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NASA NTRS1996

Possible effects of protracted exposure on the additivity of risks from space radiations

Conventional radiation risk assessments are presently based on the additivity assumption. This assumption states that risks from individual components of a complex radiation field involving many different types of radiation can be added to yield the total risk of the complex radiation field. If the assumption is not correct, the summations and integrations performed to obtain the presently quoted risk estimates are not appropriate. This problem is particularly important in the area of space radiation risk evaluation because of the many different types of high- and low-LET radiation present in the galactic cosmic ray environment. For both low- and high-LET radiations at low enough dose rates, the present convention is that the addivity assumption holds. Mathematically, the total risk, Rtot is assumed to be Rtot = summation (i) Ri where the summation runs over the different types of radiation present. If the total dose (or fluence) from each component is such that the interaction between biological lesions caused by separate single track traversals is negligible within a given cell, it is presently considered to be reasonable to accept the additivity assumption. However, when the exposure is protracted over many cell doubling times (as will be the case for extended missions to the moon or Mars), the possibility exists that radiation effects that depend on multiple cellular events over a long time period, such as is probably the case in radiation-induced carcinogenesis, may not be additive in the above sense and the exposure interval may have to be included in the evaluation procedure. It is shown, however, that "inverse" dose-rate effects are not expected from intermediate LET radiations arising from the galactic cosmic ray environment due to the "sensitive-window-in-the-cell-cycle" hypothesis.

NASA Discipline Number 45-10↗

DOE OSTI2023

A practical approach to determine minimal quantum gate durations using amplitude-bounded quantum controls

Here, we present an iterative scheme to estimate the minimal duration in which a quantum gate can be realized while satisfying hardware constraints on the control pulse amplitudes. The scheme performs a sequence of unconstrained numerical optimal control cycles that each minimize the gate fidelity for a given gate duration alongside an additional penalty term for the control pulse amplitudes. After each cycle, the gate duration is adjusted based on the inverse of the resulting maximum control pulse amplitudes by re-scaling the dynamics to a new duration where control pulses satisfy the amplitude constraints. Those scaled controls then serve as an initial guess for the next unconstrained optimal control cycle, using the adjusted gate duration. We provide multiple numerical examples that each demonstrate fast convergence of the scheme toward a gate duration that is close to the quantum speed limit, given the control pulse amplitude bound. The proposed technique is agnostic to the underlying system and control Hamiltonian models, as well as the target unitary gate operation, making the time-scaling iteration an easy to implement and practically useful scheme for reducing the durations of quantum gate operations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Recent Developments of Thermal Protection Materials to Enable Lower Cost Space Missions

Introduction: Starting with the Commercial Crew Program, a new paradigm has emerged at NASA. Rather than designing rockets and spacecrafts for every mission optimized to achieve science, NASA has begun to use a service-based model and utilizing public-private partnership in developing the vehicles that can bring broader benefits as well as lower the cost for NASA missions. Commercial companies own and operate those vehicles. This allows NASA to not design missions from the bottom up, and has cost, risk, and schedule savings implications. On the other side, the constraints require meeting the requirements in terms of mass, volume, power, etc. By leveraging NASA developed technologies, commercial companies can quickly demonstrate the commercial mission concept, and, through technology transfer, adopt needed technology to address supply chain problems. A downside is that the technology has to be sufficiently mature to be transferred by NASA, which means that it requires significant investment, expertise, and time to develop. Space entities are focused on rapid development with an emphasis on manufacturing and integration innovation with reduced cost and schedule and quick entrance into the market. Thermal Protection Systems (TPS) are mission critical, but their development takes years, and involve access to arc jets or unique test facilities. Therefore, their development is both risky and investment heavy. NASA ARC developed several new TPS materials over the last decade (C-PICA, HEEET, 3MDCP, 3DMAT, ADEPT woven TPS) and brought them to high TPS maturity, making them enablers for commercials space missions from LEO, Lunar Sample Return, Mars, and Venus missions. LEO missions are relevant to future Mars missions due to the comparable entry conditions. External Partners' Missions: C-PICA is a recent improvement on NASA’s heritage PICA lightweight TPS ablator. C-PICA is now considered an enabling technology for New Frontiers and other NASA missions. C-PICA was infused into several missions from external partners. Varda Space Industries’ Winnebago-1 spacecraft successfully returned to Earth from LEO on Feb. 21st, 2024, using a C-PICA heatshield. Inversion Space’s Ray vehicle will test both ARC’s C-PICA and SIRCA TPS materials on a LEO return mission later in 2024. The Kentucky Re-Entry Probe Experiment (KREPE) is another example of a low-cost flight experiment to demonstrate the use of small entry capsules to gather data with three instrumented Kentucky Re-entry and Universal Payload System (KRUPS) capsules. NASA Arc provided C-PICA and Soft-PICA for two of the next KRUPS capsules scheduled to re-enter Earth from the ISS later in 2024. Finally, Rocket Lab’s low-cost mission to Venus, scheduled to launch in December 2024, will search for habitable conditions in Venus’ cloud layer, making use of NASA ARC provided HEEET insulation layer heat shield, and SIRCA backshell TPS materials. Future NASA Missions: NASA’s ability to help commercial missions can lead to future low-cost missions for several reasons: Competition encourages lower cost; technology maturation is now done at an integrated system level; and a common design architecture between commercial and scientific applications requires no specialized engineering design. From an engineering perspective, both of these commercial LEO capsules aforementioned are capable of a Mars entry; the commercial payload mut be replaced with as science payload. Finally, several NASA mission concepts, that could be candidates for future SIMPLEx program calls, such as VATMOS-SR and Nephele, both proposing to target the Venusian atmosphere, would make use of the HEEET insulation layer TPS for part of their heat shield.

