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At least 55 records · Page 3

National Energy Education Development Project (NEED Project) (CRADA Final Report)

The U.S. Department of Energy Building Technologies Office (BTO) funds student competitions that introduce students to careers in the building sciences and increase public awareness around high-performance buildings to support the goal of developing, demonstrating, and accelerating the adoption of cost-effective technologies, techniques, tools, and services that enable high-performing, energy-efficient and demand-flexible residential and commercial buildings in both the new and existing buildings markets. The U.S. Department of Energy Solar Decathlon® (DOE/SD) is a flagship, high-visibility international competition started in 2002 that advances the goals of BTO by introducing students to building science careers; educating students and the public about the latest technologies and materials in high-performance buildings; encouraging student-led projects and research centered around building science; and demonstrating to the public the comfort and savings of homes that combine energy-efficient construction, home systems, appliances and innovative design with onsite renewable energy production. SD is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. Solar Decathlon is comprised of two Challenges – Design Challenge (annual) and Build Challenge (biennial). The National Renewable Energy Laboratory (NREL) provides competition management for Solar Decathlon. NREL and Participant establish this CRADA to enable the success of the overall Solar Decathlon program by managing sponsorship funds and creating a K12 education program. Participant is to act as an Education Partner to Solar Decathlon, which includes: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing K12 education program to support Solar Decathlon Competition Events in April each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integration of a real-time orientation measurement system for a real-time evaluator (RTE) to measure the position and orientation of crane-lifted components

Prefabrication of building components holds the potential to revolutionize the construction industry. Prefabrication consists of manufacturing building components, modules, and other elements in a factory to be shipped and installed on a construction site. Prefabricated components have been produced for various applications including precast concrete panels for new construction and exterior wall retrofits. The manufacturing process has seen much innovation in recent years; however, the installation process has seen minimal advancements. A real-time evaluator (RTE) was developed to reduce the installation cost of prefabricated components by reducing installation time, decreasing rework, and improving accuracy. The RTE uses off-the-shelf hardware and novel algorithms to assist erectors with component installation by measuring the real-time positions of connections and prefabricated components, providing installation guidance through a graphical user interface, and monitoring the accumulated installation errors. An overview of the RTE and the proposed workflow is presented. Previous on-site demonstrations provided valuable feedback from users on the potential areas for improvement of the system. One common request was real-time measurement of component orientation during lifting, a process that previously required that the component remain stationary while the laser tracker cycled through target prisms. This paper will present the incorporation and testing of a real-time orientation measurement system as it was implemented into the RTE, allowing for measurement of component orientation during movement.

Selvakumar, Balaji [ORNL]↗

LAMP DTL Scoping Studies (Technical Report)

The present studies are based on the preliminary design efforts, and on the Scoping Studies of the “Strawman” design of LAMP front-end upgrade, referred in the text below to as “Feb.2024 Iteration”, presented in. The main accomplishment of present studies was substantial increase of the fidelity of the beam dynamics simulations in the proposed drift tube linac (DTL). The main accent was on development of the methodology for calculation of the longitudinal (synchrotron) and transverse (betatron) oscillations frequencies (phase advance per focusing period) values and providing the accelerating structure focusing lattice that has safe parameters of such oscillations to avoid unwanted emittance growth and possible beam halo formation. The resulting values of the oscillations phase advances are presented in Table 1, and in Figure 5 in the main body of the report. Special efforts were made to achieve the RF power consumption within limits of the existing RF power system and make sure that DTL fits in the existing tunnel. The LAMP scope does not suggest any additional building and/or tunnel construction. Table 1 summarizes some of these results, as well as Table 3 in the main body of the report.

