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DOE OSTI2024

Advanced Method Optimization for Sampling and Analysis Instrumentation

This work presents a generalized approach for analytical method optimization that branches the gap between techniques historically employed and accurate modern optimization techniques suitable for various applications. The novelty of the described strategy is the utilization of multivariate, multiobjective optimization with Karush-Kuhn-Tucker conditions to bound the optimization space to solutions within the physical limitations of instrumentation. Briefly, the basic steps outlined in this paper are to (1) determine the objective(s) that should be maximized or minimized based on the goals of the analytical application, (2) conduct a screening experiment, (3) perform ANOVA to determine the parameters which have a statistically significant effect on the objective, (4) conduct an experiment (e.g., Box-Behnken design) to collect data for fitting the objective equation, and (5) determine the physical constraints of the parameters and solve the Lagrangian to determine the optimal method parameters. A broad approach to optimization target selection allows for robust method tuning to develop improved data sets amenable for chemometrics and machine learning algorithm development. Gas chromatography-mass spectrometry was selected as a use case due to its broad use across scientific fields and time-consuming method development involving numerous parameters. In conclusion, this strategy can reduce the cost of research, improve data quality, and enable the rapid development of new analytical technique.

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

Iodine solid sorbent design: a literature review of the critical criteria for consideration

Designing sorbents for iodine capture in different conditions requires selection and optimization of a large and diverse range of variables. These variables fall into general categories (or features) of sorbent activity, sorbent stability, and the fate of the loaded material in terms of the disposal (waste form) options available. To illustrate, silver-loaded, high-porosity sorbents make for maximized iodine capture and less pressure drop in a column-based sorption system approach, however, this high porosity can lead to less mechanically stable sorbents. Additionally, waste forms containing silver must also be compliant with additional criteria for hazardous waste disposal. Thus, all these aspects must be considered simultaneously when selecting a sorbent for utilization under specific conditions. Information is given for different types of sorbent design considerations for different operating conditions and some emphasis is also given on promising alternatives for silver as the active (chemisorption-based) getter metal. Discussion is given around demonstrated options for waste forms for different metal-iodide compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rewiring cell-free metabolic flux in E. coli lysates using a block—push—pull approach

Abstract Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the ‘block—push—pull’ concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2022

Considering Strain Variation and Non-Type Strains for Yeast Metabolic Engineering Applications

A variety of yeast species have been considered ideal hosts for metabolic engineering to produce value-added chemicals, including the model organism Saccharomyces cerevisiae, as well as non-conventional yeasts including Yarrowia lipolytica, Kluyveromyces marxianus, and Pichia pastoris. However, the metabolic capacity of these microbes is not simply dictated or implied by genus or species alone. Within the same species, yeast strains can display distinct variations in their phenotypes and metabolism, which affect the performance of introduced pathways and the production of interesting compounds. Moreover, it is unclear how this metabolic potential corresponds to function upon rewiring these organisms. These reports thus point out a new consideration for successful metabolic engineering, specifically: what are the best strains to utilize and how does one achieve effective metabolic engineering? Understanding such questions will accelerate the host selection and optimization process for generating yeast cell factories. In this review, we survey recent advances in studying yeast strain variations and utilizing non-type strains in pathway production and metabolic engineering applications. Additionally, we highlight the importance of employing portable methods for metabolic rewiring to best access this metabolic diversity. Finally, we conclude by highlighting the importance of considering strain diversity in metabolic engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Selective Determination of Methylmercury Levels in Mercury-Contaminated Topsoils from Oak Ridge, TN - 18163