TPS materials↗

NASA NTRSDate not supplied

Recent Developments of Thermal Protection Materials to Enable Lower Cost Space Missions

TPS materials↗

NASA NTRS1992

Numerical analysis of right-half plane zeros for a single-link manipulator

The purpose of this research is to further develop an understanding of how nonminimum phase zero location is affected by structural link design. As the demand for light-weight robots that can operate in a large workspace increases, the structural flexibility of the links become more of an issue in controls problems. When the objective is to accurately position the tip while the robot is actuated at the base, the system is nonminimum phase. One important characteristic of nonminimum phase systems is system zeros in the right half of the Laplace plane. The ability to pick the location of these nonminimum phase zeros would give the designer a new freedom similar to pole placement. The research targets a single-link manipulator operating in the horizontal plane and modeled as a Euler-Bernoulli beam with pinned-free end conditions. Using transfer matrix theory, one can consider link designs that have variable cross-sections along the length of the beam. A FORTRAN program was developed to determine the location of poles and zeros given the system model. The program was used to confirm previous research on nonminimum phase systems, and develop a relationship for designing linearly tapered links. The method allows the designer to choose the location of the first pole and zero and then defines the appropriate taper to match the desired locations. With the pole and zero location fixes, the designer can independently change the link's moment of inertia about its axis of rotation by adjusting the height of the beam. These results can be applied to inverse dynamic algorithms currently under development at Georgia Tech.

Girvin, Douglas Lynn↗

DOE OSTI2025

Geometric Interpretation of the Cluster Location Problem Part II: Application to the Pahala, Hawaii, Earthquake Sequence

In the companion “Theory” article, we presented a new framing of the seismic location problem in terms of differential geometry (Harris et al., 2025). From that viewpoint, we developed a “project and correct” approach for estimating the relative locations of earthquakes. Here, in this study, we use project and correct to estimate high-precision relative locations of events from an earthquake sequence beneath the town of Pahala, Hawaii, using high-precision correlation-derived picks. The sequence was active from 2020 through 2022 and produced many highly correlated signals at Hawaii Volcano Observatory (HVO) stations on the island of Hawaii. The data we inverted consisted of 2882 events with observations at 5 HVO stations. For comparison with the travel-time image, we also produced conventional hypocenter solutions using both the Bayesloc program (Myers et al., 2007, 2009) and a purpose-built double-difference code. There were obvious structural elements in the resulting image, the resolution of which we used to test the performance of the project and the correct algorithm. For the projection step, we first produced a 3D local basis using an singular value decomposition (SVD) of the 2882 groups of times. Projection of the travel-time vectors into this basis resulted in an image with structures similar to those produced by our conventional locators, but with distortion as predicted by theory. Removing the distortion requires an inverse operator generated from the metric tensor at the geometric centroid of the events. We compared two approaches to obtaining such an inverse operator. The first uses an estimate of the geographic centroid of the event cloud from the centroid of the travel-time data. The second approach uses the centroid of the conventionally produced locations. The first approach produces a corrected image very similar to the conventional results, but with a rotation. The corrected image produced using the conventionally derived centroid is a near-exact match to the conventional locations.

