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All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Lunar Surface Cargo Offloading Concepts

A sustainable presence on the lunar surface will serve as a vital training ground and technology demonstration test site in preparation for future human missions to Mars. Robotic lunar surface campaigns will focus on the exploration of resources providing information on the availability and extraction of usable resources, such as oxygen and water, and prepare the surface for a sustained human presence. Landers, outfitted with sensor packages, will be used to conduct risk-reduction activities and aid in the development of technologies prior to the crewed lunar missions that drive the need to for a logistics supply chain that requires offloading. A series of landers will be required on other planetary surfaces to build up the capabilities, capitalizing on those resources, required for sustained human presence. In each of those landers will be cargo including ascent vehicles, habitats, supplies, science packages, spare parts, fluids commodities for fuel and life support, and others varying in volume and ranging from mass in hundreds of kilograms to an estimated 6-14 metric tons to support Human Landing Systems and surface logistics requirements. This paper will examine the challenge of offloading examples of these cargo elements from different categories of landers on the lunar surface using a variety of methodologies. Challenges on the lunar surface arise with the conditions present (thermal, lighting, communications, regolith consistency), the desire to minimize mass of all landed systems, the desire to perform much of the activities with limited to minimal human interaction, and the overall configuration of the landers that are responsible for landing the cargo.

Lunar↗

NASA NTRSDate not supplied

Lunar Surface Cargo Offloading Concepts

Lunar↗

NASA NTRS2023

Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) in Support of Plant-Growth Systems

As the National Aeronautics and Space Association (NASA) begins to pursue long-duration space flights, they will need to be able to provide astronauts with a nutritious and reliable food source. To meet the administration’s goal of traveling to the Moon and Mars, astronauts will need to begin to grow their own food in space. To protect their food source, extensive monitoring will occur to test for the effects of a space flight environment (e.g., radiation) as well as for early pathogen and disease detection. Genomic sequencing allows for both concerns to be tested on a regular basis. However, NASA’s current sequencer is unable to process plant tissues. Therefore, a novel method for plant DNA extraction using microneedle (MN) patches that will be able to feed into NASA’s existing system, but also require minimal human input is proposed. To support this, the design was broken down into four components (1) MN patch fabrication (2) MN patch extraction, (3) automated sampling motion control, and (4) a processing module. The MN patch is fabricated using a custom mold with conically shaped needles. The mold is filled with Polyvinyl alcohol (PVA) solution and placed in a vacuum desiccator. The mold is left in the vacuum overnight until the patch is dry and ready for use. The protocol was tested with varying pressures, drying times, volume amounts, and preparation methods to determine if highquality needles can be produced. A MN is a method of DNA extraction where the patch is applied to a leaf, the needles penetrate the leaf, breaking the rigid plant cell wall to isolate the DNA. A protocol for this method of extraction was tested to ensure the patch could produce the needed yield and purity. The tests varied by the number of patches, number of applications, and plant type. To automate the MN extraction method, motion control will utilize two separate axis tables which move in the x and y directions. The y-axis table will have an end effector that fits a MN patch and will have the ability to apply the patch to the leaf sample. This end effector will also act as a lid for a downstream processing module. The other axis will position the leaf sample and processing container so that the patch can be applied accurately. The Joint Comprehensive Sequencing System (JCSS) module integrates all the components together. The output of this module feeds into the NASA Charged Information-Storage Polymer Preparation System (CHIPPS) for genomic sequencing. The extraction module operates using a series of syringes and tubing to pump the varying reagents needed for the extraction protocol. The results of the study proved that MN patches are a viable method of DNA extraction. While fabrication of high-quality needles was unsuccessful, the protocol was able to be further developed using centrifugation. The integrated design between the motion control and the JCSS enabled the potential for automation with a complete conceptual design and prototype. Future research and development for this study would include (1) further testing for fabrication (2) expanding the range of plant species compatible with the MN patch, and (3) building a working prototype for the integrated system.

