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Venus climate stability and volcanic resurfacing rates

The climate of Venus is to a large degree controlled by the radiative properties of its massive atmosphere. In addition, outgassing due to volcanic activity, exospheric escape processes, and surface/atmosphere interactions may all be important in moderating the abundances of atmospheric CO2 and other volatiles. We have developed an evolutionary climate model for Venus using a systems approach that emphasizes feedbacks between elements in the climate system. Modules for atmospheric radiative transfer, surface/atmosphere interactions, tropospheric chemistry, and exospheric escape processes have so far been developed. Climate feedback loops result from interconnections between modules, in the form of the environmental parameters pressure, temperature, and atmospheric mixing ratios. The radiative transfer module has been implemented by using Rosseland mean opacities in a one dimensional grey radiative-convective model. The model has been solved for the static (time independent) case to determine climate equilibrium points. The dynamics of the model have also been explored by employing reaction/diffusion kinetics for possible surface atmosphere heterogeneous reactions over geologic timescales. It was found that under current conditions, the model predicts that the climate of Venus is at or near an unstable equilibrium point. The effects of constant rate volcanism and corresponding exsolution of volatiles on the stability of the climate model were also explored.

Bullock, M. A.↗

NPSS on NASA's IPG: Using CORBA and Globus to Coordinate Multidisciplinary Aeroscience Applications

Within NASA's High Performance Computing and Communication (HPCC) program, the NASA Glenn Research Center is developing an environment for the analysis/design of aircraft engines called the Numerical Propulsion System Simulation (NPSS). The vision for NPSS is to create a "numerical test cell" enabling full engine simulations overnight on cost-effective computing platforms. To this end, NPSS integrates multiple disciplines such as aerodynamics, structures, and heat transfer and supports "numerical zooming" between O-dimensional to 1-, 2-, and 3-dimensional component engine codes. In order to facilitate the timely and cost-effective capture of complex physical processes, NPSS uses object-oriented technologies such as C++ objects to encapsulate individual engine components and CORBA ORBs for object communication and deployment across heterogeneous computing platforms. Recently, the HPCC program has initiated a concept called the Information Power Grid (IPG), a virtual computing environment that integrates computers and other resources at different sites. IPG implements a range of Grid services such as resource discovery, scheduling, security, instrumentation, and data access, many of which are provided by the Globus toolkit. IPG facilities have the potential to benefit NPSS considerably. For example, NPSS should in principle be able to use Grid services to discover dynamically and then co-schedule the resources required for a particular engine simulation, rather than relying on manual placement of ORBs as at present. Grid services can also be used to initiate simulation components on parallel computers (MPPs) and to address inter-site security issues that currently hinder the coupling of components across multiple sites. These considerations led NASA Glenn and Globus project personnel to formulate a collaborative project designed to evaluate whether and how benefits such as those just listed can be achieved in practice. This project involves firstly development of the basic techniques required to achieve co-existence of commodity object technologies and Grid technologies; and secondly the evaluation of these techniques in the context of NPSS-oriented challenge problems. The work on basic techniques seeks to understand how "commodity" technologies (CORBA, DCOM, Excel, etc.) can be used in concert with specialized "Grid" technologies (for security, MPP scheduling, etc.). In principle, this coordinated use should be straightforward because of the Globus and IPG philosophy of providing low-level Grid mechanisms that can be used to implement a wide variety of application-level programming models. (Globus technologies have previously been used to implement Grid-enabled message-passing libraries, collaborative environments, and parameter study tools, among others.) Results obtained to date are encouraging: we have successfully demonstrated a CORBA to Globus resource manager gateway that allows the use of CORBA RPCs to control submission and execution of programs on workstations and MPPs; a gateway from the CORBA Trader service to the Grid information service; and a preliminary integration of CORBA and Grid security mechanisms. The two challenge problems that we consider are the following: 1) Desktop-controlled parameter study. Here, an Excel spreadsheet is used to define and control a CFD parameter study, via a CORBA interface to a high throughput broker that runs individual cases on different IPG resources. 2) Aviation safety. Here, about 100 near real time jobs running NPSS need to be submitted, run and data returned in near real time. Evaluation will address such issues as time to port, execution time, potential scalability of simulation, and reliability of resources. The full paper will present the following information: 1. A detailed analysis of the requirements that NPSS applications place on IPG. 2. A description of the techniques used to meet these requirements via the coordinated use of CORBA and Globus. 3. A description of results obtained to date in the first two challenge problems.