Mercury (Hg) is a strong neurotoxin that affects the central and peripheral nervous system. Mercury has several organomercury species that bio-accumulate in many different environments. In early 1950's, elemental mercury was used for manufacturing of various components nuclear weapons systems in the Y-12 Security Complex in Oak Ridge, TN. The mercury released to the environment contaminated the facilities, soil, sediment, surface water, and groundwater within the boundaries of the Y-12 Plant and the downstream environment along the East Fork Poplar Creek. Remediation efforts have been made since then to alleviate the amount of mercury contamination that impacts the soil, water and wildlife at the Y-12 complex and surrounding areas. Yet, mercury levels in the water still exceed both the regulatory limits (51 ng/L) and the remediation goal (200 μg/L). Methylmercury (CH{sub 3}Hg) is the most toxic form of mercury that bio-accumulates exponentially compared to other forms of mercury. It is hypothesized that contaminated soils contain significant levels of methylmercury that contributes to contamination in nearby freshwater ecosystems in Y-12 complex. The objective of this study was to develop analytical method for selective determination of CH{sub 3}Hg from mercury-contaminated soils that contained elevated levels of inorganic mercury, Hg(II). Attempts were made to selectively extract CH{sub 3}Hg from spiked template soils via extraction in dilute hydrochloric (HCl) and nitric acids (HNO{sub 3}). The latter performed better than HCl affording quantitative extraction of CH{sub 3}Hg with minimal extraction of Hg(II). Under same circumstance, only about 5% of Hg(II) extracted from the soil matrix. Coprecipitation efforts were made using Bi(III), Fe(III) and La(III) alone and in conjunction with thiourea and L-cysteine. A combination of La(III) + L-cysteine afforded highest elimination of Hg(II) from solutions. Thiourea was not suitable for coprecipitation of Hg(II) as it also precipitated up to 67% of CH{sub 3}Hg from simulated soil solutions. Cold vapor generation (CVG) interfaced to ICP-MS was optimized for selective determination of CH{sub 3}Hg{sup +}. Calibration curves were established with CH{sub 3}Hg standards in La(III) and 0.1% L-cysteine and 5% (v/v) HNO{sub 3} by CVG-ICP-MS. The method was validated by determination of CH{sub 3}Hg in sediment reference material (SQC1238) and Estuarine sediment (ERM - CC580) containing trace levels of CH{sub 3}Hg in Hg(II) matrix. The procedure was applied to floodplain soils from Oak Ridge, TN. Methylmercury levels were in the range of 0.031 to 0.047 μg/g. The results indicated that CH{sub 3}Hg{sup +} levels were substantially lower inorganic Hg(II), still though CH{sub 3}Hg at these levels could be significant source of persistent mercury contamination in freshwater systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Leveraging visible and near-infrared spectroelectrochemistry to calibrate a robust model for Vanadium(IV/V) in varying nitric acid and temperature levels

Spectroelectrochemistry and optimal design of experiments can be used to rapidly build accurate models for species quantification and enable a greater level of process awareness. Optical spectroscopy can provide vital elemental and molecular information, but several hurdles must be overcome before it can become a widely adopted analytical method for remote analysis in the nuclear field. Analytes with varying oxidation state, acid concentration, and fluctuating temperature must be efficiently accounted for to minimize time and resources in restrictive hot cell environments. The classic one-factor-at-a-time approach is not suitable for frequent calibration/maintenance operations in this setting. Therefore, a novel alternative was developed to characterize a system containing vanadium(IV/V) (0.01–0.1 M), nitric acid (0.1–4 M), and varying temperatures (20–45 °C). Here, spectroelectrochemistry methods were used to acquire a sample set selected by optimal design of experiments. This new approach allows for the accurate analysis of vanadium and HNO 3 concentration by leveraging UV–Vis–NIR absorption spectroscopy with robust and accurate chemometric models. The top model's root mean squared error of prediction percent values were 3.47%, 4.06%, 3.40%, and 10.9% for V(IV), V(V), HNO 3 , and temperature, respectively. These models, efficiently developed using the designed approach, exhibited strong predictive accuracy for vanadium and acid with varying oxidation states and temperature using only spectrophotometry, which advances current technology for real-world hot cell applications. Additionally, Nernstian analysis of the V(IV/V) standard potential was performed using traditional absorbance methods and multivariate curve resolution (MCR). The successful tests demonstrated that MCR Nernst tests may be valuable in highly convoluted spectral systems to better understand the redox processes' behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Using hydrogen and ammonia for renewable energy storage: A geographically comprehensive techno-economic study