Peter Ling↗

DOE OSTI2021

Polyelectrolyte Complex Coacervation across a Broad Range of Charge Densities

Polyelectrolyte complex coacervates of homologous (co)polyelectrolytes with a near-ideally random distribution of a charged and neutral ethylene oxide comonomer were synthesized. The unique platform provided by these building blocks enabled an investigation of the phase behavior across charge fractions 0.10 ≤ f ≤ 1.0. Experimental phase diagrams for f = 0.30–1.0 were obtained from thermogravimetric analysis of complex and supernatant phases and contrasted with molecular dynamics simulations and theoretical scaling laws. At intermediate to high f, a dependence of polymer weight fraction in the salt-free coacervate phase (w P,c ) of w P,c ~ f 0.37±0.01 was extracted; this trend was in good agreement with accompanying simulation predictions. Below f = 0.50, w P,c was found to decrease more dramatically, qualitatively in line with theory and simulations predicting an exponent of 2/3 at f ≤ 0.25. Preferential salt partitioning to either coacervate or supernatant was found to be dictated by the chemistry of the constituent (co)polyelectrolytes.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Review of In Situ Sensing for Directed Energy Deposition for Industrial Part Quality Assessment

As the use additive manufacturing (AM) processes continues to grow in critical industries, improved quality assurance methods are becoming increasingly sought after for qualification and certification of AM components. Traditional nondestructive evaluation of printed components is often unable to supply the required confidence in print quality to justify qualification and certification, but the layer-by-layer nature of AM provides unprecedented opportunities for in situ quality inspection. This document summarizes recent developments in process monitoring research specifically related to Directed Energy Deposition (DED). Particular attention is given to three aspects of the highlighted manuscripts: (1) the type of sensors used, (2) features extracted from each sensor modality, and (3) analysis of extracted features for AM quality assessment. Based on the review of the state-of-the-art, several observations have been made. First, none of the reviewed works have applied their trained models to real part geometries, with many of the works relying on single track experiments, thin-walled structures, and cubes. Similarly, there have not been any works demonstrating model generalizability, i.e., a model trained on data from one build allows for fruitful analysis of data from another build. Many works used machine learning techniques to distinguish different process regimes (i.e., normal, keyholing, lack-of-fusion), but very few papers have investigated stochastic variation in an already “optimized” process. Sensor fusion approaches are also limited in the DED sensing literature, but the few works that have employed such techniques have demonstrated the benefits. Finally, registration of in situ data to the build coordinate system is of paramount importance to producing industrially relevant in situ monitoring systems. Data registration allows direct correlations between process anomalies detected in the process monitoring data to localized departures in part quality, but such techniques are generally lacking in the current literature.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Threat Reduction Research Networks: Fostering Sustainable Collaborations Through Trainings for Genomics for Biosurveillance

Scientific research communities can be represented as heterogeneous or multidimensional networks encompassing multiple types of entities and relationships. These networks might include researchers, institutions, meetings, and publications, connected by relationships like authorship, employment, and attendance. We describe a method for efficiently and flexibly capturing, storing, and extracting information from multidimensional scientific networks using a graph database. The database structure is based on an ontology that captures allowable types of entities and relationships. This allows us to construct a variety of projections of the underlying multidimensional graph through database queries to answer specific research questions. We demonstrate this process through a study of the U.S. Biological Threat Reduction Program (BTRP), which seeks to develop Threat Reduction Networks to build and strengthen a sustainable international community of biosecurity, biosafety, and biosurveillance experts to address shared biological threat reduction challenges. Networks like these create connectional intelligence among researchers and institutions around the world, and are central to the concept of cooperative threat reduction. Our analysis focuses on a series of seven BTRP genome sequencing training workshops, showing how they created a growing network of participants and countries over time, which is also reflected in coauthorship relationships among attendees. By capturing concept and relationship hierarchies, our ontology-based approach allows us to pose general or specific questions about networks within the same framework. This approach can be applied to other research communities or multidimensional social networks to capture, analyze, and visualize different types of interactions and how they change over time.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1974

Multispectral scanner data applications evaluation. Volume 1: User applications study

A six-month systems study of earth resource surveys from satellites was conducted and is reported. SKYLAB S-192 multispectral scanner (MSS) data were used as a baseline to aid in evaluating the characteristics of future systems using satellite MSS sensors. The study took the viewpoint that overall system (sensor and processing) characteristics and parameter values should be determined largely by user requirements for automatic information extraction performance in quasi-operational earth resources surveys, the other major factor being hardware limitations imposed by state-of-the-art technology and cost. The objective was to use actual aircraft and spacecraft MSS data to outline parametrically the trade-offs between user performance requirements and hardware performance and limitations so as to allow subsequent evaluation of compromises which must be made in deciding what system(s) to build.