Lopez, Isaac↗

Towards a Comprehensive Computational Simulation System for Turbomachinery

The objective of this work is to develop algorithms associated with a comprehensive computational simulation system for turbomachinery flow fields. This development is accomplished in a modular fashion. These modules includes grid generation, visualization, network, simulation, toolbox, and flow modules. An interactive grid generation module is customized to facilitate the grid generation process associated with complicated turbomachinery configurations. With its user-friendly graphical user interface, the user may interactively manipulate the default settings to obtain a quality grid within a fraction of time that is usually required for building a grid about the same geometry with a general-purpose grid generation code. Non-Uniform Rational B-Spline formulations are utilized in the algorithm to maintain geometry fidelity while redistributing grid points on the solid surfaces. Bezier curve formulation is used to allow interactive construction of inner boundaries. It is also utilized to allow interactive point distribution. Cascade surfaces are transformed from three-dimensional surfaces of revolution into two-dimensional parametric planes for easy manipulation. Such a transformation allows these manipulated plane grids to be mapped to surfaces of revolution by any generatrix definition. A sophisticated visualization module is developed to al-low visualization for both grid and flow solution, steady or unsteady. A network module is built to allow data transferring in the heterogeneous environment. A flow module is integrated into this system, using an existing turbomachinery flow code. A simulation module is developed to combine the network, flow, and visualization module to achieve near real-time flow simulation about turbomachinery geometries. A toolbox module is developed to support the overall task. A batch version of the grid generation module is developed to allow portability and has been extended to allow dynamic grid generation for pitch changing turbomachinery configurations. Various applications with different characteristics are presented to demonstrate the success of this system.

Shih, Ming-Hsin↗

Detection of non‐native species formed during fibrillization of the myocilin olfactomedin domain

Abstract Glaucoma is a group of neurodegenerative diseases that together are the leading cause of irreversible blindness worldwide. Myocilin‐associated glaucoma is an inherited form of this disease, caused by intracellular aggregation of misfolded mutant myocilin. In vitro, the myocilin C‐terminal olfactomedin domain (OLF), the relevant domain for glaucoma pathogenesis, can be driven to form amyloid‐like fibrils under mild conditions. Here we characterize a species present during in vitro fibrillization. Purified OLF was subjected to fibrillization at concentrations required for downstream electron microscopy imaging and NMR spectroscopy. Additional biophysical techniques, including analytical ultracentrifugation and X‐ray crystallography, were employed to further characterize the multicomponent mixture. Negative stain transmission electron microscopy (TEM) shows a non‐native species reminiscent of known prefibrillar oligomers from other amyloid systems, NMR indicates a minor population of partially misfolded species is present in solution, and cryo‐EM imaging shows two‐dimensional protein arrays. The predominant soluble species remaining in solution after the fibril reaction is natively folded, as evidenced by X‐ray crystallography. In summary, after incubating OLF under fibrillization‐promoting conditions, there is a heterogeneous mixture consisting of soluble folded protein, mature amyloid‐like fibrils, and partially misfolded intermediate species that at present belie additional molecular detail. The characterization of OLF fibrillar species illustrates the challenges associated with developing a comprehensive understanding of the fibrillization process for large, non‐model amyloidogenic proteins.

Scelsi, Hailee F. [School of Chemistry and Biochem↗

Solvation directed morphological control in metal oxide nanostructures

The development of structural hierarchy on various length scales during the crystallization process is ubiquitous in biological systems and minerals and is common in synthetic nanomaterials. The driving forces for the formation of complex architectures range from local interfacial interactions, that modify interfacial speciation, local supersaturation, and nucleation barriers, to macroscopic interparticle forces. Although it is enticing to interpret the formation of hierarchical architectures as the assembly of independently nucleated building blocks, crystallization pathways often follow monomer-by-monomer addition with structural complexity arising from interfacial chemical coupling and strongly correlated fluctuation dynamics in the electric double layers. Here, we show that the development of structural hierarchy through heterogeneous nucleation is driven by dipolar and solvation forces. Specifically, coupled simulations and experimental studies revealed that dipole build-up along the slow growth direction can trigger twinning and the development of branched architectures. Enthalpic solvation interactions were shown to either enhance or reduce the dipole moment of the nanoparticles and, thereby, control crystal morphology and architecture. The systematic studies of chemical coupling between different solvents and undercoordinated surface atoms of the growing nanocrystals revealed the mechanism of dimensionality control and the development of structural hierarchy without ligands or structure-directing agents.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Contrast Between 1992 and 1997 High Latitude Spring Haloe Observations of Lower Stratospheric HCl