43 PARTICLE ACCELERATORS↗

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Characterization and Analytical Technique↗

Future Opportunities for LWR Irradiations in US Test Reactors

After several years of relatively low activity in the field of Light Water Reactor (LWR) fuel development, the Department of Energy again began to engage in developing new fuel technologies and irradiation performance data prompted by the Fukushima Daichi nuclear accidents. New competencies for irradiation testing in material test reactors in the United States began to be developed at this time using the Advanced Test Reactor (ATR), High Flux Isotope Reactor (HFIR), Massachusetts Institute of Technology Reactor (MITR), and the Transient Reactor Test Facility (TREAT). Capsules for testing fuel and cladding materials in ATR and HFIR were deployed, a Pressurized Water Reactor (PWR) condition loop for testing fuel rods was established in ATR, cladding corrosion studies were performed using a water loop in MITR, and TREAT pulse testing capabilities were commissioned for fuel rods in water capsules. The more recent and unexpected closure of the Halden Boiling Water Reactor (HBWR) also prompted further investments in Loss of Coolant Accident (LOCA) testing capabilities at TREAT. New configurations of these test devices show further potential in enhanced steam condition control and other investigations are building toward a flowing water loop for testing transient to dryout conditions. The closure of HBWR also prompted a major project currently underway to construct additional water loops in ATR where a novel approach is being pursued to enable Boiling Water Reactor (BWR) conditions. A meaningful collaborative project was awarded to MITR which, amidst an unexpected major overhaul of the reactor, has expanded cladding corrosion test capabilities at MITR. New explorations have led to methods for unique experiments at HFIR including channel box irradiations. New device developments are also bridging toward future potential for instrumented capsule irradiation tests in ATR and HFIR. Finally, a new project referred to as the System Physics Advanced Reactor Critical facility (SPARC) is gaining traction towards a large zero-power reactor able to produce physics validation data for LWR fuel bundle designs with increased enrichment and enhanced absorbers for 24-month operation cycles. This paper provides a brief summary of the status of these irradiation testbed capabilities with an emphasis on current efforts toward future capabilities to obtain new data and maximize the performance potential of LWR fuel technologies.

Woolstenhulme, Nicolas [Idaho National Laboratory ↗

Fuel‐Driven π‐Conjugated Superstructures to Form Transient Conductive Hydrogels

Despite advances in creating dissipative materials with transient properties, such as hydrogels and active droplets, their application remains confined to temporal changes in structural properties. Developing out-of-equilibrium materials whose electronic functions are parameterized by a chemical reaction cycle is challenging. Yet, this class of materials is required to construct biomimetic materials. In contrast to traditional chemical reaction cycles that exploit molecularly dissolved building blocks at thermodynamic equilibrium, we show that fiber structures derived from reactive naphthalene diimide (NDI) building blocks can be used as resting states to form far-from-equilibrium conductive hydrogels after the addition of chemical fuels. Upon fueling the NDI-derived fibers, a dual-component activation and deactivation pathway is deduced by kinetic analysis and is absent when using a molecularly dissolved resting state. Investigating the solid-state morphologies of the structures formed throughout the fuel-driven reaction cycle using cryo-EM reveals that the resting thermodynamic fibers evolve to transient thicker fibrils and layered superstructures. We show that the transient redox-active hydrogels exhibit a nearly threefold increase in electrical conductivity upon fuel consumption before reverting to their original value over hours. In conclusion, these far-from-equilibrium materials are potential candidates in applications such as programmable biorobotics and chemical computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗

A Permanently Porous Chalcogen-Bonded Organic Framework

The nature of connectivity between constituent atomic or molecular building blocks is fundamental in shaping the properties and functionality of materials. The extrapolation of emergent interatomic interactions to enable functional materials has driven transformative technological advancements. However, the bonding interactions used in material design have been largely static since the emergence of dynamic covalent chemistry ~30 years ago. Here we demonstrate that non-covalent chalcogen bonding (Ch-bonding) is a distinct mode of interatomic connectivity for constructing functional materials by design. This is established by leveraging self-complementary assembly of 1,2,5-telluradiazole moieties to construct a honeycomb-type permanently porous Ch-bonded organic framework, assembled and stabilized solely through non-covalent Te...N contacts. Empirical and computational studies of electronic structure, structural healing and lattice dynamics highlight the pi-type electronic communication, controlled assembly and modulated lattice dynamics in Trip3Tez-I arising directly from the unique nature of the Te...N Ch-bonding that holds substantial implications for next generation crystalline semiconductors. In addition to introducing a distinct class of permanently porous frameworks, this work establishes Ch-bonding as a programmable molecular tool for constructing functional materials with distinct properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Extremely Scalable Distributed Computation of Contour Trees via Pre-Simplification