Hydrogen and, more recently, ammonia have received worldwide attention as energy storage media. In this work we investigate the economics of using each of these chemicals as well as the two in combination for islanded renewable energy supply systems in 15 American cities representing different climate regions throughout the country. We use an optimal combined capacity planning and scheduling model which minimizes the levelized cost of energy (LCOE) by determining optimal unit selection and size along with unit commitments, production rates, and storage inventories for each period of system operation. These periods are aggregated from full year hourly resolution data via a consecutive temporal clustering algorithm. Ammonia is generally more economical than hydrogen as a single method of energy storage. Additionally, systems which use both hydrogen and ammonia outperform those which use only one storage option and have LCOE between $\$ 0.17$/kWh and $\$ 0.28$/kWh, including full investment in renewable generation infrastructure.

25 ENERGY STORAGE↗
DOE OSTI2018

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt model is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.

14 SOLAR ENERGY↗
DOE OSTI2023

Performance Comparison of Object Detection Networks for Shrapnel Identification in Ultrasound Images

Ultrasound imaging is a critical tool for triaging and diagnosing subjects but only if images can be properly interpreted. Unfortunately, in remote or military medicine situations, the expertise to interpret images can be lacking. Machine-learning image interpretation models that are explainable to the end user and deployable in real time with ultrasound equipment have the potential to solve this problem. We have previously shown how a YOLOv3 (You Only Look Once) object detection algorithm can be used for tracking shrapnel, artery, vein, and nerve fiber bundle features in a tissue phantom. However, real-time implementation of an object detection model requires optimizing model inference time. Here, we compare the performance of five different object detection deep-learning models with varying architectures and trainable parameters to determine which model is most suitable for this shrapnel-tracking ultrasound image application. We used a dataset of more than 16,000 ultrasound images from gelatin tissue phantoms containing artery, vein, nerve fiber, and shrapnel features for training and evaluating each model. Every object detection model surpassed 0.85 mean average precision except for the detection transformer model. Overall, the YOLOv7tiny model had the higher mean average precision and quickest inference time, making it the obvious model choice for this ultrasound imaging application. Other object detection models were overfitting the data as was determined by lower testing performance compared with higher training performance. In summary, the YOLOv7tiny object detection model had the best mean average precision and inference time and was selected as optimal for this application. Next steps will implement this object detection algorithm for real-time applications, an important next step in translating AI models for emergency and military medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Selecting the Best Graphite for Long-Life, High-Energy Li-Ion Batteries

Here, most lithium-ion batteries still rely on intercalation-type graphite materials for anodes, so it is important to consider their role in full cells for applications in electric vehicles. Here, we systematically evaluate the chemical and physical properties of six commercially-available natural and synthetic graphites to establish which factors have the greatest impact on the cycling stability of full cells with nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) cathodes. Electrochemical data and post-mortem characterization explain the origin of capacity fade. The NMC811 cathode shows large irreversible capacity loss and impedance growth, accounting for much of full cell degradation. However, six graphite anodes demonstrate significant differences with respect to structural change, surface area, impedance growth, and SEI chemistry, which impact overall capacity retention. We found long cycle life correlated most strongly with stable graphite crystallite size. In addition, graphites with lower surface area generally had higher coulombic efficiencies during formation cycles, which led to more stable long-term cycling. The best graphite screened here enables a capacity retention around 90% in full pouch cells over extensive long-term cycling compared to only 82% for cells with the lowest performing graphite. The results show that optimal graphite selection improves cycling stability of high energy lithium-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2019

Photovoltaic Blend Microstructure for High Efficiency Post-Fullerene Solar Cells. To Tilt or Not To Tilt?

