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At least 235 records · Page 13

Developmental assembly of multi-component polymer systems through interconnected synthetic gene networks in vitro

Abstract Living cells regulate the dynamics of developmental events through interconnected signaling systems that activate and deactivate inert precursors. This suggests that similarly, synthetic biomaterials could be designed to develop over time by using chemical reaction networks to regulate the availability of assembling components. Here we demonstrate how the sequential activation or deactivation of distinct DNA building blocks can be modularly coordinated to form distinct populations of self-assembling polymers using a transcriptional signaling cascade of synthetic genes. Our building blocks are DNA tiles that polymerize into nanotubes, and whose assembly can be controlled by RNA molecules produced by synthetic genes that target the tile interaction domains. To achieve different RNA production rates, we use a strategy based on promoter “nicking” and strand displacement. By changing the way the genes are cascaded and the RNA levels, we demonstrate that we can obtain spatially and temporally different outcomes in nanotube assembly, including random DNA polymers, block polymers, and as well as distinct autonomous formation and dissolution of distinct polymer populations. Our work demonstrates a way to construct autonomous supramolecular materials whose properties depend on the timing of molecular instructions for self-assembly, and can be immediately extended to a variety of other nucleic acid circuits and assemblies.

Science & Technology - Other Topics↗

Casein kinase II protein kinase is bound to lamina-matrix and phosphorylates lamin-like protein in isolated pea nuclei

A casein kinase II (CK II)-like protein kinase was identified and partially isolated from a purified envelope-matrix fraction of pea (Pisum sativum L.) nuclei. When [gamma-32P]ATP was directly added to the envelope-matrix preparation, the three most heavily labeled protein bands had molecular masses near 71, 48, and 46 kDa. Protein kinases were removed from the preparation by sequential extraction with Triton X-100, EGTA, 0.3 M NaCl, and a pH 10.5 buffer, but an active kinase still remained bound to the remaining lamina-matrix fraction after these treatments. This kinase had properties resembling CK II kinases previously characterized from animal and plant sources: it preferred casein as an artificial substrate, could use GTP as efficiently as ATP as the phosphoryl donor, was stimulated by spermine, was calcium independent, and had a catalytic subunit of 36 kDa. Some animal and plant CK II kinases have regulatory subunits near 29 kDa, and a lamina-matrix-bound protein of this molecular mass was recognized on immunoblot by anti-Drosophila CK II polyclonal antibodies. Also found associated with the envelope-matrix fraction of pea nuclei were p34cdc2-like and Ca(2+)-dependent protein kinases, but their properties could not account for the protein kinase activity bound to the lamina. The 71-kDa substrate of the CK II-like kinase was lamin A-like, both in its molecular mass and in its cross-reactivity with anti-intermediate filament antibodies. Lamin phosphorylation is considered a crucial early step in the entry of cells into mitosis, so lamina-bound CK II kinases may be important control points for cellular proliferation.

NASA Discipline Plant Biology↗

Characterizing parallel file-access patterns on a large-scale multiprocessor

Rapid increases in the computational speeds of multiprocessors have not been matched by corresponding performance enhancements in the I/O subsystem. To satisfy the large and growing I/O requirements of some parallel scientific applications, we need parallel file systems that can provide high-bandwidth and high-volume data transfer between the I/O subsystem and thousands of processors. Design of such high-performance parallel file systems depends on a thorough grasp of the expected workload. So far there have been no comprehensive usage studies of multiprocessor file systems. Our CHARISMA project intends to fill this void. The first results from our study involve an iPSC/860 at NASA Ames. This paper presents results from a different platform, the CM-5 at the National Center for Supercomputing Applications. The CHARISMA studies are unique because we collect information about every individual read and write request and about the entire mix of applications running on the machines. The results of our trace analysis lead to recommendations for parallel file system design. First the file system should support efficient concurrent access to many files, and I/O requests from many jobs under varying load conditions. Second, it must efficiently manage large files kept open for long periods. Third, it should expect to see small requests predominantly sequential access patterns, application-wide synchronous access, no concurrent file-sharing between jobs appreciable byte and block sharing between processes within jobs, and strong interprocess locality. Finally, the trace data suggest that node-level write caches and collective I/O request interfaces may be useful in certain environments.

