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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 343 records · Page 19

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

Identifying Challenges in Safeguards for Metallic Fuel Fabrication Facilities

As new advanced reactors gain popularity, there is an increasing interest in metallic fuel fabrication for fast reactors. While metallic fuels themselves are not a new idea, as many of the first reactors employed metallic fuels, new designs, compositions, and fabrication methods are appearing throughout the nuclear community. As the interest grows and facilities are constructed, both domestic and international safeguards will need to be heavily involved to support safeguards-by-design (SBD) measures from the start. This work compiles a review of historical and modern fuel types and fabrication methods, fabrication processes, safeguards gaps, and potential safeguards solutions. Metallic nuclear fuel types have been around for many decades and were included in some of the first reactors including the Experimental Breeder Reactor (EBR)-I and -II, the Fermi 1 reactor, the Integral Fast Reactor (IFR), and the Dounreay Fast Reactor (DFR). These reactors used various compositions including pure uranium (U) metal, U-zirconium (Zr) alloys, plutonium (Pu)-aluminum (Al) alloys, U-fissium (Fs) alloys, U-Pu-Zr alloys, and U-molybdenum (Mo) alloys [1, 2, 3, 4, 5]. These small alloying additions are included to improve the material properties of the pure U metal. The alpha-phase U (stable below 661C) suffers elongation in one direction causing grain boundary cracking and increasing creep rate due to irradiation growth, thermal cycling, and preferential crystal orientation. It is ideal to utilize the gamma-phase U (typically stable above 769C) by adding small amounts of alloying elements such as Zr or Mo to stabilize this phase down to room temperature [3]. Additionally, some research has been focused on U with transuranic (TRU) elements present, typically coming from the used fuel recycling process. Including these elements in fast reactor fuel can aid in the reduction of nuclear waste by burning minor long-lived actinides. However, the additions of TRU elements can cause concerns to arise when trying to fabrication or safeguard metallic fuels. A typical metallic fuel element is shown in Figure 1. Sodium is added into the cladding to create a thermal bond between the fuel slug and cladding wall. The fuel slug is then inserted and the end plug is welded on to the top of the fuel element. A gas plenum is left to create a headspace for gaseous fission products to escape rather than continue to build in the fuel itself [1, 5]. Other fuel element geometries exist as well, such as the Lightbridge twisted cruciform geometry shown in Figure 2 [6]. This design allows for better cooling performance and provides room for fuel rod swelling without impacting the fuel rod diameter. There are many different fabrication methods for metallic fuels, which is one of the many benefits of these fuel types. Many of these fabrication methods are relatively easy and cost-efficient. The most popular fabrication method is injection casting, sometimes called vacuum induction melting (VIM), shown in Figure 3 [4, 8, 9, 7, 10]. This method was largely used for EBR-II fuel fabrication. The injection casting system is contained inside of a vessel consisting of a Y2O3-coated graphite crucible surrounded by an induction coil with ZrO2-coated quartz molds suspended above the crucible. The fuel feedstock is placed inside of the graphite crucible and melted using the induction furnace. The induction furnace utilizes a dual frequency with the high frequency melting the feedstock and the low frequency causing stirring of the melted feedstock to form a homogeneous mixture. The mixture is heated to approximately 1600C in an argon environment. The vessel is evacuated and then the quartz molds are lowered into the graphite crucible containing the molten metal and the vessel is repressurized to inject the metal fuel upwards into the molds. The molds are removed and then shattered to release the fuel slugs. This fabrication method was used to fabricate 39,000 metallic fuel pins for EBR-II. While injection casting has been the most common metallic fuel fabrication method throughout the decades, many other methods have been explored including low-pressure gravity casting, microwave casting, continuous casting, centrifugal casting, coextrusion, and many others [11, 12, 8, 13, 14, 15]. Some of these methods aim to mitigate challenges that arise with americium (Am) volatilization during the casting process for TRU-containing fuel feedstocks, an issue with injection casting. Coextrusion is one of the methods explored at the Idaho National Laboratory (INL) and has been utilized for the initial fabrication tests of Lightbridge's unique fuels, as well as other metallic fuels with cladding coextruded. In this process, large billets are formed and machined and then inserted into a molten salt bath for approximately 30 minutes. The billets are then loaded into the extrusion press and extruded. This process can be seen in Figure 4 [15].