Contour trees offer an abstract representation of the level set topology in scalar fields and are widely used in topological data analysis and visualization. However, applying contour trees to large-scale scientific datasets remains challenging due to scalability limitations. Recent developments in distributed hierarchical contour trees have addressed these challenges by enabling scalable computation across distributed systems. Building on these structures, advanced analytical tasks—such as volumetric branch decomposition and contour extraction—have been introduced to facilitate large-scale scientific analysis. Despite these advancements, such analytical tasks substantially increase memory usage, which hampers scalability. In this paper, we propose a pre-simplification strategy to significantly reduce the memory overhead associated with analytical tasks on distributed hierarchical contour trees. We demonstrate enhanced scalability through strong scaling experiments, constructing the largest known contour tree—comprising over half a trillion nodes with complex topology—in under 15 minutes on a dataset containing 550 billion elements.

Li, Mingzhe [University of Utah]↗

Measuring changes in environmental radiological background from construction of an advanced nuclear reactor testing facility

We present a method to survey and track changes in the environmental radiological background during the construction and operation of advanced nuclear reactor facilities. We discuss the results of two surveys of the environmental gamma-radiation background at NEXT Lab, an advanced nuclear reactor research facility on the campus of Abilene Christian University, prior to the introduction of radioactive material. In both surveys, the observed radiation dosage rates are low, with the highest rates at 15% of the average total radiation dosage rate for the United States. We observe ≈20% changes in the radiological background of the property in locations where the environment was changed by construction and ≈20% variations within the facilities correlated with variations in building materials.

Environment↗

Machine Learning Based Metamodel for Faster Life Cycle Assessment of Large Portfolio of Buildings

Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision

Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape cosmic evolution. This whitepaper presents a vision for how Artificial Intelligence (AI) can accelerate discovery in this field. We outline grand challenges that must be addressed to enable transformative breakthroughs and describe how current and planned experimental facilities can implement this vision to advance our understanding of the vast and complex physical world from the smallest to the largest scales. We show how facilities currently under construction, such as the HL-LHC, DUNE and soon EIC, can both benefit from and serve as proving grounds for this vision, while also enabling a longer-term goal for how future experiments -- like FCC-ee at CERN, IceCube-Gen2, a Muon Collider in the U.S., and smaller to mid-scale projects -- can be fully AI-native. We describe how a truly national-scale collaboration, jointly managed across large funding partners, and involving both DOE laboratories and universities, can make this happen.

Aarrestad, Thea Klaeboe [ETH, Zurich (main)]↗

Engineering microalgal cell wall-anchored proteins using GP1 PPSPX motifs and releasing with intein-mediated fusion

AbstractHarnessing and controlling the localization of recombinant proteins is critical for advancing applications in synthetic biology, industrial biotechnology, and drug delivery. This study explores protein anchoring and controlled release inChlamydomonas reinhardtii, providing innovative tools for these fields. Using truncated variants of the GP1 glycoprotein fused to the plastic-degrading enzyme PHL7, we identified the PPSPX motif as essential for anchoring proteins to the cell wall. Constructs with increased PPSPX content exhibited reduced secretion but improved anchoring, pinpointing the potential anchor-signal sites of GP1 and highlighting the distinct roles of these motifs in protein localization. Building on the anchoring capabilities established with these glycomodules, we also demonstrated a controlled release system using a pH-sensitive intein derived from RecA fromMycobacterium tuberculosis. This intein efficiently cleaved and released PHL7 and mCherry that was fused to GP1 under acidic conditions, enabling precise temporal and environmental control. At pH 5.5, fluorescence kinetics demonstrated significant mCherry release from the pJPW4mCherry construct within 4 hours. In contrast, release was minimal under pH 8.0 conditions and negligible for the pJPW2mCherry (W2) control, irrespective of the pH. Additionally, bands on the Western blot at the expected size of mCherry also showed its efficient release from the mCherry::intein::GP1 fusion protein at pH 5.5. Conversely, at pH 8.0, no bands were detected. This anchor-release approach offers significant potential for drug delivery, biocatalysis, and environmental monitoring applications. By integrating glycomodules and pH-sensitive inteins, this study establishes a versatile framework for optimizing protein localization and release inC. reinhardtii, with broad implications for proteomics, biofilm engineering, and scalable therapeutic delivery systems.Graphical Abstract