Purakayastha, Apratim↗

Neutron skins probed in proton knockout from neutron-rich nuclei

Proton-induced quasifree knockout reactions provide a powerful probe of nuclear single-particle structure and reaction dynamics in both stable and neutron-rich nuclei. Here, in this work, we develop a unified theoretical framework for the calculation of inclusive (𝑝, 2⁢𝑝) and sequential (𝑝, 3⁢𝑝) reaction cross sections and fragment momentum distributions at intermediate and relativistic energies. The approach is based on a probabilistic extension of Glauber multiple-scattering theory combined with microscopic nuclear densities obtained from Hartree-Fock-Bogoliubov calculations using Skyrme energy-density functionals. We focus in particular on the sensitivity of total cross sections and longitudinal momentum dispersions to neutron-skin thickness along isotopic chains. Our results indicate that both (𝑝, 2⁢𝑝) and (𝑝, 3⁢𝑝) reactions exhibit a systematic decrease of cross section and momentum width with increasing neutron excess, reflecting enhanced attenuation and surface bias induced by neutron skins. The effect is significantly stronger for two-proton removal, suggesting that (𝑝, 3⁢𝑝) reactions may offer enhanced sensitivity to isovector nuclear structure. These findings establish proton-induced knockout reactions as complementary hadronic probes of neutron skins and the density dependence of the nuclear symmetry energy.

direct reactions↗

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

Comparison of First-Come First-Served and Optimization Based Scheduling Algorithms for Integrated Departure and Arrival Management

Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA) are investigating scheduling algorithms that will be a part of an integrated arrival and departure management system. Inha University, one of the Korean collaborators of KARI, developed an Extended First-Come First-Served (EFCFS) algorithm that is robust and efficient. However, since the EFCFS algorithm sequentially computes the schedule based on priority, the end results may not be optimal for system efficiency. The approach based on Mixed Integer Linear Programming (MILP) originally developed by NASA and modified by KARI is known to produce better schedules at the expense of computational cost. In this paper, the two different scheduling approaches are compared using common traffic scenarios and constraints at Incheon International Airport. Capabilities to apply weight class based wake turbulence runway separation minima and Miles-in-Trail (MIT) restrictions at selected meter fixes are added to the previously developed EFCFS scheduler. Based on historic data, 40 departures and 20 arrivals are chosen in a one-hour period and 100 scenarios were created by randomly assigning gate numbers, gate departure times, and runway landing times. With the current runway separation requirements, MILP resulted in about ten to twenty percent smaller average delays depending on the constraints. With artificially increased separation minima, the difference between MILP and EFCFS became more noticeable. However, the EFCFS was about ten times faster with smaller variations among different scenarios and constraints. The comparison suggests that the MILP-based algorithm has a small advantage at the current traffic level; however, has potential to be more effective in higher demand or severe weather situations. The EFCFS algorithm may be better suited for real-time applications or investigating larger scale scheduling problems.

air traffic optimization↗

Long-term changes in reflectivity and larger scale motions in the atmospheres of Jupiter and Saturn

A multi-color, broad-band photographic program for monitoring atmospheric variability of Jupiter and Saturn with the 61-cm, f/75 telescope was continued. The archivial product consists of approximately 20 sequential images on 3 1/4 x 4 1/4 glass plates with a plate scale of 4.53 arc sec/mm. An eleven-step sensitometric wedge, recorded times of acquisition, and fiducial marks which determine the orientation of the plate, are recorded on each individual plate. This allows accurate positional measurements, as well as detailed relative surface brightness determinations. Detailed measurements of the Red Spot are being utilized in a study of zonal velocity variation and the ability to predict the longitude of the Red Spot during the Galileo mission. An ongoing 5-color series of Saturn has been maintained to map the seasonal changes in the belt-zone reflectivity. Digitization of a series of blue images containing the Red Spot and a series of red and blue images excluding the Red Spot are being processed and reduced to normalized surface brightness maps. This data is being utilized to map time-dependent brightness variations of selected features, belts, and ones.

