes to further optimize and enhance the efficiency of GVL-based pretreatment.

09 BIOMASS FUELS↗
DOE OSTI2024

2024 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2024 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products now include data (Excel workbook, Tableau workbooks, and structured summary csv files), as well as documentation and user engagement via a website, presentation, and webinar. Starting in 2021, the data are cloud optimized and provided in the OEDI data lake. The data for 2015 - 2020 are can be found on the NREL Data Search Page. The website documentation can be found on the ATB Website.

Array↗
DOE OSTI2021

Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development Of Thermodynamic and Kinetic Simulation Tools and Testing Procedures for Enhanced Durability of Concrete Containing Industrial By-Products

This project developed screening tools that enable evaluation of alternative cementitious binders that create concretes to significantly reduce energy and emissions while remaining cost competitive on both initial and long-term costs. The team began with the viewpoint that acceptance of new cementitious binder products has a substantially greater chance of successful implementation when capital investment is not excessive and the end product has customers that have experience and resources to use this. As such, a binder system that is based on portland cement with blended using industrial by-products (alternative cementitious materials) has the potential for dramatic and meaningful impact. The team has focused on developing implementable solutions in specifications and current practice. This however requires three main factors: 1) ability to screen byproducts and alternative materials for success, 2) ability to ‘treat’ materials chemically to enhance kinetics, and 3) ability to provide predictions of performance of both binders and concrete from first principles. The project developed/refined a state of the art and scientifically based screening test for SCM called the pozzolanic reactivity test. The team developed kinetic models to simulate these materials as well as experimental approaches to alter selected reactions. Simulation tools were developed that enable the performance of concrete to be predicted based on the chemistry and reactivity of the cement and alternative SCM. Specifically, this project: • enhanced the kinetic reactivity models for use in multi-scale computational programs that use thermodynamics to predict reaction products. 2 • developed scaling models to extend thermodynamic modeling to link these models with pore structure. This enables strength, transport property, and coupled transport prediction. • developed tools to predict performance of cementitious materials using the pozzolanic reactivity test and chemical composition. The predicted properties are consistent with AASHTO R101 and the CEB-FIP model code and can be measured using associated test procedures. • demonstrated mechanical and fracture based modeling tools that thermodynamic predictions and inputs to predict concrete service life. These results have been used to demonstrate the value of enabling specifications to include ASTM C 595 cement as well ASTM C150 cement. In addition, these products are being used to expedite the evaluation of alternative SCM to aide in determining which materials have potential value and what ‘compositions’ of blended cements merit further investment.

42 ENGINEERING↗
DOE OSTI2021

Development of Additively Manufactured Complex Tools for Autoclave Cure Composites