Thomson, F. J.↗

NASA NTRS2012

Remediation Technologies Eliminate Contaminants

All research and development has a story behind it, says Jacqueline Quinn, environmental engineer at Kennedy Space Center. For Quinn, one such story begins with the Saturn 1B launch stand at Kennedy and ends with a unique solution to a challenging environmental problem. Used in a number of Apollo missions and during the Skylab program, the Saturn 1B launch stand was dismantled following the transition to the Space Shuttle Program and stored in an open field at Kennedy. Decades later, the Center s Environmental Program Office discovered evidence of chemicals called polychlorinated biphenyls (PCBs) in the field s soil. The findings were puzzling since PCBs a toxin classified as a probable carcinogen by the Environmental Protection Agency (EPA) have been banned in the United States since 1979. Before the ban, PCBs were commonly used in transformer oils that leached into the ground when the oils were changed out and dumped near transformer sites, but there were no electrical transformers near the dismantled stand. It soon became apparent that the source of the PCBs was the launch stand itself. Prior to the ban, PCBs were used extensively in paints to add elasticity and other desirable characteristics. The PCB-laden paint on the Saturn 1B launch stand was flaking off into the field s soil. Nobody knew there were PCBs in the paint, says Quinn, noting that the ingredient was not monitored carefully when it was in use in 1960s. In fact, she says, the U.S. EPA was not even established until 1970, a year after Neil Armstrong first set foot on the Moon. Nobody knew any better at the time, Quinn says, but today, we have the responsibility to return any natural environmental media to as close to pristine a condition as possible. Quinn, fellow engineer Kathleen Loftin, and other Kennedy colleagues already had experience developing unprecedented solutions for environmental contamination; the team invented the emulsified zero-valent iron (EZVI) technology to safely treat groundwater tainted by chlorinated solvents once used to clean rocket engine components. The award-winning innovation (Spinoff 2010) is now NASA s most licensed technology to date. PCBs in paint presented a new challenge. Removing the launch stand for recycling proved a difficult operation; the toxic paint had to be fully stripped from the steel structure, a lengthy and costly process that required the stripped paint to be treated before disposal. Noting the lack of efficient, environmentally friendly options for dealing with PCBs, Quinn and her colleagues developed the Activated Metal Treatment System (AMTS). AMTS is a paste consisting of a solvent solution containing microscale particles of activated zero-valent metal. When applied to a painted surface, the paste extracts and degrades the PCBs into benign byproducts while leaving the paint on the structure. This provides a superior alternative to other methods for PCB remediation, such as stripping the paint or incinerating the structure, which prevents reuse and can release volatized PCBs into the air. Since its development, AMTS has proven to be a valuable solution for removing PCBs from paint, caulking, and various insulation and filler materials in older buildings, naval ships, and former munitions facilities where the presence of PCBs interferes with methods for removing trace explosive materials. Miles of potentially toxic caulking join sections of runways at airports. Any of these materials installed before 1979 potentially contain PCBs, Quinn says. "This is not just a NASA problem," she says. "It s a global problem."

Source record↗

DOE OSTI2022

Methodology of the Extraction of Multi-Differential Cross Sections of Charged-Current $\nu_\mu$-Argon Interactions in MicroBooNE Using Wire-Cell $\nu_\mu$CC Selection

Neutrino physics experiments rely on accurate nuclear-interaction models that are in part guided by experimental observations. Multi-differential cross section measurements are particularly valuable for exploring the underlying physics described in these models, making them a significant step forward in the field. This note presents methodology in preparation to unfold neutrino flux-averaged double and triple-differential cross sections of the inclusive muon neutrino charged-current interaction on Argon. This work builds upon the existing framework and methodology presented in recent energy dependent cross section measurements at MicroBooNE using the Wire-Cell tomographic event reconstruction. The signal definition, choice of binning, and handling of estimated detector uncertainties are discussed, and the MicroBooNE simulation model is validated over the multi-dimensional phase space of muon momentum, muon polar angle, and visible hadronic energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