Dodge, Douglas A. [Lawrence Livermore National Lab↗

DOE OSTI2022

Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Abstract We develop a physics‐informed machine learning approach for large‐scale data assimilation and parameter estimation and apply it for estimating transmissivity and hydraulic head in the two‐dimensional steady‐state subsurface flow model of the Hanford Site given synthetic measurements of said variables. In our approach, we extend the physics‐informed conditional Karhunen‐Loéve expansion (PICKLE) method to modeling subsurface flow with unknown flux (Neumann) and varying head (time‐dependent Dirichlet) boundary conditions. We demonstrate that the PICKLE method is comparable in accuracy with the standard maximum a posteriori (MAP) method, but is significantly faster than MAP for large‐scale problems. Both methods use a mesh to discretize the computational domain. In MAP, the parameters and states are discretized on the mesh; therefore, the size of the MAP parameter estimation problem directly depends on the mesh size. In PICKLE, the mesh is used to evaluate the residuals of the governing equation, while the parameters and states are approximated by the truncated conditional Karhunen‐Loéve expansions with the number of parameters controlled by the smoothness of the parameter and state fields, and not by the mesh size. For a considered example, we demonstrate that the computational cost of PICKLE increases near linearly (as N 1.15 ) with the number of grid nodes N , while that of MAP increases much faster (as N 3.28 ). We also show that once trained for one set of Dirichlet boundary conditions (i.e., one river stage), the PICKLE method provides accurate estimates of the hydraulic head for any value of the Dirichlet boundary conditions (i.e., for any river stage).

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Topographic mapping using a monopulse SAR system

Terrain height variations in mountainous areas cause two problems in the radiometric correction of SAR images: the first being that the wrong elevation angle may be used in correcting for the radiometric variation of the antenna pattern; the second that the local incidence angle used in correcting the projection of the pixel area from slant range to ground range coordinates may vary from that given by the flat earth assumption. We propose a novel design of a SAR system which exploits the monopulse principle to determine the elevation angle and thus the height at the different parts of the image. The key element of such a phase monopulse system is an antenna, which can be divided into a lower and upper half in elevation using a monopulse comparator. In addition to the usual sum pattern, the elevation difference pattern can be generated by a -pi phase shift on one half of the antenna. From the ratios of images radiometrically modulated by the difference and sum antenna pattern in cross-track direction, we can derive the appropriate elevation angle at any point in the image. Together with the slant range we can calculate the height of the platform above this point using information on the antenna pointing and the platform attitude. This operation, repeated at many locations throughout the image, allows us to build up a topographic map of the height of the aircraft above each location. Inversion of this map, using the precisely determined aircraft altitude and the accurate flight path, leads to the actual topography of the imaged surface. The precise elevation of one point in the image could also be used to convert the height map to a topographic map. In this paper, we present design considerations for a corresponding airborne SAR system in X-Band and give estimates of the error due to system noise and azimuth ambiguities as well as the expected performance and precision in topographic mapping.

Zink, M.↗

NASA NTRS1997

Analysis of Hydrodynamic (Landau) Instability in Liquid-Propellant Combustion at Normal and Reduced Gravity

The burning of liquid propellants is a fundamental combustion problem that is applicable to various types of propulsion and energetic systems. The deflagration process is often rather complex, with vaporization and pyrolysis occurring at the liquid/gas interface and distributed combustion occurring either in the gas phase or in a spray. Nonetheless, there are realistic limiting cases in which combustion may be approximated by an overall reaction at the liquid/gas interface. In one such limit, the gas flame occurs under near-breakaway conditions, exerting little thermal or hydrodynamic influence on the burning propellant. In another such limit, distributed combustion occurs in an intrusive regime, the reaction zone lying closer to the liquid/gas interface than the length scale of any disturbance of interest. Finally, the liquid propellant may simply undergo exothermic decomposition at the surface without any significant distributed combustion, such as appears to occur in some types of HydroxylAmmonium Nitrate (HAN)-based liquid propellants at low pressures. Such limiting models have recently been formulated,thereby significantly generalizing earlier classical models that were originally introduced to study the hydrodynamic stability of a reactive liquid/gas interface. In all of these investigations, gravity appears explicitly and plays a significant role, along with surface tension, viscosity, and, in the more recent models, certain reaction-rate parameters associated with the pressure and temperature sensitivities of the reaction itself. In particular, these parameters determine the stability of the deflagration with respect to not only classical hydrodynamic disturbances, but also with respect to reactive/diffusive influences as well. Indeed, the inverse Froude number, representing the ratio of buoyant to inertial forces, appears explicitly in all of these models, and consequently, in the dispersion relation that determines the neutral stability boundaries beyond which steady, planar burning is unstable to nonsteady, and/or nonplanar (cellular) modes of burning. These instabilities thus lead to a number of interesting phenomena, such as the sloshing type of waves that have been observed in mixtures of HAN and TriEthanolAmmonium Nitrate (TEAN) with water. Although the Froude number was treated as an O(1) quantity in these studies, the limit of small inverse Froude number corresponding to the microgravity regime is increasingly of interest and can be treated explicitly, leading to various limiting forms of the models, the neutral stability boundaries, and, ultimately, the evolution equations that govern the nonlinear dynamics of the propagating reaction front. In the present work, we formally exploit this limiting parameter regime to compare some of the features of hydrodynamic instability of liquid-propellant combustion at reduced gravity with the same phenomenon at normal gravity.