IACMI Project 4.9, Tooling for Composites with Washout Features Produced by Additive Manufacturing, assembled a team including the industry lead, Ability Composites, NREL and Colorado State University (CSU). Ability Composites had originally expressed interest in alternate methods of producing tooling for composite parts. In follow-up discussions, it became clear that one of the bigger tooling challenges revolved around small production volume composite parts that were tooled on washout material due to the complex geometry. To build an understanding of the potential, both from a technology and a cost perspective, for replacing conventional washout tooling with 3D printed thermoplastic tooling, a number of commercially available dissolvable FDM printing materials were evaluated, leading to tooling representative of commercial articles of interest to Ability Composites. Ultimately, Ability Composites was able to directly compare autoclave processed prepreg composite parts produced on conventional washout tooling to composite parts molded on 3D printed dissolvable tooling produced at CSU. Small, laboratory test specimens were developed to investigate the structural performance of the candidate materials under autoclave processing conditions, which were nominally 121 °C (250 °F) and 345 kPa (50 psi). In addition, several internal structural configurations (infills) were evaluated under autoclave conditions using model materials. The results of these tests indicated that two materials, Stratasys ST 130 and Infinite Materials Solutions Aquasys 180 (AQ 180), were the best candidates, given the specified autoclave processing conditions. ST-130 was slightly more robust than AQ-180; however, the AQ-180 was carried forward as it was dissolvable in water, not requiring the basic solution needed to dissolve ST-130. Based on the preliminary material and 3D printed structures evaluations, larger tools with a truncated square pyramid geometry were created to produce prepreg composite test articles for 3D printed dissolvable tool evaluation under standard autoclave fabrication conditions. Two tools were manufactured using ST-130 and one tool using traditional ceramic washout tooling media. The tools were evaluated for geometric fidelity and surface roughness changes before and after carbon fiber/epoxy prepreg composites were manufactured on the tooling. The autoclave processing did not impact the geometry significantly and was completed at 121 °C and 345 kPa, indicating satisfactory tool performance. The results from surface roughness testing of both the resulting composite and the associated tooling indicated that an adequate surface resulted without the need for a surface sealing step, as was required for the conventional washout tooling. Based on results of the truncated pyramid tests as a basis, ST-130, AQ-120 and AQ-180 materials were carried forward to the tool geometry of interest to Ability Composites. These hollow rectangular bent ducts, which were complex in nature and not extractable after cure, were used to understand the impacts of tool material and thickness. One ST-130 tool was produced as a partially solid part, with an enclosed 40% dense infill region to reduce weight and material use. This was the same approach evaluated in the truncated pyramid portion of the study. This tool was to be envelope vacuum bagged and directly compared to a monolithic tool of conventional washout material. The traditional monolithic ceramic tool was manufactured by Ability composites using CNC-based subtractive methods. An additional five dissolvable polymer tools, manufactured from ST-130, AQ-120, and AQ-180, using a hollow design were 3D printed and used to produce carbon fiber/epoxy composite evaluation articles. These hollow dissolvable tools were expected to be less influenced by the autoclave conditions as the wall was solid and vacuum bagging was inside and outside the tool. This alternative geometry was also evaluated as an option in techno-economic modeling. Print times were reduced from in excess of 3 days to under 30 hours, while surface quality and and tool integrity were substantially improved in the transition from the partially solid tool to the hollow tooling concept. Ability Composites produced autoclave-cured prepreg ducts on each of these tools. The autoclave conditions utilized were more severe than those of the initial trials, reaching temperatures of 160 °C and a pressure of 414 kPa. Under these conditions, the partially solid 3D printed tool with skin and 40% dense infill crushed significantly; however, the thicker ST-130 hollow tool showed good promise, deforming only slightly. The thinner hollow tool walls were unsuccessful as were the other materials. Overall, the hollow tool manufacturing process saved significant amounts of time and material in manufacturing as compared to the solid ducts and produced composite surface quality improvements compared to the traditional washout tooling. The TEM was developed to allow direct comparisons between conventional washout tool manufacturing processes and those developed at CSU. It also allowed for two separate 3D printed tool geometries to be analyzed and compared. In this case, the square bent duct tool geometry was determined to be representative of common washout tools. This geometry was compared with a scaled-up version of it to assess differences in the two manufacturing processes based on tool size. The model was developed to make use of user input in the form of geometry details, process steps, manufacturing parameters, bulk material costs, capital equipment costs, and general costs to calculate overall labor, material, capital equipment, and energy costs per manufactured tool for the conventional and additive manufacturing processes for the two representative geometries. It was also able to estimate step-by-step process times for the manufacturing process and geometries. Based on significant input from Ability Composites and CSU from their knowledge gained from hands-on manufacturing of the 3D printed bent duct tool geometry, costs and process times were calculated for the two manufacturing processes. Results showed that the additive manufacturing techniques developed at CSU can substantially reduce the costs of tool manufacturing by reducing labor times and material usage. This is because additive manufacturing is a relatively hands-off process and allows for the tool design to be optimized to reduce material usage. The disadvantage, however, is that process times for additive manufacturing are significantly longer. The three-dimensional (3D) printing process is slow if tight tolerances are required, but the analysis did show that print times could be reduced with the hollow tool geometry. Also, further advances in additive manufacturing could expedite the process. Costs and process times for the tool washout process were calculated separately. They showed that costs are relatively insignificant when compared to the overall tool manufacturing processes, but with increases in tool size, costs for the conventional manufacturing approach are larger than for additive manufacturing. Again, the washout process for conventional tools is very hands-on, whereas for additively manufactured tools the print medium is dissolved in an automated detergent bath at the sacrifice of process time. The analysis showed that optimizing the additively manufactured tools may also reduce washout times. Overall, Project 4.9 demonstrated that commercially available dissolvable 3D printing materials exist that can be used to produce dissolvable tooling capable of surviving prepreg composites fabrication under autoclave conditions of 121 °C (250 °F) and 345 kPa (50 psi). An alternative hollow dissolvable tool design was developed which was structurally superior to the initial concept and was cost and time effective versus conventional washout tooling. The 3D printed sacrificial tool required no added surface sealing steps prior to composite part layup and cure, offering a significant advantage over the porous conventional washout tooling.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Data Quality Methodology (4.2.1)