HCl measurements from HALOE in the northern hemisphere during mid-May 1997 revealed vortex fragments in which the chlorine reservoir partitioning was strongly pushed toward HCl (approx. 90% HCl, approx. 10% ClONO2), similar to partitioning previously observed in the Antarctic vortex region. In contrast, observations of ClONO2 and HCl in the northern polar spring, 1992, and in other years, show these species established the balance typical for gas phase photochemical reactions in this region (approx. 60% HCl, approx. 40% ClONO2). Annually, chlorine reservoirs in the winter lower stratosphere polar vortex are converted to chlorine radicals via heterogeneous reactions on particle surfaces at very cold temperatures (less than about 200 K). As temperatures warm in spring, the heterogeneous processes become insignificant compared with gas phase reactions, and the chlorine reservoirs are reformed. Measurements through the northern winter/spring in 1992 show rapid formation of ClONO2, followed by steady loss of ClONO2 and increasing HCl. Although ClONO2 measurements are not available for 1997, the HCl increase in 1997 is observed to be much more rapid and the eventual HCl mixing ratio is about 50% greater than that of 1992. The observations are examined through comparison with the Goddard three-dimensional chemistry and transport model. This model utilizes winds and temperatures from the Goddard Earth Observing System Data Assimilation System and a complete integration scheme for stratospheric photochemistry. Analysis of the evolution of HCl and ClONO2 shows that the observed difference in the overall rate of HCl formation is explained by the sensitivity of the gas-phase chemistry to the ozone mixing ratio and the temperature. The results show that the model accurately simulates HCl and ClONO2 evolution during these two winters. Model validity is further supported by comparisons with O3 and reactive nitrogen species NO and NO2. This analysis provides a sensitive test of the lower stratospheric chlorine photochemistry, particularly because the analysis considers constituent evolution at a time when the HCl and ClONO2 are far from a photochemical stationary state.

Douglass, A. R.↗

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗

Mixing and Transport in the Solar Nebula

Boss & Vanhala (2000, 2001) prepared reviews of triggered collapse and injection models, using Prudence Foster's finite differences code at very high spatial resolution (440 x 1440 cells) to demonstrate the convergence of the R-T fingers in triggered injection models. A two dimensional hydrodynamical calculation with unprecedentedly high spatial resolution (960 x 2880 zones, or almost 3 million grid points) demonstrated that it suitable shock front can both trigger the collapse of an otherwise stable presolar cloud, and inject shock front particles into the collapsing cloud through the formation of what become Rayleigh-Taylor fingers of compressed fluid layers falling into the gravitational potential well of the growing protostar. These calculations suggest that heterogeneity derived from these R-T fingers will persist down to the scale of their injection onto the surface of the solar nebula. Haghighipour developed a numerical code capable of calculating the orbital evolution of dust grains of varied sizes in a gaseous nebula, subject to Epstein and Stokes drag as well as the self-gravity of the disk. In collaboration with the PI and George W. Wetherill, Haghighipour has been involved in development of a new idea on the possibility of rapid formation of ice giant planets via the disk instability mechanism. Haghighipour studied the stability of a five-body system consisting of the Sun and four protoplanets by numerically integrating their equations of motions. Using Levison and Duncan s SWIFT integrator, Haghighipour showed that, depending on the orbital parameters of the bodies, such a system can be stable for 0.1-10 Myr. Time periods of 1 Myr or more are long enough to be consistent with the time scale proposed for the formation of giant planets by the disk instability mechanism and the photoevaporation of the gaseous envelopes of the outermost protoplanets by a nearby OB star, resulting in the formation of ice giant planets. The PI has used his three dimensional models of marginally gravitationally unstable disks to study the preservation of isotopic heterogeneity in evolving protoplanetary disks. Such heterogeneity might arise from the infall onto the disk s surface of solids processed in the X-wind region of the disk, or derived from stellar nucleosynthesis and injected by R-T fingers. The technique used consists of solving a color equation, identical to the gas continuity equation, which follows the time evolution in three space dimensions of an arbitrarily placed initial color field, i.e., a dye inserted the disk. The models show that significant concentrations of color could persist for time periods of about a thousand years or more, even in the most dynamically active region of such a disk. Such a time period might be long enough for solids to coagulate and grow to significant sizes while retaining the isotopic signature of their birth region in the nebula.