Kang, Kalisa (ORCID:0009000619398129)↗

Coupled Aerodynamic and Hydrodynamic Hybrid Simulation of Floating Offshore Wind Turbines

The development and innovation of floating offshore wind energy in the U.S. requires detailed high-fidelity observations and measurements of turbine and platform loading due to wind, waves, and currents. However, full-scale and quasi-full-scale experiments require significant financial and temporal investments for construction, experimental testing, and long-term field campaigns. To support the commercial advancement of the offshore wind energy industry, specialized wind tunnel and wave basin experimental facilities are critical to be able to test FOWT designs at small scale under controlled conditions prior to full-scale deployment. Oregon State University (OSU) is internationally known as a leader in water and energy research, development, and testing. The O.H. Hinsdale Wave Research Laboratory (HWRL) and the Wallace Energy Systems and Renewables Facility (WESRF) at OSU have extensive experience building, modeling, monitoring, controlling, and actuating scaled systems. Experiments on wave-structure interaction have been performed at the HWRL since its establishment in 1972. Studies have included the interaction of waves with coastal structures (breakwaters, seawalls, buildings, cylinders, bridges, fixed foundations of offshore wind turbines, etc.) and with floating structures (e.g., wave energy converters, maneuvering of vessels, etc.). Hinsdale is actively used by marine energy technology developers, both for private testing and OSU-collaborative research projects. However, despite the availability of several large-scale facilities for hydrodynamic testing (at OSU and elsewhere in the U.S.), existing experimental laboratories are generally limited in their ability to accurately generate combined wind and wave conditions. The simulation of both wind and waves in experimental testing is complicated due to a number of constraints, including: [i] incompatible similitude laws governing the wind and waves for scaled experiments, [ii] producing accurate wind over a large enough control volume via fans, and [iii] generating wind that reasonably represents the atmospheric boundary layer in existing wave basins/flumes. Hence, physical test data providing insight into the simultaneous wave- and wind-structure response of floating offshore wind components can be difficult to generate. Given the aforementioned challenges in classic hydrodynamic experiments, the motivation of this project is to establish a real-time hybrid simulation (RTHS) approach that can apply aero- and hydro-dynamic loading by augmenting wave-only experimental facilities with virtual aerodynamic forces through numerical models representing the remaining dynamic forces. RTHS is a physical-numerical approach that partitions a prototype system into physical and numerical sub-assemblies that interact with each other through actuators and sensors in real time. In coupling physical and numerical models, the hybrid simulation approach applied herein is ideal for problems with: (1) structures subjected to different scaling laws, such as floating offshore wind turbines subjected to combined aero/hydro-dynamic loading, (2) structures that are too large or complex to be tested entirely in a laboratory setting, such as deep-water mooring applications, and (3) component testing, where the behavior of a portion of the assembly is uncertain but still interacts with other portions of the structure, such as testing the fatigue life of turbine blades. Few U.S. experimental facilities are able to test simultaneous aero- and hydro-dynamic loading and none can accurately produce aero/hydro-dynamic response on scaled FOWT models due to conflicting similitude laws between the wind (commonly Reynolds) and the waves (commonly Froude). To aid in accelerating the development of the U.S. floating offshore industry, there is a significant need to develop a flexible, modular framework that can expand the capacities of existing wave-only laboratories. The project goal is to demonstrate a hydrodynamic real-time hybrid simulation (hydro-RTHS) framework that couples numerical wind and physical waves acting on a FOWT, thus representing simultaneous aero/hydro-dynamic loading. The FOWT is partitioned into a full-scale numerical sub-assembly associated with the aerodynamics and a model-scale physical sub-assembly associated with the hydrodynamics. The numerical-physical partition associated with hydro-RTHS mitigates scaling constraints by supplying different scaling laws to the physical and numerical sub-assemblies. Herein, length, force, and time are scaled and exchanged between the sub-assemblies using Froude scaling to represent the open-channel flow in the physical sub-assembly. Other similitude laws could also be utilized depending on the problem definition. It is envisioned that the ability to model FOWTs under waves and wind, with mitigation of similitude distortions, would result in reduced development costs (currently, FOWT concept development is performed with full-size pro- totypes at enormous expense and risk) and increase the reliability of the FOWT industry (since extreme wave and wind conditions and contingency events can be tested safely in a controlled environment).