SECARB-USA Deliverable 4.2.1 utilizes the outputs from the Needs Assessment (Subtask 2.1) to develop a data quality methodology. Many types of data are needed to evaluate a site for technical and financial viability. Several inventories of data types have been produced (for example NETL, 2010). The objective here is to organize the data types so that the needs met are specified. From this cross index (Table 1 in the Appendix), it will be possible in future tasks to (1) determine, on a site-specific basis, how much of each data type is required at each stage of a project to meet the need, and conversely (2) to further specify and define the data collection methods applied such that the data are tailored to fit that need. Derivative tables can then be developed to semi-quantitively evaluate the extent to which need is critical for early go/no decision points, or if it is more important than average, requiring faster or larger capitalization and spend to meet the need. In an additional step, the current availability of data for a site can be semi-quantitively assessed. From the table of data criticality and the table of data availability, site-specific cost for meeting the data needs can be determined, and allow a pre-permit spend estimated for a portfolio of projects. All of the data needs to evaluate a site are somewhat interconnected. We used criterion (2) above to determine if the data collection design would have to be modified to meet the need; if this was commonly true a linkage was shown. The application of this cross index to sites in the subsequent tasks will demonstrate that the demand for data types varies site-to-site and project-to-project. Examples of factors to be considered are the complexity of the geology, the injection goals such as rate and duration of the injection, and the types of risk and risk tolerance of key stakeholders. In future tasks the team will compare the demand for data with existing data availability. This will, in turn, determine when data needs to be acquired to support project development. For example, in a project area with complex structure, 3-D seismic data may be needed earlier and more urgently than in an area with simple rock body geometries. In some locations, a 3-D seismic survey has already been collected and can be purchased. In other locations the project developer will need to collect these data. For another example, a project near an urban area or near to a park may generate earlier and more substantive public concern than a site that is developed in mined lands. A calculation using the derivative from table 1 will show the different investment needs. Project cost will vary corresponding to data criticality and data availability.

42 ENGINEERING↗
DOE OSTI2024

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗
DOE OSTI2022

2022 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2022 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products now include data (Excel workbook, Tableau workbooks, and structured summary csv files), as well as documentation and user engagement via a website, presentation, and webinar. Starting in 2021, the data are cloud optimized and provided in the OEDI data lake. The data for 2015 - 2020 are can be found on the NREL Data Search Page. The website documentation can be found on the ATB Website.

Array↗
DOE OSTI2023

Magnesium production by molten salt electrolysis with liquid tin cathode and multiple effect distillation

Low-cost clean primary production of magnesium metal is important for its use in many applications, from light-weight structural components to energy technologies. This work describes new experiments and cost and emissions analysis for a magnesium metal production process. The process combines molten salt electrolysis of MgO using MgF₂-CaF₂ electrolyte and a reactive liquid tin cathode, with gravity-driven multiple effect thermal system (G-METS) distillation to separate out the magnesium product, and re-use of the tin. Electrolysis experiments with carbon anodes showed current yield above 90%, while a yttria-stabilized zirconia solid oxide membrane (SOM) anode experiment showed 84% current yield. G-METS distillation is an important component of the envisioned process. It can potentially lower costs and energy use considerably compared with conventional magnesium distillation. Techno-economic analysis including detailed mass and energy balances shows that this electrolyte composition could lower costs by utilizing CaO, which is the primary impurity in MgO, as the Hall-Héroult process uses the sodium impurity in alumina. Analysis options include: raw material types (magnesite rock vs. brine or seawater), drying and calcining using electricity vs. natural gas, and carbon vs. SOM anode type. Using SOM inert anodes results in a cost premium around 10%–15%, mostly due to higher electrical energy usage resulting from membrane resistance, and reduces GHG emissions by approximately 1 kg CO₂/kg Mg product. Capital and operating cost estimates, and cradle to gate greenhouse gas (GHG) emissions analysis under several raw material and process technology scenarios, show comparable costs and emissions to those of aluminum production.

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

2023 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2023 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products now include data (Excel workbook, Tableau workbooks, and structured summary csv files), as well as documentation and user engagement via a website, presentation, and webinar. Starting in 2021, the data are cloud optimized and provided in the OEDI data lake. The data for 2015 - 2020 are can be found on the NREL Data Search Page. The website documentation can be found on the ATB Website.