Boss, Alan P.↗

Using Controlled Impact Experiments to Understand the Effects of Cohesive Blocks on the Cratering Process

When considering large-scale impact events that occur in the gravity-regime, smallscale target heterogeneities (on order of the projectile diameter) are anticipated to have a minimal effect on the cratering process and are therefore not considered in scaling relations [1-3]. Such heterogeneities and other details of the target's strength and structure, however, become increasingly influential as the magnitude of the impact decreases [4]. At the scale of craters forming mostly in regolith on the Moon (< a few meters), for example, target properties such as cohesive strength, density, porosity, and friction have more leverage than gravity to influence the resultant crater dimensions [5]. Further complications beyond just target properties can manifest in many forms, such as subsurface layers [6]; the presence of random, competent blocks [7]; buried lenses of impact melt; and/or pockets of regolith compacted or indurated to varying degrees by previous impacts. Summing the total effect of target properties and any additional heterogeneities for integration into scaling relations is not straightforward, as each individual parameter will have unequal, and so far, unquantified, effects on the final crater. Even when craters are produced under a best-case scenario of controlled laboratory conditions, understanding the entire relevant parameter space can be a formidable task, and deconvolution of all the contributing factors can be a complex undertaking. To begin the process of quantifying such effects, we are conducting an extensive series of impact experiments to build a framework for the interpretation of craters observed on the characteristically complex surfaces throughout the solar system. Here we present the first, and simplest, configuration to be examined in this multi-year experimental campaign: one in which solitary, cohesive blocks are placed in the path of the projectile’s trajectory at different burial depths in granular, sand targets. Among the variables to be investigated in this configuration are the influence of block size, compressive strength, and burial depth.

impact crater↗

On-PIC Light Source Integration & Micro-dispensing of Solder Paste for Flip Chip Application

To reach the next level benefits of photonic integrated circuits (PICs), the Integrated Photonic Systems Roadmap-International describes the necessity of either heterogeneous or hybrid integration of light sources [1]. A new approach for hybrid integration is Photonic Wire Bonding where 3D nanolithography is used to pattern a polymer waveguide that connects light sources to PIC waveguides. The waveguides resemble electrical wire bonds and essentially do the same as their electrical counterpart for packaging photonic chips together. In order to reap the full benefits of a photonic wire bonds, the light source must be carefully packaged. In this work I seek to expand RIT’s photonic packaging capability by establishing a packaging process to integrate light sources, specifically an Indium Phosphide distributed feedback lasers and a reflective semiconductor optical amplifiers, directly onto a photonic integrated circuits. Another necessary requirement for PIC packaging is densely integrated electrical connectivity. In this thesis I developed a fine pitch flip chip interconnect technique demonstrated using gold stud bumps in conjunction with micro-dispensed solder paste. This work opens the door to high density photonic flip chip applications. The micro-dispensed solder paste dots having diameters 50-125 µm are currently being tested at a pitch of 150 µm . The gold stud bumps are formed with 1mil gold wire creating bumps with a diameter of 40-60 µm depending on specific parameter values. These capabilities will allow RIT to assemble and test novel photonic integrated devices, cutting down on the time and cost associated with third party assembly and tests facilities. Thereby keeping RIT at the forefront of photonic research.