Achieving efficient polymer solar cells (PSCs) requires a structurally optimal donor-acceptor heterojunction morphology. In this paper, we report the combined experimental and theoretical characterization of a benzodithiophene benzothiadiazole donor polymer series (PBTZF4-R; R = alkyl substituent) blended with the non-fullerene acceptor ITIC-Th, and analyse the effects of substituent dimensions on blend morphology, charge transport, carrier dynamics, and PSC metrics. Varying substituent dimensions has a pronounced effect on the blend morphology with a direct link between domain purity, to some extent domain dimensions, and charge generation and collection. The polymer with the smallest alkyl substituent yields the highest PSC power conversion efficiency (PCE, 11%), reflecting relatively small, high-purity domains, and possibly benefiting from “matched” donor polymer - small molecule acceptor orientations. The distinctive morphologies arising from the substituents are investigated using molecular dynamics (MD) computation which reveals that substituent dimensions dictate a well-defined set of polymer conformations, in turn driving chain aggregation, and ultimately, the various film morphologies and mixing with acceptor small molecules. Finally, a straightforward energetic parameter explains the experimental polymer domain morphological trends, hence PCE, and suggests strategies for substituent selection to optimize PSC materials morphologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Comparison of the efficacy of a biocompatible and a distillable solvent for pretreatment of mixed bioenergy feedstocks

Biomass deconstruction is a crucial step in the production of lignocellulosic biofuels and bioproducts. However, identifying and selecting an optimal pretreatment solvent that enhances enzymatic saccharification while being cost-efficient and ensuring sustainability remains a challenge. In this study, we compare the effectiveness of the biocompatible ionic liquid cholinium lysinate ([Ch][Lys]) against the distillable solvent ethanolamine, when used for the pretreatment of mixed bioenergy feedstocks, including poplar, switchgrass, and sorghum. [Ch][Lys] was used at a concentration of 10 % wt. in a one-pot configuration without biomass washing and ethanolamine was used in a concentrated form and removed with a vacuum oven, before performing enzymatic hydrolysis and microbial conversion. Our results show that ethanolamine pretreatment consistently enhances the glucose yield across various biomass types compared to [Ch][Lys], with improvements ranging from 22.0 % to 52.7 %. The highest combined sugar release was observed when the three feedstocks were combined in equal amounts and pretreated with ethanolamine, achieving a glucose yield of 84.6 % and a xylose yield of 76.6 %. Additionally, ethanolamine exhibited exceptional solvent recovery efficiency, with removal efficiencies exceeding 99.8 % at 120 °C across all feedstocks, highlighting its advantage over non-distillable solvents. While both solvents produced biocompatible hydrolysates, the hydrolysates prepared using ethanolamine resulted in higher bioproduct formation. These findings highlight the industrial relevance of selecting recyclable and biocompatible solvents for scalable, sustainable, and cost-effective bioenergy production. This study contributes to the development of economically viable and scalable pretreatment technologies for bioenergy applications using different feedstocks and process configurations.

Rahman, Maksudur↗
DOE OSTI2021

Quantitative Evaluation of Top Coal Caving Methods at the Working Face of Extra‐Thick Coal Seams Based on the Random Medium Theory