Beebe, R. F.↗

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyse this dependence using multiple machine learning methods and a dataset of >200 000 nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence in diverse non-axisymmetric geometries. The dataset is generated using a large collection of both optimised and randomly generated stellarator equilibria. At fixed gradients and other input parameters, the turbulent heat flux varies between geometries by several orders of magnitude. Trends are apparent among the configurations with particularly high or particularly low heat flux. Regression and classification techniques from machine learning are then applied to extract patterns in the dataset. Due to a symmetry of the gyrokinetic equation, the heat flux and regressions thereof should be invariant to translations of the raw features in the parallel coordinate, similar to translation invariance in computer vision applications. Multiple regression models including convolutional neural networks (CNNs) and decision trees can achieve reasonable predictive power for the heat flux in held-out test configurations, with highest accuracy for the CNNs. Using Spearman correlation, sequential feature selection and Shapley values to measure feature importance, it is consistently found that the most important geometric lever on the heat flux is the flux surface compression in regions of bad curvature. The second most important geometric feature relates to the magnitude of geodesic curvature. These two features align remarkably with surrogates that have been proposed based on theory, while the methods here allow a natural extension to more features for increased accuracy. The dataset, released with this publication, may also be used to test other proposed surrogates, and we find that many previously published proxies do correlate well with both the heat flux and stability boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Importance of Semi-Major Axis Knowledge in the Determination of Near-Circular Orbits

Modem orbit determination has mostly been accomplished using Cartesian coordinates. This usage has carried over in recent years to the use of GPS for satellite orbit determination. The unprecedented positioning accuracy of GPS has tended to focus attention more on the system's capability to locate the spacecraft's location at a particular epoch than on its accuracy in determination of the orbit, per se. As is well-known, the latter depends on a coordinated knowledge of position, velocity, and the correlation between their errors. Failure to determine a properly coordinated position/velocity state vector at a given epoch can lead to an epoch state that does not propagate well, and/or may not be usable for the execution of orbit adjustment maneuvers. For the quite common case of near-circular orbits, the degree to which position and velocity estimates are properly coordinated is largely captured by the error in semi-major axis (SMA) they jointly produce. Figure 1 depicts the relationships among radius error, speed error, and their correlation which exist for a typical low altitude Earth orbit. Two familiar consequences are the relationship Figure 1 shows are the following: (1) downrange position error grows at the per orbit rate of 3(pi) times the SMA error; (2) a velocity change imparted to the orbit will have an error of (pi) divided by the orbit period times the SMA error. A less familiar consequence occurs in the problem of initializing the covariance matrix for a sequential orbit determination filter. An initial covariance consistent with orbital dynamics should be used if the covariance is to propagate well. Properly accounting for the SMA error of the initial state in the construction of the initial covariance accomplishes half of this objective, by specifying the partition of the covariance corresponding to down-track position and radial velocity errors. The remainder of the in-plane covariance partition may be specified in terms of the flight path angle error of the initial state. Figure 2 illustrates the effect of properly and not properly initializing a covariance. This figure was produced by propagating the covariance shown on the plot, without process noise, in a circular low Earth orbit whose period is 5828.5 seconds. The upper subplot, in which the proper relationships among position, velocity, and their correlation has been used, shows overall error growth, in terms of the standard deviations of the inertial position coordinates, of about half of the lower subplot, whose initial covariance was based on other considerations.

Carpenter, J. Russell↗

Bacterial community dynamics as a result of growth-yield trade-off and multispecies metabolic interactions toward understanding the gut biofilm niche

Abstract Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.