Wongk, Nicole↗

Exploring single-cell biosynthetic noise and dynamics for enhanced betaxanthin production in Escherichia coli

Cell-to-cell variability often limits the efficiency of microbial bioproduction, yet how individual cells fluctuate over time and how these fluctuations shape population-level output remain unclear. To address this issue, we tracked a heterologous betaxanthin pathway in Escherichia coli using microfluidics-assisted time-lapse microscopy, allowing simultaneous measurement of fluctuations in betaxanthin, its biosynthetic enzyme DOD and growth across generations. Here we show that over 50% of high betaxanthin producers become medium or low producers after two divisions. Betaxanthin variation primarily originates from DOD noise, with a smaller contribution from growth rate fluctuations. We further develop a stochastic model to explore various control circuits and find that pathway enzyme or metabolite-based growth selection strategies are most effective in enhancing production. We experimentally validate the model by coupling enzyme expression to nutrient availability, which enriches high producers and boosts titer by 4.4-fold. Our results highlight key sources of metabolic heterogeneity and provide a framework for designing robust microbial processes.

Bacterial systems biology↗

Isolated and H 2 -reduced Anderson clusters catalyse low-temperature hydrogenation of CO 2 to methanol

CO 2 hydrogenation, especially to methanol, is crucial to establishing sustainable closed-loop systems for carbon utilization. However, the difficulties of CO 2 activation at low temperatures and the ambiguity of structure–activity correlations are obstacles to reducing the energy consumption of the hydrogenation process. Here we report that molecularly defined Anderson PtMo 6 O 24 clusters, sited within a robust metal–organic framework, are catalytic for low-temperature CO 2 hydrogenation. The performance of the cluster showed no signs of decay in either its activity or methanol selectivity over 3,600 h at 180 °C. It also achieves a per-pass yield exceeding that of state-of-the-art heterogeneous catalysts under similar conditions. Combined in situ spectroscopy and density functional theory calculations demonstrated that CH 3 OH formation is dominated by the reverse water–gas shift and subsequent CO* hydrogenation pathway, while the HCOO* pathway may serve as a supplementary route. The well-defined cluster structure offers an ideal model for elucidating structure–activity correlations and opens exciting avenues for the rational design of high-activity, low-temperature catalysts for CO 2 hydrogenation.

heterogeneous catalysis↗

Laminar Dust Flames: A Program of Microgravity and Ground Based Studies at McGill

Fundamental knowledge of heterogeneous combustion mechanisms is required to improve utilization of solid fuels (e.g. coal), safe handling of combustible dusts in industry, and solid propulsion systems. The objective of the McGill University research program on dust combustion is to obtain a reliable set of data on basic combustion parameters for dust suspensions (i.e. laminar burning velocity, flame structure, quenching distance, flammability limits, etc.) over a range of particle sizes, dust concentrations, and types of fuel. This set of data then permits theoretical models to be validated and, when necessary, new models to be developed to describe the detailed reaction mechanisms and transport processes. Microgravity is essential to the generation of a uniform dust suspension of arbitrary particle size and concentration. When particles with a characteristic size on the order of tens of microns are suspended, they rapidly settle in a gravitational field. To maintain a particulate in suspension for time duration adequate to carry out combustion experiments invariably requires continuous convective flow in excess of the gravitational settling velocity (which is comparable with and can even exceed the dust laminar burning velocity). This makes the experiments turbulent in nature and thus renders it impossible to study laminar dust flames. Even for small particle sizes on the order of microns, a stable laminar dust flow can be maintained only for relatively low dust concentrations at normal gravity conditions. High dust loading leads to gravitational instability of the dust cloud and to the formation of recirculation cells in the dust suspension in a confined volume, or to the rapid sedimentation of the dense dust cloud, as a whole, in an unconfined volume. Many important solid fuels such as carbon and boron also have low laminar flame speeds (of the order of several centimeters per second). Convection that occurs in combustion products due to buoyancy disrupts the low speed dust flames and makes observation of such flames at normal gravity difficult.