Margolis, Stephen B.↗

DOE OSTI2025

The Principle of Maximum Conformality Correctly Resolves the Renormalization-Scheme-Dependence Problem

In this paper, we clarify a serious misinterpretation and consequent misuse of the Principle of Maximum Conformality (PMC), which also can serve as a mini-review of PMC. In a recently published article, P. M. Stevenson has claimed that “the PMC is ineffective and does nothing to resolve the renormalization-scheme-dependence problem”, concluding incorrectly that the success of PMC predictions is due to the PMC being a “laborious, ad hoc, and back-door” version of the Principle of Minimal Sensitivity (PMS). We show that such conclusions are incorrect, deriving from a misinterpretation of the PMC and an overestimation of the applicability of the PMS. The purpose of the PMC is to achieve precise fixed-order pQCD predictions, free from conventional renormalization schemes and scale ambiguities. We demonstrate that the PMC predictions satisfy all the self-consistency conditions of the renormalization group and standard renormalization-group invariance; the PMC predictions are thus independent of any initial choice of renormalization scheme and scale. The scheme independence of the PMC is also ensured by commensurate scale relations, which relate different observables to each other. Moreover, in the Abelian limit, the PMC dovetails into the well-known Gell-Mann–Low framework, a method universally revered for its precision in QED calculations. Due to the elimination of factorially divergent renormalon terms, the PMC series not only attains a convergence behavior far superior to that of its conventional counterparts but also deftly curtails any residual scale dependence caused by the unknown higher-order terms. This refined convergence, coupled with its robust suppression of residual uncertainties, furnishes a sound and reliable foundation for estimating the contributions from unknown higher-order terms. Anchored in the bedrock of standard renormalization-group invariance, the PMC simultaneously eradicates the factorial divergences and eliminates superfluous systematic errors, which inversely provides a good foundation for achieving high-precision pQCD predictions. Consequently, owing to its rigorous theoretical underpinnings, the PMC is eminently applicable to virtually all high-energy hadronic processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Final Report DE-FE0031785 Mohsen Ahmadian, Ph.D. Demonstration of Proof of Concept of a Multiphysics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks

Hydraulic fracturing has evolved into a multistep process with varying flow rates, carrier fluids (e.g., gel or slickwater), proppant loadings, and proppant grain sizes. As a result, primary recovery from a hydraulically fractured tight-oil reservoir is often a tiny fraction of the original oil in place, ranging between 5 and 10%. As stated in the FOA1990, “part of this problem is due to the inability of current well completion processes to effectively stimulate the entire reservoir volume in contact with the wellbore. Innovative technologies are needed that can help improve the effectiveness of reservoir completion methods, maximize stimulated reservoir volumes, and optimize recovery over the entire producing life span of a well”. We first need to enhance the current fracture diagnostic techniques to improve a well-completion design. However, detecting and delineating a subsurface hydraulic fracture is extremely difficult because the induced fracture network is only fractionally propped, and these propped fractures are generally very thin. Microseismic and tiltmeter monitoring techniques can provide information on the fracture extent but provide little or no information on the movement and final distribution of proppant or production fluids. On the other hand, electromagnetic (EM) imaging has shown the capability to monitor proppant distribution throughout the fracture area, especially in the presence of Electrically Active Proppants (EAPs). A previous EM survey of hydraulic fracturing at the Devine Fracture Pilot Site (DFPS) and subsequent EM code developments demonstrated this survey as a robust technique to remotely interrogate the extent of the EAP-filled hydraulic fracture during its propagation. The objectives of the project were threefold: (1) to capitalize on the material properties of an EAP to demonstrate remote monitoring of relative changes in pressure, pressure, and flow that are commonly encountered during production from a hydraulically fractured reservoir; (2) to evaluate EM imaging tools, to achieve Objective 1 in near real-time; and (3) to develop a multi-physics joint inversion approach to precisely predict flow patterns and physiochemical changes within an EAP-filled fracture network. This research project was built upon our previous work at the Devine Test Site managed by the Bureau of Economic Geology (BEG) at The University of Texas at Austin (UT-Austin). It also leveraged a significant investment from the Advanced Energy Consortium (AEC) to address the DOE's interest in subsurface flow, containment, and characterization by multiple signals. This three-year and three-month project succeeded in demonstrating the feasibility of a real-time dynamic fluid flow mapping technique at Technology Readiness Level 5 (TRL5) by utilizing a commercially available surface-based Controlled-Source Electromagnetic (CSEM) method (Objectives 1, 2). We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, the observed electric field in our study is influenced by bottomhole pressure, flow rate, and salinity, which is demonstrated by comparing these parameters with the electrical field potentials. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce the whole measured electric field magnitudes. Preliminary estimates showed that including Streaming Potential (SP) in our geophysical model is likely needed to reduce the simulation misfit.

02 PETROLEUM↗

DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging

Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include seismic exploration of the Earth’s subsurface, acoustic imaging and nondestructive testing (NDT) in material science, and ultrasound computed tomography (USCT) in medicine. Current approaches for solving CWI problems can be divided into two categories: those rooted in traditional physics and those based on deep learning. Physics-based methods stand out for their ability to provide high-resolution and quantitatively accurate estimates of acoustic properties within the medium. However, they can be computationally intensive and are susceptible to ill-posedness and nonconvexity typical of CWI problems. Machine learning (ML)-based computational methods have recently emerged, offering a different perspective to address these challenges. Diverse scientific communities have independently pursued the integration of deep learning in CWI. This review discusses how contemporary scientific ML techniques, and deep neural networks in particular, have been developed to enhance and integrate with traditional physics-based methods for solving CWI problems. We present a structured framework that consolidates existing research spanning multiple domains, including computational imaging, wave physics, and data science. This study concludes with important lessons learned from existing ML-based methods and identifies technical hurdles and emerging trends through a systematic analysis of the extensive literature on this topic.

42 ENGINEERING↗

DOE OSTI2022

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Fluid – Fluid Interfacial Area and Its Impact on Relative Permeability - A Pore Network Modeling Study

Abstract Relative permeability (kr) is commonly modeled as an empirical function of phase saturation. Although current empirical models can provide a good match of one or two measured relative permeabilities using saturation alone, they are unable to predict relative permeabilities well when there is hysteresis or when physical properties such as wettability change. Further, current models often result in relative permeability discontinuities that can cause convergence and accuracy problems in simulation. To overcome these problems, recent research has modeled relative permeability as a state function of both saturation (S) and phase connectivity (X). Pore network modeling (PNM) data, however, shows small differences in relative permeability for the same S-X value when approached from a different flow direction. This paper examines the impact of one additional Minkowski parameter (Mecke and Arns, 2005), the fluid-fluid interfacial area, on relative permeability to identify if that satisfactorily explains this discrepancy. We calculate the total fluid-fluid interfacial areas (IA) during two-phase (oil/water) flow in porous media using pore network modeling. The area is calculated from PNM simulations using the areas associated with corners and throats in pore elements of different shapes. The pore network is modeled after a Bentheimer sandstone, using square, triangular, and circular pore shapes. Simulations were conducted for numerous primary drainage and imbibition cycles at a constant contact angle of 0° for the wetting phase. Simultaneous measurements of capillary pressure, relative permeability, saturation, and phase connectivity are made for each displacement. Fluid-fluid interfacial area is calculated from the PNM capillary pressure, the fluid location in the pore elements, and the pore element dimensional data. The results show that differences in the relative permeability at the same (S,X) point is explained well by differences in the fluid-fluid interfacial area (IA). That is, for a larger change in IA at these intersection points, the permeability difference is greater. That difference in relative permeability approaches zero as the difference in IA approaches zero. This confirms that relative permeability can be modeled better as a unique function of S, X, and IA. The results also show that an increase in IA restricts flow decreasing the nonwetting (oil) phase permeability. This decrease is caused by an increase in the throat area fraction compared to the corner area as the total area IA increases. The wetting phase relative permeability, however, shows the inverse trend, in that its relative permeability is greater when IA becomes larger owing to a greater fraction of the total area associated with the corners. The area IA, however, impacts the nonwetting phase relative permeability more than the wetting phase relative permeability. Corner flow improves the wetting phase relative permeability because the wetting phase is continuous there. Finally, a sensitivity analysis shows that relative permeability a is more sensitive to change in S than they are for IA for the case studied implying that if only two parameters are used to model relative permeability it is better to choose S and X.