Adopting an effective top coal caving method is the key to enhancing coal recovery and reducing gangue content for the fully mechanized top coal caving working face with extra‐thick coal seams. In this study, the movement of coal particles generated during top coal caving is considered to follow a normal distribution. Then, the caving body and coal‐rock settlement along the working face during the caving process are studied based on both the random media theory and probability theory. Accordingly, the optimal caving interval and caving sequences are determined, and a novel interval symmetrical coal caving method is proposed. The proposed method is systematically verified with results from physical similarity tests, and different caving methods are assessed by field tests. The results show the following: (1) The coal‐rock settlement and the caving body demonstrate clear axial symmetrical features along the working face; the size of the caving body increases as the caving height grows and its shape turns progressively from semicircular to semielliptical with a lower foot of the coal‐rock settlement. (2) The caving interval is derived using the sum of the radii of the coal‐rock settlement curves formed by the two largest caving bodies. (3) The symmetrical caving approach provides a symmetrical space for the subsequent movement of the broken top coal, which enables a uniform development of the caving body. (4) Compared with the traditional sequential coal caving method with the same number of supports, the interval symmetrical caving method results in a 21.7% of coal production increase, 17% caving rate promotion, and a shortened caving time by 23.4%. (5) The interval symmetrical caving method is found to improve the controllability of the caving process at the fully mechanized top coal caving working face. In general, this work presents a theoretical approach to select the optimal caving methods for the fully mechanized caving working face in extra‐thick coal seams for an improved production efficiency of the work face. The results of this study can also provide theoretical significance and referencing value for quantitative analyses of the coal caving methods for work faces with similar geological conditions.

Jiulin, Shi (ORCID:0000000155819062)↗
NASA NTRS1999

High Pressure Water Stripping Using Multi-Orifice Nozzles

The use of multi-orifice rotary nozzles greatly increases the speed and stripping effectiveness of high pressure water blasting systems, but also greatly increases the complexity of selecting and optimizing the operating parameters. The rotational speed of the nozzle must be coupled with its transverse velocity as it passes across the surface of the substrate being stripped. The radial and angular positions of each orifice must be included in the analysis of the nozzle configuration. Orifices at the outer edge of the nozzle head move at a faster rate than the orifices located near the center. The energy transmitted to the surface from the impact force of the water stream from an outer orifice is therefore spread over a larger area than energy from an inner orifice. Utilizing a larger diameter orifice in the outer radial positions increases the total energy transmitted from the outer orifice to compensate for the wider distribution of energy. The total flow rate from the combination of all orifices must be monitored and should be kept below the pump capacity while choosing orifice to insert in each position. The energy distribution from the orifice pattern is further complicated since the rotary path of all the orifices in the nozzle head pass through the center section. All orifices contribute to the stripping in the center of the path while only the outer most orifice contributes to the stripping at the edge of the nozzle. Additional orifices contribute to the stripping from the outer edge toward the center section. With all these parameters to configure and each parameter change affecting the others, a computer model was developed to track and coordinate these parameters. The computer simulation graphically indicates the cumulative affect from each parameter selected. The result from the proper choices in parameters is a well designed, highly efficient stripping system. A poorly chosen set of parameters will cause the nozzle to strip aggressively in some areas while leaving the coating untouched in adjacent sections. The high pressure water stripping system can be set to extremely aggressive conditions allowing stripping of hard to remove adhesives, paint systems, and even cladding and chromate conversion coatings. The energy force can also be reduced to strip coatings from thin aluminum substrates without causing any damage or deterioration to the substrate's surface. High pressure water stripping of aerospace components has thus proven to be an efficient and cost effective method for cleaning and removing coatings.