Goroshin, Sam↗

Detection of Ionospheric Alfven Resonator Signatures Onboard C/NOFS: Implications for IRI Modeling

The 2008-2009 long-lasting solar minimum activity has been the one of its kind since the dawn of space age, offering exceptional conditions for investigating space weather in the near-Earth environment. First ever detection of Ionospheric Alfven Resonator (IAR) signatures in orbit offers new means for investigating ionospheric electrodynamics, namely MHD (MagnetoHydroDynamics) wave propagation, aeronomy processes, ionospheric dynamics, and Sun-Earth connection mechanisms at a local scale. Local and global plasma density heterogeneities in the ionosphere and magnetosphere allow for formation of waveguides and resonators where magnetosonic and shear Alfven waves propagate. The ionospheric magnetosonic waveguide results from complete magnetosonic wave reflection about the ionospheric F-region peak, where the Alfven index of refraction presents a maximum. MHD waves can also be partially trapped in the vertical direction between the lower boundary of the ionosphere and the magnetosphere, a resonance mechanism known as IAR. In this work we present C/NOFS (Communications/Navigation Outage Forecasting System) Extremely Low Frequency (ELF) electric field measurements related to IAR signatures, discuss the resonance and wave propagation mechanisms in the ionosphere, and address the electromagnetic inverse problem from which electron/ion distributions can be derived. These peculiar IAR electric field measurements provide new, complementary methodologies for inferring ionospheric electron and ion density profiles, and also contribute for the investigation of ionosphere dynamics and space weather monitoring. Specifically, IAR spectral signatures measured by C/NOFS contribute for improving the International Reference Ionosphere (IRI) model, namely electron density and ion composition.

Simoes, F.↗

Zelda and company - Petrogenesis of sulfide-rich Fremdlinge and constraints on solar nebula processes

A detailed petrographic and chemical study of Zelda (a gigantic sulfide-rich Fremdling from the Allende Ca-rich inclusion, CAI, Egg 6) and its contact with the host was conducted using analytical SEM and electron-microprobe techniques, and the results were compared with those obtained on other sulfide-rich and oxide-rich Fremdlinge. Strong evidence is presented that Zelda, a type-example of sulfide-rich Fremdlinge, has been formed from a preexisting Ur-Fremdling, similar by composition to Willy, by closed-system sulfidization of magnetite and metal. At least two different sulfidization mechanisms appear to have occurred in altering Fremdlinge: one producing compositionally homogeneous equigranular objects such as Zelda, the other producing compositionally and texturally heterogeneous objects.

Armstrong, John T.↗

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗

Mixing of cryogenic fluids and predicted detonation properties for multiphase liquid oxygen and liquid hydrogen

The mixing and explosion of LOX and LH sub 2 is a concern for Space Transportation System operations. To understand this problem, cryogenic mixing is experimentally studied by pouring 1,2,2 trichloro 2,1,1 trifluoroethane (Freon 113) into LN sub 2, LN sub 2 into LH sub 2, and LH sub 2 into into LN sub 2 in a 1 m by 15 cm cylindrical glass vessel. Data from these experiments is compared with previous studies and a hypothesis is advanced that LOX/LH sub 2 mixing will result in a complex, heterogenous, multiphase aggregation including LOX, SOX, LH sub 2, and VH sub 2 using the multiphase hypothesis. Visual and x ray observations of the process and mass measurements are reported.

Bishop, C. V.↗

Effects of Pre-Existing Target Structure on the Formation of Large Craters

The shapes of large-scale craters and the mechanics responsible for melt generation are influenced by broad and small-scale structures present in a target prior to impact. For example, well-developed systems of fractures often create craters that appear square in outline, good examples being Meteor Crater, AZ and the square craters of 433 Eros. Pre-broken target material also affects melt generation. Kieffer has shown how the shock wave generated in Coconino sandstone at Meteor crater created reverberations which, in combination with the natural target heterogeneity present, created peaks and troughs in pressure and compressed density as individual grains collided to produce a range of shock mineralogies and melts within neighboring samples. In this study, we further explore how pre-existing target structure influences various aspects of the cratering process. We combine experimental and numerical techniques to explore the connection between the scales of the impact generated shock wave and the pre-existing target structure. We focus on the propagation of shock waves in coarse, granular media, emphasizing its consequences on excavation, crater growth, ejecta production, cratering efficiency, melt generation, and crater shape. As a baseline, we present a first series of results for idealized targets where the particles are all identical in size and possess the same shock impedance. We will also present a few results, whereby we increase the complexities of the target properties by varying the grain size, strength, impedance and frictional properties. In addition, we investigate the origin and implications of reverberations that are created by the presence of physical and chemical heterogeneity in a target.

Barnouin-Jha, O. S.↗