The Mira–Titan Universe – IV. High-precision power spectrum emulation

Modern cosmological surveys are delivering data sets characterized by unprecedented quality and statistical completeness; this trend is expected to continue in the future as new ground- and space-based surveys come online. In order to maximally extract cosmological information from these observations, matching theoretical predictions are needed. At low redshifts, the surveys probe the non-linear regime of structure formation where cosmological simulations are the primary means of obtaining the required information. The computational cost of sufficiently resolved large-volume simulations makes it prohibitive to run very large ensembles. Nevertheless, precision emulators built on a tractable number of high-quality simulations can be used to build very fast prediction schemes to enable a variety of cosmological inference studies. We have recently introduced the Mira–Titan Universe simulation suite designed to construct emulators for a range of cosmological probes. This gravity-only set of simulations covers the standard six cosmological parameters {ω m , ω b , σ 8 , $h, n_s, w_0$} and, in addition, includes massive neutrinos and a dynamical dark energy equation of state {ω ν , $w_a$}. In this paper, we present the final emulator for the matter power spectrum based on 111 cosmological simulations, each covering a (2.1 Gpc) 3 volume and evolving 3200 3 particles. In this work, an additional set of 1776 lower resolution simulations and TimeRG perturbation theory results for the power spectrum are used to cover scales straddling the linear to mildly non-linear regimes (maximum wavenumber $\textit{k}$ = 5 Mpc –1 ). The emulator provides predictions at the 2–3 percent level of accuracy over a wide range of cosmological parameters and is publicly released as part of this paper.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Modeling Multi-View Impedance-Based Cross-Geometry SOH Estimator for Li-ion Batteries

Abstract: Accurately estimating battery’s State of Health (SOH) remains challenging when models must generalize across cell designs and operating conditions. Most Electrochemical Impedance Spectroscopy (EIS)-based approaches either (i) hand-engineer a few Nyquist-plot features for shallow models—fast but does not generalize across geometries—or (ii) learn directly from Nyquist plots with deep networks, which removes manual feature extraction, yet still limited to a single plot type. As a result, cross-geometry robustness and deployability on constrained Internet of Things (IoT) devices remain open problems. We propose a compact Convolutional Neural Network (CNN) (∼ 10k parameters) that takes multi-representation EIS inputs—Nyquist (real/imaginary) and phase–magnitude (|Z|/ϕ) stacked as four channels, so the model can learn complementary degradation signatures while remaining small enough for fast inference. We build a dataset from cyclic aging of two geometries (LG INR18650MJ1 cylindrical cells and LIR2032 coin cells), acquire EIS every ten cycles from 10 kHz to 10 mHz (10 points/decade), and evaluate with leave-one-cell-out testing strategy. We further study fusion vs. single-representation inputs and assess feasibility for on-device deployment (e.g., NVIDIA Jetson device). The results show that training on multiple EIS representations improves SOH estimation accuracy and cross-geometry generalization compared to single-representation models, which uses only Nyquist or phase–magnitude plots. This design targets accurate, generalizable SOH prediction without manual feature engineering while enabling practical real-time use.

Bakr, Ahmed [The University of Alabama (UA)]↗

NASA NTRS2010

Using SCOR as a Supply Chain Management Framework for Government Agency Contract Requirements

This paper will present a model that uses the Supply-Chain Operations Reference (SCOR) model as a foundation for a framework to illustrate the information needed throughout a product lifecycle to support a healthy supply chain management function and the subsequent contract requirements to enable it. It will also show where in the supply chain the information must be extracted. The ongoing case study used to exemplify the model is NASA's (National Aeronautics and Space Administration) Ares I program for human spaceflight. Effective supply chain management and contract requirements are ongoing opportunities for continuous improvement within government agencies, specifically development of systems for human spaceflight operations. Multiple reports from the Government Accountability Office (GAO) reinforce this importance. The SCOR model is a framework for describing a supply chain with process building blocks and business activities. It provides a set of metrics for measuring supply chain performance and best practices for continuously improving. This paper expands the application of the SCOR to also provide the framework for defining information needed from different levels of the supply chain and at different phases of the lifecycle. These needs can be incorporated into contracts to enable more effective supply chain management. Depending on the phase of the lifecycle, effective supply chain management will require involvement from different levels of the organization and different levels of the supply chain.

Paxton, Joseph↗

NASA NTRS2021

Autonomous Safe Landing Site Detection for a FutureMars Science Helicopter

Future Mars Rotorcrafts require advanced navigation capabilities to enable all terrain access for science investigations with long distance flights that are executed fully autonomously. A critical component is the ability to safely land in hazardous terrain as part of a mission, or triggered by an emergency situation. In this paper, we present an advanced navigation system for continuous on-board terrain reconstruction for the purpose of hazard-free landing site detection for the autonomous navigation of a Mars Science Helicopter - a JPL research concept that investigates the feasibility of flying a multi-kilogram science payload at various Mars science locations, with flight ranges of multiple kilometers per flight. Our approach builds on a visionbased perception system that incorporates an on-board visualinertial state estimator augmented by a laser altimeter (range- VIO), and a structure-from-motion 3D reconstruction approach that uses a single, downward-looking camera to provide dense depth measurements while the vehicle is in motion. Depth measurements are accumulated in a local, robot-centric, multiresolution elevation map that is analyzed by a landing site detector to extract safe landing areas below the rotorcraft, based on a heuristic that includes slope, roughness and the presence of landing hazards. Detected landing sites are prioritized by an on-board autonomy engine that either selects suitable landing sites for immediate landing maneuvers, or can explore a terrain location as part of a mission in order to find a best landing site in a pre-planned area. We demonstrate and evaluate our approach on simulated data and data acquired with a surrogate unmanned aerial system (UAS) executing flights over relevant terrain.