Engineering↗

NASA NTRS2001

Our Sun V: A Bright Young Sun Consistent with Helioseismology and Warm Temperatures on Ancient Earth and Mars

The relatively warm temperatures required on early Earth and Mars have been difficult to account for with warming from greenhouse gases. A slightly more massive young Sun would be brighter than predicted by the standard solar model, simultaneously resolving this problem for both Earth and Mars. We computed high-precision solar models with seven initial masses, from Mi = 1.01 to 1.07 solar mass - the latter being the maximum permitted if the early Earth is not to lose its water via a moist greenhouse effect. The relatively modest early mass loss that is required remains consistent with observational limits on mass loss from young stars and with estimates of the past solar wind obtained from lunar rocks. We considered three types of mass loss rates: (1) a reasonable choice of a simple exponential decline, (2) an extreme step-function case that gives the maximum effect consistent with observations, and (3) the radical case of a linear decline which is inconsistent with the solar wind mass loss estimates from lunar rocks. Our computations demonstrated that mass loss leaves a fingerprint oil the Sun's internal structure large enough to be detectable with helioseismic observations. All of our mass-losing solar models were consistent with the helioseismic observations; in fact, our preferred mass-losing cases were in marginally better agreement with the helioseismology than the standard solar model was, although this difference was smaller than the effects of other uncertainties in the input physics and in the solar composition. Mass loss has only a relatively minor effect on the predicted lithium depletion; the major portion of the solar lithium depletion must still be due to rotational mixing. Thus the modest mass loss cases considered here cannot be ruled out by observed lithium depletions. For the three mass loss types considered, the preferred initial masses were 1.07 solar mass for the exponential case and 1.04 solar mass for the step-function and linear cases; all of these provided high enough solar fluxes at Mars 3.8 Gyr ago to be consistent with the existence of liquid water. For a more massive early Sun, the planets would have had to be closer to the young Sun in order to end up in their present orbits; the orbital radii of the planets would vary inversely with the solar mass. Both of these effects contribute to the fact that the early solar flux at the planets would have been considerably higher than that of the standard solar model at that time. In fact, the 1.07 solar mass exponential case has a flux at birth 5% higher than the present solar flux, while the radical 1.04 solar mass linear case has a nearly constant flux over the first 3 Gyr only about 10% lower than at present. The early solar evolution would be in the opposite direction in the H-R diagram to that of the standard Sun.

Sackmann, I.-Juliana↗

NASA NTRS2000

Characterization of Electronic Materials HgZnSe and HgZnTe Using Innovative and Conventional Techniques