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Big Data Analysis and Technical Review of Regeneration for Carbon Capture Processes

Carbon capture remains an integral technology to mitigate pollution from one of the most prevalent greenhouse gases. CO 2 desorption/absorbent regeneration for both solid- and liquid-based systems is widely recognized as an energy-intensive and costly process operation. Consequently, tremendous work was devoted towards developing new absorbents and regeneration processes to promote their economic feasibility for extensive implementation. In this review, we broadly and deeply review more than 10,000 papers and extract the hidden trends of carbon capture and absorbents regeneration in the past few decades, using a novel data-mining analysis technique. We comprehensively analyzed an array of recent absorbent regeneration methods utilized in post-combustion, pre-combustion, carbon capture from industrial point sources, and direct air carbon capture, with an emphasis on sorbent and solvent-based techniques. In conclusion, advanced regeneration methods in these techniques were illustrated and discussed, followed by recommendations for further research efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hybrid CFD Engineering Model of Plume Induced Erosion and Crater Formation During Descent of Lunar Landers

With rapidly increased worldwide interest in landing on the moon, the issue of Plume Surface Interactions (PSI) is gaining attention. Hazards posed by lander plume induced dust and debris, as well as landing site deformation can be mitigated when better understood through predictive simulations. As simulation enabling computational power continues to increase, hybrid Computational Fluid Dynamics (CFD)/Engineering models provide the immediate ability to conduct parametric/trade studies driving design decisions for landers. Reduced order erosion engineering models apply correlations of the surface erosion rate to the plume induced surface forces with the correlations anchored to flight observations from Apollo LM landings. The MSFC propulsion fluid dynamics branch has developed such a hybrid model for predicting the plume induced viscous erosive regression of the Lunar surface beneath a landing vehicle. The (Descent Interpolated Gas Granular Erosion Model) DIGGEM was originally implemented as a post processing tool to calculate induced erosion rates through vehicle descent using CFD solutions of the vehicle plume at several fixed altitudes. This capability has since been advanced in the Loci/Chem-DIGGEM model to allow transient, moving vehicle, fully coupled viscous erosion modeling of vehicle descent PSI. This model has recently been used to make preflight predictions of the erosive regression of the ground beneath a Commercial Lunar Payload Services (CLPS) vehicle in support of measurements to be made by the Stereo Cameras for Lunar Plume Surface Studies (SCALPSS) instrument.

Plume Surface Interaction↗

Hybrid CFD Engineering Model of Plume Induced Erosion and Crater Formation During Descent of Lunar Landers

With rapidly increased worldwide interest in landing on the moon, the issue of Plume Surface Interactions (PSI) is gaining attention. Hazards posed by lander plume induced dust and debris, as well as landing site deformation can be mitigated when better understood through predictive simulations. As simulation enabling computational power continues to increase, hybrid Computational Fluid Dynamics (CFD)/Engineering models provide the immediate ability to conduct parametric/trade studies driving design decisions for landers. Reduced order erosion engineering models apply correlations of the surface erosion rate to the plume induced surface forces with the correlations anchored to flight observations from Apollo LM landings. The MSFC propulsion fluid dynamics branch has developed such a hybrid model for predicting the plume induced viscous erosive regression of the Lunar surface beneath a landing vehicle. The (Descent Interpolated Gas Granular Erosion Model) DIGGEM was originally implemented as a post processing tool to calculate induced erosion rates through vehicle descent using CFD solutions of the vehicle plume at several fixed altitudes. This capability has since been advanced in the Loci/Chem-DIGGEM model to allow transient, moving vehicle, fully coupled viscous erosion modeling of vehicle descent PSI. This model has recently been used to make preflight predictions of the erosive regression of the ground beneath a Commercial Lunar Payload Services (CLPS) vehicle in support of measurements to be made by the Stereo Cameras for Lunar Plume Surface Studies (SCALPSS) instrument.