Array↗
DOE OSTI2020

Argonne’s global critical materials agent-based model (GCMat)

Several studies have identified rare earths as critical materials. Although reasonably abundant in the Earth’s crust, rare earths typically occur in low concentrations of mined ores. Processes for recovering rare earth concentrates from these ores are complex and capital intensive. Further, lead times for deposit development, licensing, and construction are long, with reports of 10- 15 years. China is a major player in the rare earths supply chain, both in production capacity and technology innovation. In 2017, China supplied more than 80% of global rare earth oxide demand. Rare earth elements (REEs) have unique magnetic, catalytic, and phosphorescent properties that significantly improve performance of a wide range of technologies. These technologies span aerospace, energy, telecommunications, electronics, transportation, defense, and other diverse applications. Consequently, disruptions in rare earth supply can have a significant societal impact. Estimating that impact requires understanding of the dynamics across the supply chain, from rare earth oxide extraction to end use application. This report documents Argonne’s Global Critical Materials model (GCMat), first described by Riddle et al. 2015. GCMat provides capabilities to explore supply chain dynamics and uncertainty under scenarios of demand growth or shrinkage, technology adoption, supply disruptions, and trade policies and mitigation strategies of new supply sources, product substitution, consumer thrifting, and stockpiling. Supply chain participants from rare earth mining through final demand are modeled as interacting agents who make market decisions independently as time progresses. Since the version documented in Riddle et al. 2015, GCMat has been expanded to cover additional REEs, derived products and supply chains that use these REEs, and includes new agent behaviors and modeling capabilities. Section 2 provides a summary of the GCMat model design, including the structure of the model and key assumptions, section 3 summarizes methods used for model calibration and sensitivity analysis, and section 4 provides examples of model results.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Role of Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology: Proceedings of a Workshop