HgZnSe and HgZnTe are electronic materials of interest for potential IR detector and focal plane array applications due to their improved strength and compositional stability over HgCdTe, but they are difficult to grow on Earth and to fully characterize. Conventional contact methods of characterization, such as Hall and van der Paw, although adequate for many situations are typically labor intensive and not entirely suitable where only very small samples are available. To adequately characterize and compare properties of electronic materials grown in low earth orbit with those grown on Earth, innovative techniques are needed that complement existing methods. This paper describes the implementation and test results of a unique non-contact method of characterizing uniformity, mobility, and carrier concentration together with results from conventional methods applied to HgZnSe and HgZnTe. The innovative method has advantages over conventional contact methods since it circumvents problems of possible contamination from alloying electrical contacts to a sample and also has the capability to map a sample. Non- destructive mapping, the determination of the carrier concentration and mobility at each place on a sample, provides a means to quantitatively compare, at high spatial resolution, effects of microgravity on electronic properties and uniformity of electronic materials grown in low-Earth orbit with Earth grown materials. The mapping technique described here uses a 1mm diameter polarized beam of radiation to probe the sample. Activation of a magnetic field, in which the sample is placed, causes the plane of polarization of the probe beam to rotate. This Faraday rotation is a function of the free carrier concentration and the band parameters of the material. Maps of carrier concentration, mobility, and transmission generated from measurements of the Faraday rotation angles over the temperature range from 300K to 77K will be presented. New information on band parameters, obtained by combining results from conventional Hall measurements of the free carrier concentration with Faraday rotation measurements, will also be presented. One example of how this type of information was derived is illustrated in the following figure which shows Faraday rotation vs wavelength modeled for Hg(l-x)ZnxSe at a temperature of 300K and x=0.07. The plasma contribution, total Faraday rotation, and interband contribution to the Faraday rotation, are designated in the Figure as del(p), FR tot, and del(i) respectively. Experimentally measured values of FR tot, each indicated by + , agree acceptably well with the model at the probe wavelength of 10.6 microns. The model shows that at the probe wavelength, practically all the rotation is due to the plasma component, which can be expressed as delta(sub p)= 2pi(e(sup 3))NBL/c(sup 2)nm*(sup 2) omega(sup 2). In this equation, delta(sub p) is the rotation angle due to the free carrier plasma, N is the free carrier concentration, B the magnetic field strength, L the thickness of the sample, n the index of refraction, omega the probe radiation frequency, c the speed of light, e the electron charge, and m* the effective mass. A measurement of N by conventional techniques, combined with a measurement of the Faraday rotation angle allows m* to be accurately determined since it is an inverse square function.

Tanton, George↗

DOE OSTI2020

Impact of K-Optimization on Trap Concentration in (Ag,Cu)(In,Ga)Se 2 Solar Cells

Recent progress has been made in improving efficiency in Cu(In,Ga)Se 2 (CIGS) absorbers with steady increases in peak efficiency. One way this has been achieved is by adding Ag to CIGS (ACIGS) to achieve higher V OC . However, these efficiencies are still well below the Shockley-Queisser efficiency limit, and traps acting as recombination centers and compensating centers are one thing limiting the solar efficiency. Past research in CIGS has shown that alkali treatment can improve the efficiency and metastability problems in CIGS, but less is understood about the role of alkali treatments in ACIGS. Here, we investigate the impact of potassium in ACIGS through its impact on trap incorporation and minority carrier lifetime. The samples in this study were grown in a roll-to-roll coater with Mo, ACIGS, CdS, and ZnO structure. Both cells were grown identically except the second (K-optimized) cell was grown with increased K-doping of the Mo contact and was more Cu-poor near the surface to optimize the K profile. This resulted in an efficiency increase from 16.8% to 18.7% for the K-optimized cell, which was mostly due to a 65 mV V OC increase. The doping profile showed a 2X increase in acceptor concentration of the K-optimized cell (2.5×10 15 cm -3 ) which suggests that the K was better incorporated into the ACIGS after these optimizations. To characterize the traps in these cells, deep level transient and optical spectroscopy were used. The DLOS measurements showed an EV+0.98 eV trap whose concentration was reduced 10X in the K-optimized cell (4×10 14 cm -3 ). This is consistent with previous results from the alkali treatment in CIGS, which also showed a decrease in near-conduction band trap concentration [1], but the reduction was larger than previous studies possibly indicating the combination of K and Cu-poor surface may both have aided in reducing the EV+0.98 eV trap concentration. The other primary trap is the mid-gap trap (EV+0.58 eV), which was quantified using DLTS. Its concentration decreased from 9×10 13 cm -3 to 4×10 13 cm -3 in the K-optimized sample, which is a 2X reduction. Previous studies have shown this trap is likely an efficient recombination center [2], which makes sense because it is near mid-gap. This trap has also been associated with V OC instability and reduction, so reducing this trap concentration is essential to achieve high V OC and cell efficiency. To help confirm this association, time-resolved photoluminescence measurements have shown in this sample set and a previous study that the minority carrier lifetime (19 ns baseline to 56 ns K-optimized) and this EV+0.56 eV trap concentration are inversely proportional, which would be expected for a recombination-limited carrier lifetime. The K optimization of ACIGS results in significantly improved cell efficiency and reduced trap concentrations that correlate with the improved material and electrical properties. We will report on this and the impact of the K optimization on the cell metastability.

14 SOLAR ENERGY↗