Plume Surface Interaction↗

Selective Valorization of CO 2 towards Valuable Hydrocarbons through Methanol-mediated Tandem Catalysis

The thermocatalytic conversion of carbon dioxide (CO 2 ) into valuable hydrocarbons presents a promising solution for mitigating anthropogenic CO 2 emissions while producing drop-in replacements for fossil-derived products. Among the two tandem mechanisms for the direct hydrogenation of CO 2 , the methanol synthesis coupled with the methanol to hydrocarbon (MTH) reaction offers an improvement over the reverse water-gas shift coupled with Fischer-Tropsch synthesis reaction (RWGS-FTS), as it is not limited by Anderson-Schulz-Flory distribution and yields higher selectivity towards specific products (e.g., olefins, aromatics, higher hydrocarbons). Herein, we focus on the recent progress achieved through this pathway and outline the existing knowledge gaps. We discuss the challenges involved in the process and highlight the key descriptors in the selection of catalyst components. Finally, we present several potential solutions to circumvent the current challenges, aiming to expedite the advancement of this route toward an efficient CO 2 hydrogenation process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lignin-enzyme interaction: A roadblock for efficient enzymatic hydrolysis of lignocellulosics

Efficiently producing second-generation biofuels from biomass is of strategic significance and meets sustainability targets, but it remains a long-term challenge due to the existence of biomass recalcitrance. Lignin contributes significantly to biomass recalcitrance by physically limiting the access of enzymes to carbohydrates, and this could be partially overcome by applying a pretreatment step to directly target lignin. However, lignin typically cannot be completely removed, and its structure is also significantly altered during the pretreatment. As a result, lignin residue in the pretreated materials still significantly hindered a complete conversion of carbohydrate to its monosugars by interacting with cellulase enzymes. The non-productive adsorption driven by hydrophobic, electrostatic, and/or hydrogen bonding interactions is widely considered as the major mechanism of action governing the unfavored lignin-enzyme interaction. One could argue this type of interaction between lignin residue and the activated enzymes is the major roadblock for efficient enzymatic hydrolysis of pretreated lignocellulosics. To alleviate the negative effects of lignin on enzyme performance, a deep understanding of lignin structural transformation upon different types of pretreatments as well as how and where does lignin bind to enzymes are prerequisites. In the last decade, the progress toward a fundamental understanding of lignin-enzyme interaction, structural characterization of lignin during pretreatment and/or conformation change of enzyme during hydrolysis is resulting in advances in the development of methodologies to mitigate the negative effect of lignin. Here in this review, the lignin structural transformation upon different types of pretreatments and the inhibition mechanism of lignin in the bioconversion of lignocellulose to bioethanol are summarized. Some technologies to minimize the adverse impact of lignin on the enzymatic hydrolysis, including chemical modification of lignin, adding blocking additives, and post-treatment to remove lignin were also introduced. The production of liquid biofuels from lignocellulosic biomass has shown great environmental benefits such as reducing greenhouse gas emissions and mitigate climate change. By addressing the root causes of lignin-enzyme interaction and how to retard this interaction, it is our hope that this comprehensive review will pave the way for significantly reducing the high cost associated with the enzymatic hydrolysis process, and ultimately achieving a cost-effective and sustainable biorefinery system.

09 BIOMASS FUELS↗

Fusing Edge Computing with Transport Security by Leveraging the Controller Area Network Transport Security Tracking and Reporting (C-STAR) Unit

Rapid advances in embedded system complexity and capability provides exciting opportunities for transportation security deployment. Manufacturers and developers of these embedded systems continue to provide lower cost and more powerful solutions that can be leveraged by researchers and engineers. Furthermore, deploying these devices at the “edge” of the Internet-of-Things (IoT) infrastructure provides opportunities for highly capable applications in transport security. In an edge computation architecture, the device is co-located at the source of the data in the larger IoT structure – this provides computational capability at the location directly where the data is collected. For shipment transport security, this provides a direct compute node for digestion of data and mitigation actions in real-time. In our application, the vehicle provides a significant amount of this data that can be processed in real-time via the Controller Area Network Transport Security Tracking and Reporting (C-STAR) edge device. Utilization of a computational node located on the vehicle, such as the C-STAR, capitalizes on previously discussed opportunities of edge architectures. In this paper, we will discuss this security solution’s usability, current deployments, and scalability to further applications in transport security. First, we will cover the supported vehicle platforms that can leverage the C-STAR technology. This will be particularly relevant to medium- and heavy-duty vehicles transporting high-risk shipments. Second, we will speak to current deployments of the C-STAR that are ongoing. Finally, we will discuss additional areas for expansion such as maturing the onboard algorithms through continuing collaborations.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗

Biofouling of filtration membranes in wastewater reuse: In situ visualization with confocal laser scanning microscopy

The filtration membranes utilized in advanced treatment of municipal wastewater are prone to biological fouling. Permeability loss and water recovery limitations due to fouling necessitate additional pretreatment and membrane cleaning, which raise the cost of water reuse. Better fouling mitigation calls for a deeper understanding of biofilm behavior on water reuse membranes. This study uses confocal microscopy to monitor biofouling under realistic conditions. To simulate water reuse, a miniature flow cell with microfiltration and ultrafiltration membranes was operated under typical filtration conditions using secondary effluent from California's East Bay Municipal Utility District. The growing biofilms were stained for extracellular polymeric substances and live and dead cells, and they were monitored in situ under filtration conditions with a confocal laser scanning microscope to produce 2-D and 3-D images. In situ image series revealed biofilm growth and removal processes including internal and external fouling, extracellular polymeric substance production, wrinkling, delamination, and film re-deposition. Additionally, changes in biofilm morphology between in situ and ex situ images highlighted limitations of ex situ imaging. Here, these results provide insight into the physical and biological mechanisms of biofouling in hopes of informing the development of improved techniques for biofouling mitigation.

ultrafiltration↗

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Food Security Challenges

Ocean color satellite measurements have yielded valuable information about the base of the marine food web for over 20 years. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is building an advanced spectrometer to further refine ecosystem monitoring. Higher spectral resolution data from PACE will enable identification of additional marine biological indicators and their response to multiple stressors to guide sustainable management. Seafood is an important source of protein for a significant number of people. Wild catches cannot match increasing demand and their sustainability is in question. Aquaculture is an ever more important industry to feed the world's population. We share early efforts to engage a community of practice around food security to increase satellite data product use in support of resource management, business decisions, and policy analysis. Understanding the needs of applied scientists as well as non-traditional users of satellite data early in the PACE mission process will improve planning and preparation for a broader user base and hopefully help to mitigate food insecurity.

Schollaert Uz, Stephanie↗

Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the ‘in-time’ aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance.

Young, Steven↗

Risk-informed Graded Approach for Reliability and Performance Assessment of Sensor and Instrumentation Systems within Advanced Condition Monitoring Technologies

Advanced condition monitoring (ACM) technologies, such as digital twins, are innovative strategies designed to provide real-time health insights, including the remaining useful life of components. The primary goal of ACM is to predict and alert operators to potential functional failures before they occur. ACM systems achieve this by integrating predictive models with various sensor instrumentation, analog-to-digital converters, data warehouses, and data pre-processors. These sensor and instrumentation systems (SIS) are essential for forming a comprehensive understanding of component conditions and ensuring the predictive success of ACM programs. Introducing new technologies like ACM involves varying degrees of risk that can impact plant reliability. Therefore, risk mitigation should be commensurate with the performance and reliability of the developed technology, following a risk-informed graded approach (RIGA). Establishing a RIGA process requires a clear understanding of the hazards and reliability of all subsystems, including their interdependencies and potential impacts on the overall system. Given the critical role of SIS in ACM, this work reviews hazard identification and reliability quantification methods for SIS. It also considers these methods' implications when developing a RIGA process for ACM.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Enhancing carbon storage through proactively managing fire-prone coniferous mountain forests