Quantum concepts hold the potential to enable significant advances in sensing and imaging technologies that could be vital to the study of biological systems. The workshop Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology, held online March 8–10, 2021, was organized to examine the research and development needs to advance biological applications of quantum technology. Hosted by the National Academies of Sciences, Engineering, and Medicine, the event brought together experts working on state-of-the-art, quantum-enabled technologies and scientists who are interested in applying these technologies to biological systems. Through talks, panels, and discussions, the workshop facilitated a better understanding of the current and future biological applications of quantum-enabled technologies in fields such as microbiology, molecular biology, cell biology, plant science, mycology, and many others. The workshop was organized around three main themes. The first, quantum in biology, examined quantum concepts that are hypothesized to be important for life processes and that researchers are working to observe through biological imaging and sensing. The second, quantum for biology, addressed ways to use quantum concepts to enhance technologies for biological imaging and sensing. The third, biology for quantum, offered a wider discussion of how the frontiers of biological imaging and sensing could enable future study using quantum concepts, tools, or technologies. Throughout the workshop, participants identified a wide range of emerging approaches and opportunities at the intersection of quantum physics and biological sensing and imaging. During the workshop, there were some differences in how each speaker defined the term quantum. During one of the panels, Prem Kumar offered thoughts on what phenomena are classical versus quantum, explaining that techniques get progressively more quantum as you move from just having superposition to having superposition with measurement and entanglement. Another explanation from Clarice Aiello delineates the definition into several levels. This includes a base level of “quantum-ness,” which reflects that all matter is made of atoms, and when these particles are isolated they behave based on quantum mechanical principles. A second level is related to quantum coherence, where a single quantum object might be found in a coherent superposition state. A final level, which she described as the quantum-entangled level, involves multiple quantum systems which are entangled among themselves. Overall, the workshop touched on concepts such as superposition, entanglement, and squeezing and their potential implications for communication, computing, and simulation, in addition to the workshop’s main focal area, biological sensing and imaging. At the opening of the workshop, Thorsten Ritz of the University of California, Irvine, identified two questions at the heart of quantum biology: Is the machinery of life quantum mechanical, and can quantum mechanics be used to study the machinery of life in new ways? Participants highlighted systems in which researchers have explored these questions, from the vast array of molecular interactions involved in biological processes such as photosynthesis, to the mechanics involved in cellular functions such as differentiation and aggregation, to the role of oscillating magnetic fields in flight orientation among birds. Sensing and imaging technologies are crucial to biological research; these technologies could both enhance the study of quantum effects and be enhanced by quantum concepts. A critical challenge in biological research is to develop imaging and sensing tools that do not damage or interfere with the often fragile and fleeting systems being studied. Attendees discussed a variety of established and emerging technologies that could enhance noninvasive biological imaging, including single- and two-photon spectroscopy, single-molecule spectroscopy, quantum illumination, ghost imaging, and cryo-electron microscopy. One example came from Marlan Scully who gave a keynote address on the first day of the workshop. Scully emphasized the use of different laser technologies, which exhibit coherence and other quantum properties, in moving toward real-world biological applications, such as the detection of SARS-CoV-2. Both tools and theory will play an important role in advancing quantum biology research and applications. Several participants suggested theorists and experimentalists should work in tandem to understand and model biological processes. While physics often reduces systems to their simplest forms for fundamental insights, participants also noted the value of observing and understanding biological systems in all their “messiness,” capturing both the inner workings of biological systems and the complex interactions that occur within and between organisms. In discussions among participants, several attendees stressed the need to match emerging tools with the right scientific questions. Rather than developing quantum technologies as “a hammer looking for a nail,” participants emphasized a focus on exploring the problems these technologies are best suited to address. For example, it is important to consider the size of the phenomenon being studied, the timescales that are important in answering the scientific question, and other relevant considerations. Every tool along the spectrum from classical to quantum involves its own set of trade-offs. For example, Ted Laurence of the Lawrence Livermore National Laboratory said that quantum measurements, such as single photon counting, fluorescence transitions, and lasers, can take longer to produce the same results as classical measurements. These quantum measurements, however, do not require calibration and can enable new research questions to be answered. Prem Kumar, Northwestern University, noted that, despite their promise, quantum approaches should not be used simply for the sake of using quantum, especially in situations where classical approaches better meet the needs of the researcher. Understanding and applying quantum concepts could enable advances in a wide range of application areas including energy, synthetic biology, medicine, and sustainability. For example, Michelle O’Malley, University of California, Santa Barbara, described how improved noninvasive imaging approaches could help capture the complex interactions and functions involved in the breakdown of organic matter by microbial communities and lead to new technologies for capturing valuable products from plant waste. Several other participants discussed needs in tracking the movement of metabolites and molecules in microbial communities for insights into nutrient cycling in environments such as soil. Margaret Ahmad, Sorbonne University, discussed potential opportunities to leverage the magnetic properties of cryptochromes to advance new treatment approaches for diseases such as COVID-19 and cancer. Looking toward the future development of the field, participants discussed challenges to advancing quantum biology that arise from disciplinary disconnects between physicists and biologists. The siloing of academic research disciplines represents a significant barrier to progress. Disconnects in terminology, motivations and priorities, and structural barriers to collaborative work underscore the need for concerted efforts to bridge these divides. Attendees and speakers offered suggestions for resolving these divergences, establishing a shared language, moving the field forward, and fostering meaningful feedback between disciplines. Overall, participants stressed a need for balance, open communication, collaboration, unity, and clear dialogue on trade-offs between quantum and classical approaches. Keiko Torii, The University of Texas at Austin, said that the best collaborations happen when the project provides mutual advantages that can show off everyone’s talents, each team finds the work interesting, and partners develop a camaraderie to pursue new knowledge. To enable near- and long-term opportunities in this space, participants suggested that exploratory, high-risk funding could improve existing instrumentation to explore quantum enhancement collaboratively. They also emphasized the need for collaboration between quantum physicists and sensing/imaging scientists, which could be advanced through a dedicated quantum biology investigator program. People, even more than technology, will be crucial to the future of quantum biology. Participants explored training, education, and workforce needs to further develop this burgeoning field and cultivate the next generation of scientists. While many programs are still in their nascent stages, participants highlighted examples of approaches and programs being developed at various types of institutions to engage students and professional scientists in quantum biology research. Several participants stressed the need for an inclusive approach, spanning disciplines as well as communities to foster a diverse field fueled by the intellectual contributions of a wide range of people, including historically under-resourced schools and students. To increase awareness and excitement about quantum physics and related areas of biology, attendees suggested capitalizing on the “buzz” around quantum. Several participants emphasized the need to start early, introducing students to quantum concepts and their appealing “weirdness” in K–12 education. Engaging students early—before they become entrenched in traditional disciplinary siloes as typically happens in graduate school—could help to galvanize interest in the area and foster a generation of scientists with the interdisciplinary mindset and skills needed to advance this interdisciplinary field. While these efforts could be advanced at many levels and across multiple sectors, several participants suggested a national quantum biology center could be a valuable hub to coordinate and support quantum biology education and workforce development across academia, industry, and government.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