16 TIDAL AND WAVE POWER↗

Meta-Analysis of Advanced Nuclear Reactor Cost Estimations

Supporting Data can be downloaded at: https://gain.inl.gov/content/uploads/4/2024/06/INL-RPT-24-77048-R1.xlsx Nuclear energy is a critical cornerstone of the current United States clean energy supply and may play a larger role in the future in support of a transition to a net-zero economy. The current fleet of nuclear reactors predominantly consists of large light-water reactors (LWRs), while many of the reactor designs under consideration are smaller and/or different technologies. Because these new designs have not yet been built, there is a high degree of uncertainty associated with their cost. This complicates energy-planning efforts because cost projections are not always standardized, consistent, and centralized in an easily accessible location. To help support energy planning in the US, this report provides advanced nuclear cost ranges using a transparent methodology along with other relevant information that can be used to help support decision making and energy planning. The purpose of this work was to conduct a methodical process for cost evaluation using only public information that was vetted with the end-goal to provide reference cost projections for nuclear energy. To provide a solid basis for these values, the approach and assumptions are explicitly laid out throughout the report allowing any user of the data to challenge or reconsider them. Because future US nuclear-reactor costs are still unknown due to little recent observed data, the report opted to compile a comprehensive list of bottom-up estimates and evaluate averages/trends within the data to identify reference ranges. This was deemed preferable to opining on the robustness or validity of one cost estimation versus another. To that end, the work evaluated thousands of lines of cost subaccounts from several bottom-up cost estimates. A wide variety of different reactor types captured in the data are of various sizes and technologies. Some of these reactors will be representative of advanced reactors under development while others will not. Thus, the results here are dependent on the data that are available and the accuracy of the estimates that are used. Each bottom-up estimate was reviewed to determine whether it was complete. Incomplete data sets were corrected to ensure an adequate basis of cross-comparison. The report is not without limitations and should be interpreted as an initial step to develop cost ranges for nuclear technology. Ultimately, future work can build upon the methodology with refined cost estimates to reduce uncertainty. US-based overnight capital cost (OCC) estimates were compiled from extensive data sets into ranges for both large and small reactor sizes for 2030. To project the cost declines over time, learning rates were sampled from literature sources. No SMRs were previously built; hence, learning rates based on bottom-up approaches (e.g., by quantifying the impact stemming from fabrication of different components, modular work, site construction, commissioning) were prioritized. For larger reactors, actual learning rates from deployments were used to project future costs (adjusted to account for standardization or lack thereof between designs). Other costs included are fixed and variable operations and maintenance costs. The final variables were capacity factors and ramp rates to support energy planning.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Furthering Advancements to Shorten the Time (FAST) to Commissioning for Pumped Storage Hydropower (PSH) Prize: Cooperative Research and Development (Final Report)

The National Renewable Energy Laboratory initiated a Prize with support from Argonne National Laboratory (ANL), Oak Ridge National Laboratory (ORNL), and Pacific Northwest National Laboratory (PNNL), and sponsored by the U.S. Department of Energy Water Power Technologies Office (DOE WPTO) to encourage ideas to reduce the time to commissioning for PSH projects. As a result, nine finalists have been chosen to develop their concepts in advance of the FAST Prize Pitch Contest to be held on October 7, 2019. The National Labs will provide technical and business advisement to the noted FAST Prize finalists in preparation for this Pitch Contest.