Mountain ecosystems typically serve as carbon (C) sinks. However, studies also suggest that they could be C sources due to climate warming, drought and insect-related mortality, wildfires, and management actions. We applied the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS), a process-based dynamic vegetation-ecosystem model, to investigate the role of ecosystem management in C storage under Mediterranean climate over the 21 st century. We modified LPJ-GUESS to include implementing mechanical thinning by vegetation size classes, components, and types along with a new mechanistic fire-occurrence model that accounts for wind speed and lightning ignition. Simulations show that mechanical thinning or prescribed fire performed 5-20 years in advance of a high-severity wildfire reduced direct wildfire C emissions by 38-66 %. Our results also show that long-term management actions repeated every 5-20 years, including thinning relatively small trees (diameters up to 7 inches or ∼178 mm), can maintain stable C levels in the forest and lower dead-fuel amounts. We found that, although prescribed fire mitigated wildfire severity, ecosystem C storage from reduced wildfire emissions can be outweighed by the added emissions from the prescribed fire themselves. Thinning plus removing and sequestering the thinned biomass can ensure that forests act as net C sinks through the end of the 21 st century. However, addition of prescribed fire is needed to reduce understory and lower the projected extent of high-severity wildfire. Achieving the competing goals of reducing wildfire and making the Sierra Nevada long-term C sink can be advanced through carefully coordinated thinning, sequestration of thinned biomass, and prescribed fire.

Climate solutions↗

NASA Tech Briefs, November 2004

Topics include: Multifunction Imaging and Spectroscopic Instrument; Position-Finding Instrument Built Around a Magnetometer; Improved Measurement of Dispersion in an Optical Fiber; Probe for Sampling of Interstitial Fluid From Bone; Neuropsychological Testing of Astronauts; Method of Calibration for a Large Cathetometer System; Four-Channel PC/104 MIL-STD-1553 Circuit Board; Improved Method of Locating Defects in Wiring Insulation; Strobe Traffic Lights Warn of Approaching Emergency Vehicles; Improved Timing Scheme for Spaceborne Precipitation Radar; Concept for Multiple-Access Free-Space Laser Communications; Variable Shadow Screens for Imaging Optical Devices; Verifying Diagnostic Software; Initial Processing of Infrared Spectral Data; Activity-Centric Approach to Distributed Programming; Controlling Distributed Planning; New Material for Surface-Enhanced Raman Spectroscopy; Treated Carbon Nanofibers for Storing Energy in Aqueous KOH; Advanced Infant Car Seat Would Increase Highway Safety; Development of Biomorphic Flyers; Second-Generation Six-Limbed Experimental Robot; Miniature Linear Actuator for Small Spacecraft; Process for Making Single-Domain Magnetite Crystals; A New Process for Fabricating Random Silicon Nanotips; Resin-Transfer-Molding of a Tool Face; Improved Phase-Mask Fabrication of Fiber Bragg Gratings; Tool for Insertion of a Fiber-Optic Terminus in a Connector; Nanofluidic Size-Exclusion Chromatograph; Lightweight, Low-CTE Tubes Made From Biaxially Oriented LCPs; Using Redundancy To Reduce Errors in Magnetometer Readings; Compact Instrument for Measuring Profile of a Light Beam; Multilayer Dielectric Transmissive Optical Phase Modulator; Second-Generation Multi-Angle Imaging Spectroradiometer; Real-Time Adaptive Color Segmentation by Neural Networks; Research and Development in Optical Communications; Tests of Multibeam Scintillation Mitigation on Laser Uplinks; and Spaceborne Infrared Atmospheric Sounder.

Source record↗

Adaptive Scalpel Scanning Probe Microscopy for Enhanced Volumetric Sensing in Tomographic Analysis

Controlling nanoscale tip‐induced material removal is crucial for achieving atomic‐level precision in tomographic sensing with atomic force microscopy (AFM). While advances have enabled volumetric probing of conductive features with nanometer accuracy in solid‐state devices, materials, and photovoltaics, limitations in spatial resolution and volumetric sensitivity persist. This work identifies and addresses in‐plane and vertical tip‐sample junction leakage as sources of parasitic contrast in tomographic AFM, hindering real‐space 3D reconstructions. Novel strategies are proposed to overcome these limitations. First, the contrast mechanisms analyzing nanosized conductive features are explored when confining current collection purely to in‐plane transport, thus allowing reconstruction with a reduction in the overestimation of the lateral dimensions. Furthermore, an adaptive tip‐sample biasing scheme is demonstrated for the mitigation of a class of artefacts induced by the high electric field inside the thin oxide when volumetrically reduced. This significantly enhances vertical sensitivity by approaching the intrinsic limits set by quantum tunneling processes, allowing detailed depth analysis in thin dielectrics. The effectiveness of these methods is showcased in tomographic reconstructions of conductive filaments in valence change memory, highlighting the potential for application in nanoelectronics devices and bulk materials and unlocking new limits for tomographic AFM.