Hoppe, David↗
NASA NTRS1998

High Pressure Water Stripping Using Multi-Orifice Nozzles

The use of multi-orifice rotary nozzles not only increases the speed and stripping effectiveness of high pressure water blasting systems, but also greatly increases the complexity of selecting and optimizing the operating parameters. The rotational speed of the nozzle must be coupled with the transverse velocity of the nozzle as it passes across the surface of the substrate being stripped. The radial and angular positions of each orifice must be included in the analysis of the nozzle configuration. Since orifices at the outer edge of the nozzle head move at a faster rate than the orifice located near the center, the energy impact force of the water stream from the outer orifice is spread over a larger area than the water streams from the inner orifice. Utilizing a larger diameter orifice in the outer radial positions increases the energy impact to compensate for its wider force distribution. The total flow rate from the combination of orifices must be monitored and kept below the pump capacity while choosing an orifice to insert in each position. The energy distribution from the orifice pattern is further complicated since the rotary path of all orifices in the nozzle head pass through the center section, contributing to the stripping in this area while only the outer most orifice contributes to the stripping in the shell area at the extreme outside edge of the nozzle. From t he outer most shell to the center section, more orifices contribute to the stripping in each progressively reduced diameter shell. With all these parameters to configure and each parameter change affecting the others, a computer model was developed to track and coordinate these parameters. The computer simulation responds by graphically indicating the cumulative affect from each parameter selected. The results from the proper choices in parameters is a well designed, highly efficient stripping system. A poorly chosen set of parameters will cause the nozzle to strip aggressively in some areas while leaving the coating untouched in adjacent sections. The high pressure water stripping system can be set to extremely aggressive conditions allowing stripping of hard to remove adhesives, paint systems, cladding and chromate conversion coatings. The energy force can be reduced to strip coatings from thin aluminum substrates without causing damage or deterioration to the substrate's surface. High pressure water stripping of aerospace components have thus proven to be an efficient and cost effective method for cleaning and removing coatings.