16 TIDAL AND WAVE POWER↗

Environmentally Friendly Use of Carbon Ore for Advanced Building Materials for Homes and Commercial Buildings

Through this effort, X-MAT CCC sought to confirm the utility and commercialization potential of carbon-derived building materials (CDBM) technology licensed from our partner, Semplastics. These CDBM products contain at least 52% coal-derived carbon by mass. Including the binders within the resin, the products contain at least 71% carbon by mass overall, meeting a key criterion for DE-FOA-0002185 – Area of Interest (AOI) 5 – Design Research and Development, Validation, and Fabrication of a Prototype Carbon-Based Building. The Phase II project has resulted in a technology demonstrator prototype structure, a detailed design for a carbon-based building, and updated techno-economic analysis (TEA) including detailed market surveys to show the commercial viability of CDBM products. We pursued the following objectives in Phase II: (1) construction of a partial building shell as a technology demonstrator, (2) testing of CDBM products, individually and in assemblies, (3) demonstration of bonding of CDBM and traditional building materials (TBM) in structural applications, (4) production of a detailed design for a carbon-based building, and (5) an update of the TEA that was performed in Phase I. In Phase II, X-MAT CCC and our industry team performed the development and testing needed to improve the maturity of the technology from a Technology Readiness Level (TRL) of 5 to TRL 6. CDBM have been shown by our partner Semplastics to exhibit a number of high-performance characteristics, including high strength (five times the flexure strength of the best commercial brick, and more than twice the compressive strength of construction-grade concrete block), lower density, improved mechanical durability and abrasion resistance, very high temperature stability, and resistance to chemicals, acids, salts, and water. These properties offer significant improvements over conventional building materials. Phase II built upon the work accomplished in Phase I by performing technical and economic research and development to confirm the viability of CDBM as commercial products in various markets. Acknowledgment: This material is based upon work supported by the Department of Energy under Award Number DE-FE0031985.

01 COAL, LIGNITE, AND PEAT↗

Predictive CRISPR-mediated gene downregulation for enhanced production of sustainable aviation fuel precursor in Pseudomonas putida

CRISPR interference (CRISPRi) has emerged as a valuable tool for redirecting metabolic flux to enhance bioproduction. However, its application is often constrained by two challenges: (i) rationally identifying effective gene targets for downregulation and (ii) efficiently constructing multiplexed CRISPRi systems. In this study, we address both challenges by integrating a computational prioritization tool with a versatile assembly method for building multiplexed CRISPRi systems. FluxRETAP (Flux-Reaction Target Prioritization) accurately identified gene targets whose knockdown led to substantial increase of isoprenol titers in Pseudomonas putida KT2440, outperforming a conventional non-computational, pathway-guided target selection. The highest isoprenol titer of nearly 1.5 g/L was achieved by knocking down PP_4118 (a gene encoding α-ketoglutarate dehydrogenase). The use of VAMMPIRE (Versatile Assembly Method for MultiPlexing CRISPRi-mediated downREgulation) enabled accurate assembly of CRISPRi constructs containing up to five sgRNA arrays, reducing context dependency and achieving uniform, position-independent gene downregulation. The integration of FluxRETAP and VAMMPIRE has the potential to advance metabolic engineering by rapidly identifying CRISPRi-mediated knockdowns and knockdown combinations that enhance bioproduction titers, with potential applicability to other microbial systems.

CRISPR interference↗