Tzanetos, Teddy↗

NASA NTRSDate not supplied

System Modeling of a Lunar Molten Regolith Electrolysis Plant

Introduction: In-Situ Resource Utilization (ISRU) is the process of extracting local resources to produce commodities for propulsion, life support systems, and off-planet construction rather than transporting consumables from Earth. Molten Regolith Electrolysis (MRE) is a novel ISRU method of extracting oxygen gas and metal alloy from lunar regolith. The MRE process involves placing lunar regolith between two electrodes, through which current is passed, to melt the regolith and reduce the metal oxide constituents by direct electrolysis (e.g. FeO, SiO2, MgO, Al2O3) into oxygen gas and metal alloys. The oxygen is liquefied and used as propellant for landers, while the metals (e.g. Ferro-alloys) are further processed and used in structural building materials and parts manufacturing. A system model was developed that accounted for the major processes of an MRE plant (from excavation of raw materials to storage of products) to assess the feasibility of a lunar MRE plant. The System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team utilized its previously documented system sizing model, the Mission Analysis and Integration Tool (MAIT) [1] as framework of the system model. MAIT uses MATLAB/Simulink to integrate subsystem models into a complete system model of the MRE plant. Total mass, volume, and power requirements were computed for numerous iterations of a MRE plant. System Model: Figure 1: MRE Plant Block Diagram The regolith excavation model determines the mass and power needed to excavate sufficient regolith. The preheating auger initiates the regolith heating process before regolith enters the MRE re-actor to reduce the energy required to turn the solid into a molten liquid. The MRE reactor is modeled in COMSOL Multiphysics and based on the research by Dominguez, Sibille, and Schreiner [2, 3, 4]. This preliminary reactor model provides an accurate calculation of thermal equilibrium during electrochemical operation of the reactor system to assess the optimal mass and power required to process the inlet flow of regolith. The model also computes the outlet flowrates of oxygen and molten products. For this analysis, the primary components of the metal alloy considered were iron and silicon. The oxygen is then purified using an Yttrium Stabilized Zirconia (YSZ) electrode, followed by liquefaction using a 90K cryocooler to be stored as liquid oxygen in insulated cylindrical tanks. In future iterations of the system model, the molten metal tapped from the MRE reactor will undergo additional processing or refinement. However, downstream handling of metals is currently a technology gap that is missing a high TRL subsystem model. Therefore, for this analysis, the accumulated metal alloy stream terminates after leaving the MRE reactor. Study Goals: This analysis investigates multiple input variables to the system to determine the sensitivity of a (near) complete plant at full-scale. This preliminary investigation ran parametric sweeps on the MRE reactor geometry, electrical current supply, layers of multi-layer insulation (MLI) on the reactor, size of the electrodes in the oxygen purification model, and regolith composition (based on landing site location). Three production targets of oxygen (1,000, 10,000, and 50,000 kg/yr) were investigated for this analysis. The parametric sweeps conducted in this analysis provide valuable insight into the expected impact of the various model inputs on plant size. This information can be used to identify the most critical components of the plant and guide future decisions on allocating funding for research and development, providing subsystem developers with appropriate interfaces with downstream and upstream processes, and assessing the overall feasibility of MRE when compared to other ISRU plants. References: [1] Carlson, A. et al. (2024) ICES, ICES-2024-53. [2] Dominguez, D.A., and Sibille, L. (2011) AIAA, AIAA-2011-700. [3] Schreiner, S.S. (2015) MIT, Dissertation. [4] Schreiner, S.S. et al. (2016) ASR, 57(7), pp.1585-1603.