IACMI Project 4.2: Thermoplastic Composite Development for Wind Turbine Blades

(Section 5.1) Composites made from Arkema’s Elium® thermoplastic resin and Johns Manville fiberglass were researched during this project for applications in wind blade manufacturing. A techno-economic model was developed to model this wind blade manufacturing process using these materials in place of traditional composites made with thermoset resin. This model was based on manufacturing a 61.5-meter wind blade, which showed a 4.7% reduction in wind blade cost as compared traditional thermoset materials. These cost savings were not from the thermoplastic material costing less than traditional thermoset materials, but rather from decreased capital costs, faster cycle times and reduced energy requirements and labor costs. (Section 5.2) An infusion and curing model was developed for thermoplastic composite wind blades using PAM-RTM. The primary goal was to demonstrate the infusion simulation for the Elium® resin system on a 13-meter wind blade. Additionally, the exotherm temperature was predicted and compared to measurements, which showed model results within 10% of actual measurements. (Section 5.3) Composite laminate panels and composite sandwich panels with a balsa core were produced; specimens were cut and characterized. Similar composite specimens were made with Elium® thermoplastic resin and Hexion thermoset epoxy (RIMR135/RIMH1366) to enable comparisons between these resin systems. The static test methods included: tensile, compression, in-plane shear, interlaminar shear, flexural, sandwich core shear flexure, and single cantilever beam tests for sandwich beams. Fatigue testing at room temperature was completed to composite laminate panels at a stress ratio of R=0.1 and R=10. In addition, fatigue testing to laminate panels was completed at -30°C, and at room temperature after conditioning specimens at 70°C and 90% relative humidity. Overall, mechanical test results from Elium® composites are similar to epoxy composites. (Section 5.4) Elium composite panels were produced with intentional defects such as voids and nonwetting of fibers to begin to understand performance sensitivity to defects. A thermal digital image correlation (TDIC) method provides high spatial resolution strain field at elevated temperatures and can be used to identify defective regions within composite panels. Flexural modulus differences of 21% were seen between defect and non-defect panels. Other Elium® composite panels were forced to be defective by boiling the resin after infusion, which created voids throughout the composite laminate. X-ray computed tomography scanning was used to view the internal structure of the defect panels. Defect panels had a significant reduction in fatigue life as compared to baseline panels produced without intentional defects. (Section 5.5) Lap shear specimens were fabricated to compare the lap shear strength of an off-the-shelf adhesive (Plexus MA590) and two new adhesives developed by Arkema (Bostik SAF30 90 and Bostik SAF30 120). ISO standard 4587:2003 was used to standardize the testing method and sample fabrication. Lap shear specimens were made at 1mm, 3mm, and 10mm thicknesses. The Bostik adhesive lap shear test results were similar to Plexus for all thicknesses. (Section 5.6) Fiber-reinforced polymer (FRP) composites are typically used in high-performance applications (e.g., aerospace), and their expansion into high-volume industries (e.g. consumer automotive and wind turbine blade manufacturer or similar) is hindered by their cost and a lack of efficient manufacturing techniques. Monitoring the curing process of these composites during manufacturing can improve the efficiency of the process, and therefore reduce the manufacturing cost. Cure monitoring techniques were developed that use probabilistic estimation methods and surface temperature measurements made using infrared cameras. These techniques enable real-time monitoring of the infusion process to locate manufacturing flaws, and they can, potentially, estimate residual stresses in the part. Their commercialization will help facilitate expansion of FRP composites in high-volume industries. (Section 5.7) A 13-meter composite wind blade was produced with Elium® resin and Johns Manville fiberglass; this blade was made with VARTM processing similar to how megawatt-scale wind blades are currently manufactured, but no post-mold heating was used for this thermoplastic composite blade. The wind blade underwent full-scale validation for static loading (4-different load orientations) and flapwise fatigue loading to simulate 20-years of operational loads. The thermoplastic composite wind blade withstood the loading without any noted issues and performed similar to results from a previous full-scale validation to an equivalent epoxy composite wind blade produced with the same blade molds. (Section 5.8) A study was conducted to determine the feasibility of recycling composite wind turbine blade components fabricated with glass fiber reinforced Elium® thermoplastic resin. Dissolution, which is a process unique to thermoplastic matrices, allows recovery of both the polymer matrix and full-length glass fibers, while maintaining their stiffness and strength throughout the recovery process. The economics of recycling is favorable if 50% of the glass fiber is recovered and resold for a process of $\$$ 0.28/kg, and 90% of the resin is recovered and resold at a price of $\$$ 2.50/kg.(Section 10) Recommendations are outlined for commercializing thermoplastic resin for composite wind blade production, in addition to recommended areas for future research.