36 MATERIALS SCIENCE↗

Optimization of Conditions for Photoluminescence-Based Sensing of Critical Minerals: Strategies and Outlook

Economically critical minerals and metals are vital to America’s security, with application areas in energy, advanced technologies, and defense systems. The growing implementation of renewable energy sources such as electric vehicles is expected to significantly increase demand for these minerals, while the global supply is monopolistic, with most of the production occurring in a few countries outside of the US. To mitigate potential supply chain vulnerabilities, the domestic production of economically critical metals has become a bipartisan priority of the US government, and unconventional sources such as coal and its utilization byproducts such as fly ash and acid mine drainage are being actively explored as an alternative method for meeting domestic demand. Slow and expensive characterization methods for critical metals present a significant pain point for domestic production, which has led to the exploration of alternative low-cost, portable platforms capable of detecting target metals during resource prospecting and downstream process monitoring. The National Energy Technology Laboratory has developed a portable fiber optic-based luminescence spectrometer that utilizes a metal-organic framework (MOF) material to detect and distinguish parts-per-billion levels of the visible-emitting rare earth elements terbium, dysprosium, samarium, and europium, which are all economically critical metals. Although preliminary results with this system are promising, a crucial barrier to practical deployment is the ability to operate in low pH, high ionic strength environments, as acidic conditions and the presence of other metal ions can significantly reduce luminescence signal. Here, current strategies related to sample treatment, material design, and sensor configuration are discussed in the context of improving sensor performance in application-relevant conditions. Additionally, future opportunities, such as the optimization of the sensing binding environment through computational methods and specific metals to be removed for treatment will be discussed, presenting a forward-looking view for innovation in luminescent sensing of critical metals.

36 MATERIALS SCIENCE↗

Plant Biosystems Design for a Carbon-Neutral Bioeconomy

Our society faces multiple daunting challenges including finding sustainable solutions towards climate change mitigation; efficient production of food, biofuels, and biomaterials; maximizing land-use efficiency; and enabling a sustainable bioeconomy. Plants can provide environmentally and economically sustainable solutions to these challenges due to their inherent capabilities for photosynthetic capture of atmospheric CO 2 , allocation of carbon to various organs and partitioning into various chemical forms, including contributions to total soil carbon. In order to enhance crop productivity and optimize chemistry simultaneously in the above- and belowground plant tissues, transformative biosystems design strategies are needed. Concerted research efforts will be required for accelerating the development of plant cultivars, genotypes, or varieties that are cooptimized in the contexts of biomass-derived fuels and/or materials aboveground and enhanced carbon sequestration belowground. Here, we briefly discuss significant knowledge gaps in our process understanding and the potential of synthetic biology in enabling advancements along the fundamental to applied research arc. Ultimately, a convergence of perspectives from academic, industrial, government, and consumer sectors will be needed to realize the potential merits of plant biosystems design for a carbon neutral bioeconomy.

59 BASIC BIOLOGICAL SCIENCES↗

Development and Analysis of the Automated Object Reentry Survival Analysis Tool Parametric Study Wrapper

The NASA Orbital Debris Program Office (ODPO) studies all aspects of spacecraft end-of-life and orbital debris measurement, modeling, and mitigation. The reentry safety group within the ODPO uses the Object Reentry Survival Analysis Tool (ORSAT) to calculate the casualty risk due to reentry of spacecraft and other types of orbital debris. ORSAT models spacecraft as a collection of fragments that break apart from the parent object at a pre-defined “breakup altitude.” It then calculates the trajectory and aero-heating of these fragments to determine which fragments are completely destroyed and which survive to the ground and pose a risk to human population. Because of the historically high computational cost of these calculations, many simplifying assumptions have been made in the traditional calculation and analysis process used by the ODPO, some of which have been shown by recent research by the ODPO and others to be incorrect. Improvements to the ORSAT code and advancements in computer technology have vastly decreased the program’s processing time, and have allowed the ODPO to develop a capability for large-scale parametric studies and Monte Carlo reentry simulations that can aid in both the initial spacecraft design and provide more detailed and accurate risk analysis to spacecraft operators.

Smith, Andrew N.↗