ISRU↗

DOE OSTI2023

Fracture-matrix fluid exchange in oil-bearing unconventional mudstones

The poromechanical properties of unconventional reservoir materials are in large part dictated by their mineralogy. Since these properties govern the response to stress experienced during hydraulic fracturing, fluid production, and fluid injection, they play a central role in the formation of microcracks or bedding delaminations which ultimately dominate mass transport. In this work we study access to the porosity of end member unconventional reservoir materials, where the end members are predominantly dictated by carbonate content. Access to the porosity is quantified using state of the art 3D x-ray computed tomography coupled with physics informed data analytics. Xenon gas, which attenuates x-rays, provides a spatiotemporal map of access to the porosity. The accessible porosity is quantified over a range of net confining stress relevant to the manmade disturbances listed above. These experiments demonstrate that heavily carbonated mudstones are nearly impermeable at the core (~ cm) scale, while carbonate free analogues afford better access to the microstructure. Consistent with previous qualitative 2D radiographs, access to the interior of the clastic mudstones is first observed along planar microcracks, followed by slow penetration into the surrounding matrix. Physics informed data analytics of the 3D tomography measurements presented here show that these microcracks do not permit uniform access to the adjacent rock matrix. In addition, variation of the effective pressure elucidates the mechanisms that govern fracture/matrix fluid exchange. Under conditions consistent with hydrocarbon production fluid accumulates in the immediate vicinity of the nearest microcrack. While there is clear evidence that, as intended, part of this accumulation is from the more distant matrix, fluid is also squeezed out of the microcrack. The fluid build-up at the microcrack indicates that migration out of the rock is hindered by the coupled poroelastic response of the microcrack and adjacent rock matrix. We show that these mechanisms ultimately account for the meager oil recovery factors realized in practice. These insights have implications for making reservoir scale predictions based on core scale observations, and provide a basis for devising new asset development techniques to access more porosity, and enhance fluid extraction. Finally, these findings shed light on key features and mechanisms that govern shale storage capacity, with relevance to other important industrial processes, such as geologic CO 2 storage.

58 GEOSCIENCES↗

DOE OSTI2025

Spotlight: efficient automated global optimization in rietveld analysis of diffraction data

Performing reliable Rietveld analysis on tens or hundreds of powder diffraction datasets from parametric or time-resolved experiments often poses a bottleneck in extracting meaningful results from the data. While automated analysis of data has recently been demonstrated, high temperature annealing studies, during which phase transformations occur and lattice parameters may change due to repartitioning of elements, are prime examples where automation by a simple phase identification from a database of room temperature structures or automation by sequential refinements is likely to fail. To enable reliable, efficient, automated Rietveld analysis, we present a Python package named Spotlight , building on established Rietveld packages such as MAUD, GSAS , or GSAS-II , which extends the refinement of best fit parameters to a global optimization using an ensemble of optimizers leveraging hierarchical parallel execution on high-performance computing clusters. Spotlight further enables the efficient design of refinement plans through the iterative automated machine-learning of a surrogate for the refinement on which the global optimizations are performed until results from the surrogate converge to the response surface data. We demonstrate Spotlight with the analysis of uranium molybdenum and Ti–6Al–4V datasets, as well as in two open-source tutorials analyzing aluminium oxide and lead sulphate.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The Role of Biofuels and Biomass Feedstocks for Decarbonizing the U.S. Economy by 2050 - (DECARB) Decarbonizing Energy Through Collaborative Analysis of Routes and Benefits

Utilizing biomass resources, such as cellulosic biomass and waste, can greatly contribute to decarbonization efforts in the U.S. economy. The U.S. bioenergy sector includes corn ethanol production, biodiesel, renewable diesel production, and the utilization of biomass wastes for electricity generation being the primary applications. Within the electricity sector, biopower can play a crucial role as a stable low-carbon resource. Enhancing the electricity mix's diversity could enhance grid reliability. If the issues regarding hot gas cleanup can be resolved, flexible biopower resources like biomass gasification facilities could complement the integration of variable renewable energy sources due to their quick ramp-up and ramp-down times. The criticality of bioenergy deployment lies in its ability to decarbonize hard-to-electrify sectors, such as aviation, where alternative decarbonization options may not be viable in the short term. Moreover, bioenergy has the potential to be converted into process heating, building materials, and plastics, which are not considered in this study. A set of pathways was carefully chosen to represent viable options for converting ample herbaceous and woody cellulosic feedstocks into fuels, chemicals, and electricity in this study. In conclusion, biomass pathways provide flexibility by generating various types of bioenergy and bioproducts, including electricity, hydrogen, liquid fuels, biochemicals, and bioplastics. When paired with carbon dioxide capture and storage (CCS), specific bioenergy approaches can effectively extract carbon dioxide from the atmosphere, thus providing an effective decarbonization option for the transportation sector.

09 BIOMASS FUELS↗

DOE OSTI2024

WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

Tetteh, Daniel A.↗