17 WIND ENERGY↗
DOE OSTI2022

Aeroelastic Modeling for Distributed Wind Turbines: March 11, 2021 - November 10, 2021

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine whereby providing an understanding of the impact of design parameters on its loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the Distributed Wind Technology (DWT) sector is limited, especially within the less established manufacturers. This project represents an in-depth assessment of the status of AM and its role within the Standards for the DWT industry. The study gathered input and feedback from a large number of national and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed recent industry workshops' and meetings' minutes, collected publicly available AM templates, and provided an evaluation of the existing AM codes. The study achieved several goals including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation (V&V), which includes discussions of measurement requirements and a sample test-plan useful for future V&V campaigns and design standard development. This document summarizes the different tasks conducted in the course of the project and highlights the steps required to improve the AM adoption based on a multifaceted approach that encompasses: 1) augmenting AM software capabilities, 2) publishing AM best-practices and design-basis, 3) creating new model templates, 4) providing guidance for V&V of codes and specific turbine models leveraging field testing best-practice, and 5) addressing weaknesses in the current standards. Many of the future objectives identified in this study could leverage NREL's upcoming testing campaigns of three modern distributed wind turbines. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool resulting in a more efficient design process, an easier path to certification, and overall better and more distributed reliable wind turbine products.

17 WIND ENERGY↗
DOE OSTI2023

Anion exchange membranes: The effect of reinforcement in water and electrolyte

Alkaline anion-conducting polymer-based CO 2 electrolysis and water electrolysis are among two emerging renewable energy conversion technologies. Their system design and integration offer promise of lower capital cost due to utilization of low-cost catalysts, in contrast to platinum group metal catalysts required for cation-conducting polymer-based devices. However, a critical component, the polymer electrolyte membrane, remains an obstacle hampering system performance and durability. In this study, commercially-available Sustainion® membranes with and without PTFE-reinforcement were investigated to understand previously unreported origins of improved device performance when compared to alternative membrane chemistries. We report critical membrane properties, such as morphology, thermal stability, as well as temperature-, hydration-, and counter-ion dependent ion conductivity. Moveover, the changes in uptake and conductivity of membranes in supporting electrolytes of K 2 CO 3 and KOH investigated as a function of their concentration. Presence of reinforcement and supporting electrolyte type alter the membrane's transport functionality, which could help guide device design for improved performance. In conclusion, the obtained results not only show how Sustainion® properties change with operating environment for CO 2 and water electrolysis applications, but also provide understanding for internal and external factors controlling anion-exhcnage membrane functionality in electrochemical devices.

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

Capabilities Development at the University of Texas at El Paso for Hydrogen Generation Research and Education