Microbiology↗

Bit-Serial Adder Based on Quantum Dots

A proposed integrated circuit based on quantum-dot cellular automata (QCA) would function as a bit-serial adder. This circuit would serve as a prototype building block for demonstrating the feasibility of quantum-dots computing and for the further development of increasingly complex and increasingly capable quantum-dots computing circuits. QCA-based bit-serial adders would be especially useful in that they would enable the development of highly parallel and systolic processors for implementing fast Fourier, cosine, Hartley, and wavelet transforms. The proposed circuit would complement the QCA-based circuits described in "Implementing Permutation Matrices by Use of Quantum Dots" (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42 and "Compact Interconnection Networks Based on Quantum Dots" (NPO-20855), which appears elsewhere in this issue. Those articles described the limitations of very-large-scale-integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCA-based signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. To enable a meaningful description of the proposed bit-serial adder, it is necessary to further recapitulate the description of a quantum-dot cellular automation from the first-mentioned prior article: A quantum-dot cellular automaton contains four quantum dots positioned at the corners of a square cell. The cell contains two extra mobile electrons that can tunnel (in the quantum-mechanical sense) between neighboring dots within the cell. The Coulomb repulsion between the two electrons tends to make them occupy antipodal dots in the cell. For an isolated cell, there are two energetically equivalent arrangements (denoted polarization states) of the extra electrons. The cell polarization is used to encode binary information. Because the polarization of a nonisolated cell depends on Coulomb-repulsion interactions with neighboring cells, universal logic gates and binary wires could be constructed, in principle, by arraying QCA of suitable design in suitable patterns. Again, for reasons too complex to describe here, in order to ensure accuracy and timeliness of the output of a QCA array, it is necessary to resort to an adiabatic switching scheme in which the QCA array is divided into subarrays, each controlled by a different phase of a multiphase clock signal. In this scheme, each subarray is given time to perform its computation, then its state is frozen by raising its inter-dot potential barriers and its output is fed as the input to the successor subarray. The successor subarray is kept in an unpolarized state so it does not influence the calculation of preceding subarray. Such a clocking scheme is consistent with pipeline computation in the sense that each different subarray can perform a different part of an overall computation. In other words, QCA arrays are inherently suitable for pipeline and, moreover, systolic computations. This sequential or pipeline aspect of QCA would be utilized in the proposed bit-serial adders.

Fijany, Amir↗

Structural Distortions and Uniaxial Negative Thermal Expansion in the Polar Dion–Jacobson Oxide RbNdTa 2 O 7

We provide deeper insight into the crystal structures, sequential structural phase transitions (I2cm → Cmce → I4/mcm → P4/mmm), thermal expansion, and electronic properties of the n = 2 Dion–Jacobson polar oxide RbNdTa 2 O 7 , through X-ray powder diffraction, neutron powder diffraction, Raman studies, and density functional theory calculations. We observed a uniaxial negative thermal expansion (NTE) across the first-order transition, I2cm → Cmce, where the unit cell contracts along the c-axis, which is driven by a contraction of the NdTa 2 O 6 layer. Here, this NTE occurs within the temperature range of the first-order phase transition and contrasts with the corkscrew mechanism typically observed in Ruddlesden–Popper phases. In RbNdTa 2 O 7 , the I2cm (hybrid improper ferroelectric) → Cmce (antipolar) transition involves crucial changes in the bond lengths of Nd and Ta polyhedra, coupled with polar to antipolar displacement of the Nd ions, leading to a net contraction in the NdTa 2 O 6 layer along the c-axis, while preserving the overall octahedral tilting magnitude. This transition highlights the intricate interplay between the Nd and Ta coordination and the associated TaO 6 distortions. Temperature-dependent Raman spectra analysis further confirms the first-order structural transition and associated NTE, providing evidence for increased bond stiffness across this transition. Additionally, using neutron powder diffraction, we have determined that the transition I4/mcm → P4/mmm occurs at approximately 1150 K. Finally, we have calculated from DFT + U, the partial density of states, the energy bandgaps, and effective masses of the charge carriers of the polar ground structure.

Chemical structure↗

Collagenase-3 binds to a specific receptor and requires the low density lipoprotein receptor-related protein for internalization

We have previously identified a specific receptor for collagenase-3 that mediates the binding, internalization, and degradation of this ligand in UMR 106-01 rat osteoblastic osteosarcoma cells. In the present study, we show that collagenase-3 binding is calcium-dependent and occurs in a variety of cell types, including osteoblastic and fibroblastic cells. We also present evidence supporting a two-step mechanism of collagenase-3 binding and internalization involving both a specific collagenase-3 receptor and the low density lipoprotein receptor-related protein. Ligand blot analysis shows that (125)I-collagenase-3 binds specifically to two proteins ( approximately 170 kDa and approximately 600 kDa) present in UMR 106-01 cells. Western blotting identified the 600-kDa protein as the low density lipoprotein receptor-related protein. Our data suggest that the 170-kDa protein is a specific collagenase-3 receptor. Low density lipoprotein receptor-related protein-null mouse embryo fibroblasts bind but fail to internalize collagenase-3, whereas UMR 106-01 and wild-type mouse embryo fibroblasts bind and internalize collagenase-3. Internalization, but not binding, is inhibited by the 39-kDa receptor-associated protein. We conclude that the internalization of collagenase-3 requires the participation of the low density lipoprotein receptor-related protein and propose a model in which the cell surface interaction of this ligand requires a sequential contribution from two receptors, with the collagenase-3 receptor acting as a high affinity primary binding site and the low density lipoprotein receptor-related protein mediating internalization.