Hoppe, David T.↗
NASA NTRS1998

Site Selection for Mars Exopaleontology in 2001

The microbial fossil record encompasses a wide range of information, including cellular remains, stromatolites, biofabrics, trace fossils, biominerals and chemofossils. The preservation of fossils is strongly influenced by the physical, chemical and biological factors of the environment which, acting together, ultimately determine the types of information that will be captured and retained in the rock record. The critical factor in assessing the suitability of a site for a microbial fossil record is the paleoenvironment. The reconstruction of ancient sedimentary environments usually requires the integration of a wide variety of geological information, including the shape, geometry and internal structure of sedimentary deposits, their mineralogy, and geochemistry. For Mars, much of our knowledge about past environments is based on orbital imaging of geomorphic features. This evidence provides an important context and starting point for site selection. However, our knowledge of the martian surface is quite limited, and a major goal of the upcoming exploration effort is to reconstruct the history of Martian volatiles, climate, and hydrology as a context for the exploration for past or present life. Mineralogical mapping from orbit will be an important key in this effort. In exploring for evidence of past life, terrestrial experience suggests that the long-term preservation of biological information as fossils occurs under a fairly narrow range of geological conditions that are well known to paleontologists (1). In detrital sedimentary systems, microbial fossilization is favored by rapid burial in fine-grained, clay-rich sediments. In chemical sedimentary systems, preservation is enhanced by rapid entombment in fine-grained chemical precipitates. For long term preservation, host rocks must be composed of stable minerals that resist chemical weathering, and which form an impermeable matrix and closed chemical system that can protect biosignatures from alteration during subsequent diagenetic change or metamorphism. In this context, host rocks composed of highly ordered, chemically-stable mineral phases, like silica (forming cherts) or phosphate (forming phosphorites), are especially favored. Such lithologies tend to have very long crustal residence times and (along with carbonates and shales), are the most common host rocks for the Precambrian microfossil record on Earth. If we assume that a subsurface hydrosphere has been present throughout martian history, then life could have originated there at any time, perhaps emerging at the surface periodically when climate changes, induced by external forcing or endogenous processes (e.g. volcanism), allowed liquid water to exist at the surface. The recent discovery of subsurface chemolithoautotrophic organisms which are capable of synthesizing organic substrates from C02 and H2 liberated from the aqueous weathering of basalt, is especially. relevant as a model for martian life. While a subsurface habitable zone may yet exist on Mars, access to such environments will likely require drilling to depths of several kilometers. Given the technological challenge of deep drilling, this is unlikely to occur prior to human missions. So, even if there is extant life on Mars today in subsurface habitats, it may be much easier to find its fossil counterparts in ancient deposits exposed at the surface. In exploring for a fossil record in subsurface environments on Mars there are several geological situations that may provide access to the appropriate materials. These include 1) ejecta from impact craters, 2) talus slopes, debris flows or alluvial fans developed below the walls of deep canyons, and 3) the deposits of outflood channels. Examples of aqueous mineral deposits of formed in subsurface environments that could harbor a microbial fossil record include such things as cements in detrital sedimentary rocks, low temperature diagenetic minerals deposited in veins, or filling vesicles in volcanic rocks, and hydrothermal deposits formed below the upper temperature limit for life (about 160 degrees C). There are many sites within the present latitudinal constraints for the 2001 mission (15 deg S to 30 deg N) that meet these requirements. But the practical problem with these kinds of deposits is that they tend to be disseminated, making up only a small percentage of a host rock. Even with mineralogical information provided by the Thermal Emission Spectrometer (TES) presently in orbit around Mars, predicting their occurrence ahead of time may be quite difficult. The deposits of surficial aqueous sedimentary systems are likely to provide the largest targets for site selection in 2001. Of these, the deposits of hydrothermal systems (subaerial and subaqueous thermal springs) have been discussed previously. It is likely that hydrothermal systems were widespread on Mars early in its history and a number of common geo-tectonic settings on Mars are likely to have hosted hydrothermal activity. Most of these are represented within the latitudinal constraints presently identified for 2001. However, the deposits of surface spring systems are likely to be difficult to find as well. On Earth, exposure areas for hydrothermal spring mounds are typically a few square kms, less than a single TES pixel. But such deposits may be quite abundant within some volcanic terrains, It is estimated, for example, that between 15-20% of the floor of Yellowstone caldera is covered by thermal spring deposits. In such abundances, subaerial sinters could well be detected by TES. Where exposed, the shallow subsurface portions of these systems may be quite a lot larger (perhaps tens of square kms), although (as noted above) mineralization may be finely disseminated in the basement rock, making remote detection more difficult. Paleolake Basins. There are a large number of potential paleolake basins on Mars (inclusive of impact craters and volcanic calderas) that have been previously identified using Viking images. Most of these lie in the southern highlands beyond the l5 deg S constraint for 2001. However, deposits of paleolakes may offer the largest and most easily identified exopaleontological targets from orbit. Based on a variety of arguments, some workers have suggested that there was once an ancient ocean on the northern plains, and some sites of interest (potential shoreline terraces) fall within the 30 deg N constraint. From a paleontological standpoint the most interesting places of this type are terminal paleolake basins which are likely to have been both saline and alkaline. Models by Schaefer suggest such environments could be widespread on Mars. The conditions in terminal lake basin settings favor widespread chemical sedimentation, an important condition for microbial fossilization. Important lithological targets for a microbial fossil record in terminal lake basins include spring-deposited carbonates, shoreline cements, a wide variety of evaporite minerals and fine-grained detrital sediments including shales, marls, and water-lain volcanic ash deposits. In developing a strategy to explore for ancient hydrothermal deposits on Mars, we can learn from the methods that have been developed by explorationists to explore for economic mineral deposits on Earth. Due to their simple mineralogy, hydrothermal deposits can often be detected using remote sensing methods. Common thermal spring mineral assemblages include silica, carbonate, and various metallic oxides and sulfides. But there are also a number of diagnostic silicate minerals, including clays, formed by the hydrothermal alteration of country rocks. These hydrothermal minerals have characteristic spectral signatures that could be detected from Mars orbit using high resolution infrared remote sensing methods. In playa lake settings, evaporite deposits often form a predictable "bull's eye" pattern with carbonates being deposited in marginal basin areas, and sulfates and halides occurring progressively more basinward. The floors of some impact craters on Mars, such as "White Rock" and Bequeral Crater (see Oxia Palus NE, Site 148), have floor deposits that could be evaporites, inclusive of carbonates. Evaporite minerals possess characteristic spectral signatures in the infrared and could similarly be identified from Mars orbit using high resolution remote sensing methods. Clearly, utilization of TES data will be important for optimizing site selection for Exopaleontology, and every effort should be made to benefit from that data before a final decision is made.

Farmer, Jack↗