Gasification-based systems have recently received much attention due to their capability of converting wastes into useful fuels. The gasification of biomass, municipal solid waste (MSW), plastics, and other sustainable resources has shown promise in hydrogen production. When coupled to a CCU or CCS unit, these systems have the potential to achieve carbon neutrality or carbon-negative emissions. In addition, these systems have an edge over conventional incineration or landfill systems by reducing greenhouse gas emissions and recovering useful energy. However, the gasification of MSW and other wastes is still in its early stages. In particular, co-gasification of wastes with biomass has significant unknowns in optimizing the reaction kinetics, operability, design and performance improvements. Currently, Supercritical Water Gasifiers (SCWG) and Plasma Gasifiers are the major systems that are capable of producing high hydrogen amounts from Biomass and MSW, respectively. However, both systems have high capital and operating costs, adversely affecting efficiency and the hydrogen production cost. Additionally, due to lower temperatures, SCWGs are prone to tar formation and fouling in the heat exchangers. Hence, there is a need to look for alternative solutions for MSW and biomass gasifications, particularly in co-gasification. The current effort aims to develop a strategic plan to establish a sustainable gasification facility for hydrogen research at the University of Texas at El (UTEP). A major part of this effort involves an extensive literature survey to identify technological gaps and potential areas of interest. Several concepts were developed in accordance with the current demands from the literature survey. Based on the concepts, a center-wide capability assessment was conducted to measure the current capacity and feasibility of establishing hydrogen research. Afterward, a strategic research plan was developed, and a list of required resources was made for the expansion of hydrogen research at UTEP. In addition, successful partnerships with the local county and the city were developed to pursue hydrogen research. The strategic goal setting and planning of UTEP Aerospace Center resulted in securing $2.5 million in external support to expand the hydrogen research during the project performance period. In addition, during the project period, a course in Hydrogen Energy Systems was developed to expand the energy curriculum at the UTEP Aerospace and Mechanical Engineering Department. The course focused on hydrogen production, storage, supply and delivery and application. The cross-listed course was offered at both undergraduate and graduate levels during the Spring 2024 semester and had 27 enrolled students. Moreover, the students supported under this award were trained in gasification process modeling, CAD, CFD and FEA during the project period. The training enabled the students to move into new projects to support gasification design, integrated gasification combined cycle process plant analysis, gasifier structural and operational analysis, and digitally threading the systems.

08 HYDROGEN↗
DOE OSTI2024

Leveraging Existing Assets for Long Duration Energy Storage

Increased renewables penetration to electrical grid is necessary to reduce overall emissions from the electrical power generation sector. Nonetheless, its integration creates challenges to grid operators who must match the power being generated by intermittent renewables and other traditional energy sources with the demand from consumers, while ensuring the reliability and power quality for the entire system. Energy storage has been proposed as an alternative to natural gas peaking plants and a form to deliver excess renewable energy generation at times of peak demand. For energy storage to provide benefits to end customers (energy consumers), it must be reliable, efficient, and cost effective. The Illinois Sustainable Technology Center (ISTC), one of the surveys that integrate the Prairie Research Institute (PRI), aims to develop a Center for Energy Storage at Existing Assets (CESEA) at UIUC with the participation of Waste Pressure Corp and Ecotek Engineering USA LLC. CESEA will focus on LDES systems that can integrate to existing infrastructure in a manner that reduces the initial capital expenditure and demonstrates the ability to repurpose fossil assets that would otherwise become stranded, to serve the energy transition. CESEA aims to leverage UIUC’s unique facilities to validate LDES systems performance at a relevant operating environment. UIUC’s facilities include a 85-MW combined heat and power (CHP) power plant, two (2) solar PV plants totaling over 18 MWdc of installed capacity, an electrical grid along with a substation at transmission and distribution voltages, a 22-mile gas pipeline network operating at two pressure levels, along with steam and chilled water distribution networks. The new LDES systems will connect to the existing UIUC grid through a new test electrical station, which will have the capacity to accommodate additional connections to test new devices and technologies as part of future CESEA R&D activities. The test electrical station will contain meters, instrumentation, and controls to accurately capture data and allow optimization of control algorithms. CESEA will initially focus on technologies that: i) utilize existing equipment or facilities to perform at least one of the process steps in LDES (charging, storage, or discharging), ii) leverage mature or commercially available components or controls, iii) show potential for cost-leadership in 10+ hour storage at a commercial scale. Initial technologies that were identified to meet these criteria include Compressed Gas Energy Storage (CGES), and TES. CGES stores electricity by raising the pressure of a compressible gas inside a control volume and converting the stored energy to electricity via expansion-generation. CGES is a generalization of CAES that covers any working gas (not just air). A successful CGES demo will help to circumvent many challenges faced by CAES (long development times due to site prospecting, high cost of compression and storage, heat recovery management, etc.) by: 1) utilizing existing infrastructure (compressors, pipelines, underground storage or pressure vessels) used in the transportation and storage of industrial gases for LDES charging and storage; 2) deploying over sites already-developed for industrial applications with minor additional work; 3) leveraging the price structure of commercial industrial gas to cover the costs of electricity used during charging. A previous DOE-sponsored conceptual study (DE-FE-0032018) estimated the levelized cost of energy of a 1.1 MW / 17 MWh CGES system at $0.08/kWh, with a commercial 10x scale system cost estimated at <$0.04/kWh (Giardinella, 2022). The pilot-sized system was estimated to avoid up to 2693 tons of CO2/year.

25 ENERGY STORAGE↗