NASA Discipline Musculoskeletal↗

Predicting the X-Ray Spectra of Stellar-mass Black Holes from Simulations

We describe results from a new technique for the prediction of complete, self-consistent X-ray spectra from three-dimensional general relativistic magnetohydrodynamic (GRMHD) simulations of black hole accretion flows. Density and cooling rate data from a harm3d GRMHD simulation are post-processed by an improved version of the Monte Carlo radiation transport code pandurata (in the corona) and the Feautrier solver PTRANSX (in the disk), with xstar subroutines. The codes are run in a sequential, iterative fashion to achieve globally energy-conserving and self-consistent radiation fields, temperature maps, and photoionization equilibria. The output is the X-ray spectrum as seen by a distant observer, including features, such as the Fe Kα emission line and corresponding K-edge absorption trough, due to disk reprocessing of coronal power. For the example cases we consider—a non-rotating 10 M(sub ⊙) black hole with solar abundances, accreting at 0.01, 0.03, 0.1, or 0.3 Eddington—we find spectra resembling actual observations of stellar-mass black holes in the soft or steep power-law state: broad thermal peaks (at 1–3 keV), steep power laws extending to high energy (Γ = 2.7–4.5), and prominent, asymmetric Fe Kα emission lines with equivalent widths in the range 40–400 eV (larger EW at lower accretion rates). By starting with simulation data, we obviate the need for parameterized descriptions of the accretion flow geometry—no a priori specification of the corona's shape or flux, or the disk temperature or density, etc., is needed. Instead, we apply the relevant physical principles to simulation output using appropriate numerical techniques; this procedure allows us to calculate inclination-dependent spectra after choosing only a small number of physically meaningful parameters: black hole mass and spin, accretion rate, and elemental abundances.

Kinch, Brooks E.↗

Individual thermal profiles as a basis for comfort improvement in space and other environments

BACKGROUND: The development of individualized countermeasures to address problems in thermoregulation is of considerable importance for humans in space and other extreme environments. A methodology is presented for evaluating minimal/maximal heat flux from the total human body and specific body zones, and for assessing individual differences in the efficiency of heat exchange from these body areas. The goal is to apply this information to the design of individualized protective equipment. METHODS: A multi-compartment conductive plastic tubing liquid cooling/warming garment (LCWG) was developed. Inlet water temperatures of 8-45 degrees C were imposed sequentially to specific body areas while the remainder of the garment was maintained at 33 degrees C. RESULTS: There were significant differences in heat exchange level among body zones in both the 8 degrees and 45 degrees C temperature conditions (p < 0.001). The greatest amount of heat was absorbed/released by the following areas: thighs (8 degrees C: -2.12 +/- 0.14 kcal min(-1); 45 degrees C: +1.58 +/- 0.23); torso (8 degrees C: -2.12 +/- 0.13 kcal min(-1); 45 degrees C: +1.31 +/- 0.27); calves (8 degrees C: -1.59 +/- 0.26 kcal min(-1); 45 degrees C: +1.53 +/- 0.24); and forearms (8 degrees C: -1.67 +/- 0.29 kcal x min(-1); 45 degrees C: +1.45 +/- 0.20). These are primarily zones with relatively large muscle mass and adipose tissue. Calculation of absorption/release heat rates standardized per unit tube length and flow rate instead of zonal surface area covered showed that there was significantly greater heat transfer in the head, hands, and feet (p < 0.001). The areas in which there was considerable between-subject variability in rates of heat transfer and thus most informative for individual profile design were the torso, thighs, shoulders, and calves or forearms. CONCLUSIONS: The methodology developed is sensitive to individual differences in the process of heat exchange and variations in different body areas, depending on their size and tissue mass content. The design of individual thermal profiles is feasible for better comfort of astronauts on long-duration missions and personnel in other extreme environments.

NASA Discipline Life Sciences Technologies↗

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm and Reduced Parallel Diagonal Dominant (RPDD) algorithm have been carefully studied on different parallel platforms for different applications, and a NASA simulation code developed by Man M. Rai and his colleagues has been parallelized and implemented based on data dependency analysis. These achievements are addressed in detail in the paper.

Sun, Xian-He↗

Light-induced electron spin qubit coherences in the purple bacteria reaction center protein

Photosynthetic reaction center proteins (RCs) provide ideal model systems for studying quantum entanglement between multiple spins, a quantum mechanical phenomenon wherein the properties of the entangled particles become inherently correlated. Following light-generated sequential electron transfer, RCs generate spin-correlated radical pairs (SCRPs), also referred to as entangled spin qubit (radical) pairs (SQPs). Understanding and controlling coherence mechanisms in SCRP/SQPs is important for realizing practical uses of electron spin qubits in quantum sensing applications. The bacterial RC (bRC) provides an experimental system for exploring quantum effects in the SCRP P 865 + Q A − , where P 865 , a special pair of bacteriochlorophylls, is the primary donor, and Q A is the primary quinone acceptor. In this study, we focus on understanding how local molecular environments and isotopic substitution, particularly deuteration, influence spin coherence times (T M ). Using high-frequency electron paramagnetic resonance (EPR) spectroscopy, we observed that the local environment surrounding P 865 and Q A plays a significant role in determining T M . Our findings show that while deuteration led to a modest increase in T M , particularly at low temperatures, but the effect was substantially smaller than predicted by classical nuclear spin diffusion alone. This result is in contrast to our previous study of the photosystem I (PSI) RC, where no increase in T M was observed upon deuteration. Theoretical modeling identified several methyl groups at key distances from the spin centers of both bRC and PSI, and methyl group tunneling at low temperatures has been previously suggested as a mechanism for enhanced spin decoherence. Additionally, our study revealed a strong dependence of spin coherence on the orientation of the external magnetic field, highlighting the influence of the protein microenvironment on spin dynamics. In conclusion, these results offer new insights for optimizing coherence times in quantum system design for quantum information science and sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Acid Alteration of Clay Minerals With Implication for Mars’ Surface Processes

The co-occurrence of phyllosilicates (clays) and sulfate stratigraphies at many locations on Mars are associated with a sharp change in surface conditions from neutral/alkaline pH during the Noachian (4.1-3.7 Ga) which favored the formation of clays to acidic conditions during the Hesperian (3.7-2.9 Ga) which favored the formation of sulfates. Yet, if these two contrasting geosystems were temporarily sequential, it is unknown how the Hesperian acidic conditions altered the previously formed clay units. We performed laboratory batch experiments to fingerprint the diagnostic features produced during interactions of Mars-analog clays and acidic solutions. Two clays, and silicon (IV) oxide, were reacted with solution of either sulfuric acid or filtered natural acid rock drainage (ARD) in plastic bottles. The solutions were adjusted at four pH values (1, 3, 5, and 7) and reacted at 4, 30, and 80°C for 3, 7, and 14 days. At the end of the experiments, the filtered supernatants were analyzed by ICP-MS while the solids were characterized by X-Ray Diffraction; Energy-Dispersive X-Ray Fluorescence analyses; Raman and Short-Wave Infrared spectroscopies and Scanning Electron Microscopy. Results show that the solution chemistry played a key role in the evolution of the clay-solution systems. In H2SO4 systems, the solution pH steadily increased due to partial clay dissolution with no secondary phase formation detected. Contrary, in the ARD systems, the pH decreased due to the ample presence of Fe which controlled both the reactivity of clays by the growth of protecting surface coatings and the solution pH by the precipitation of Fe nanophases; secondary phase detected included goethite, jarosite, gypsum, and siderite. These results indicate that, on Mars, the chemical interaction between clays and acidic solutions was complex and dependent on the solution chemistry. Acidic, sulfate-rich solutions have a high dissolution capacity and could have induced widespread clay disintegration. Notably, if Fe-rich ARD was involved, the clays on Mars could have remained stable during acidic Hesperian period due to formation of protective coatings. Comparison of our results with martian observations will be performed to determine how acidic conditions could potentially affect clays in sedimentary settings, including the Gale crater.

L. Lefticariu↗