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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Analytical and experimental studies of leak location and environment characterization for the international space station
The International Space Station program is developing a robotically-operated leak locator tool to be used externally. The tool would consist of a Residual Gas Analyzer for partial pressure measurements and a full range pressure gauge for total pressure measurements. The primary application is to demonstrate the ability to detect NH{sub 3} coolant leaks in the ISS thermal control system. An analytical model of leak plume physics is presented that can account for effusive flow as well as plumes produced by sonic orifices and thruster operations. This model is used along with knowledge of typical RGA and full range gauge performance to analyze the expected instrument sensitivity to ISS leaks of various sizes and relative locations (“directionality”). The paper also presents experimental results of leak simulation testing in a large thermal vacuum chamber at NASA Goddard Space Flight Center. This test characterized instrument sensitivity as a function of leak rates ranging from 1 lb{sub m/}/yr. to about 1 lb{sub m}/day. This data may represent the first measurements collected by an RGA or ion gauge system monitoring off-axis point sources as a function of location and orientation. Test results are compared to the analytical model and used to propose strategies for on-orbit leak location and environment characterization using the proposed instrument while taking into account local ISS conditions and the effects of ram/wake flows and structural shadowing within low Earth orbit.
Removal of malachite green dye from aqueous solution using mesoporous silica synthesized from 1-octyl-3-methylimidazolium chloride ionic liquid
In this research, mesoporous silica was synthesized via a modified sol-gel route using 1-octyl-3-methylimidazolium chloride and was employed to remove malachite green (MG) dye from aqueous solution. Subsequently, this material was characterized and identified by different techniques such as Fourier transform infrared spectroscopy (FT-IR), N{sub 2} adsorption-desorption method, scanning electron microscopy (SEM), and thermosgravimetric analysis (TGA). Unique properties such as high surface area and pore diameter, in addition to highly reactive atoms and presence of various functional groups make the mesoporous silica possible for efficient removal of malachite green (MG). In batch experimental set-up, optimum conditions for quantitative removal of MG by mesoporous silica was attained by varying different variables such as adsorbent dosage, initial dye concentration, contact time, and pH. Optimum values were set as pH of 8.0, 0.5 g of adsorbent at contact time of 120 min. The adsorption of MG follows the pseudo-second-order rate equation. Equilibrium data fitted well with the Freundlich model at all amount of adsorbent, while maximum adsorption capacity was 5.981 mg g{sup −}1 for 0.5 g mesoporous silica synthesized in IL.
Modeling of the blood rheology in steady-state shear flows
We undertake here a systematic study of the rheology of blood in steady-state shear flows. As blood is a complex fluid, the first question that we try to answer is whether, even in steady-state shear flows, we can model it as a rheologically simple fluid, i.e., we can describe its behavior through a constitutive model that involves only local kinematic quantities. Having answered that question positively, we then probe as to which non-Newtonian model best fits available shear stress vs shear-rate literature data. We show that under physiological conditions blood is typically viscoplastic, i.e., it exhibits a yield stress that acts as a minimum threshold for flow. We further show that the Casson model emerges naturally as the best approximation, at least for low and moderate shear-rates. We then develop systematically a parametric dependence of the rheological parameters entering the Casson model on key physiological quantities, such as the red blood cell volume fraction (hematocrit). For the yield stress, we base our description on its critical, percolation-originated nature. Thus, we first determine onset conditions, i.e., the critical threshold value that the hematocrit has to have in order for yield stress to appear. It is shown that this is a function of the concentration of a key red blood cell binding protein, fibrinogen. Then, we establish a parametric dependence as a function of the fibrinogen and the square of the difference of the hematocrit from its critical onset value. Similarly, we provide an expression for the Casson viscosity, in terms of the hematocrit and the temperature. A successful validation of the proposed formula is performed against additional experimental literature data. The proposed expression is anticipated to be useful not only for steady-state blood flow modeling but also as providing the starting point for transient shear, or more general flow modeling.
Dynamic scan control in STEM: spiral scans
Abstract Scanning transmission electron microscopy (STEM) has emerged as one of the foremost techniques to analyze materials at atomic resolution. However, two practical difficulties inherent to STEM imaging are: radiation damage imparted by the electron beam, which can potentially damage or otherwise modify the specimen and slow-scan image acquisition, which limits the ability to capture dynamic changes at high temporal resolution. Furthermore, due in part to scan flyback corrections, typical raster scan methods result in an uneven distribution of dose across the scanned area. A method to allow extremely fast scanning with a uniform residence time would enable imaging at low electron doses, ameliorating radiation damage and at the same time permitting image acquisition at higher frame-rates while maintaining atomic resolution. The practical complication is that rastering the STEM probe at higher speeds causes significant image distortions. Non-square scan patterns provide a solution to this dilemma and can be tailored for low dose imaging conditions. Here, we develop a method for imaging with alternative scan patterns and investigate their performance at very high scan speeds. A general analysis for spiral scanning is presented here for the following spiral scan functions: Archimedean, Fermat, and constant linear velocity spirals, which were tested for STEM imaging. The quality of spiral scan STEM images is generally comparable with STEM images from conventional raster scans, and the dose uniformity can be improved.
The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models
Core Ideas We propose VSHC for calculating soil water percolation in continuous models. VSHC relates permeability to daily hydraulic properties to estimate hydraulic conductivity. VSHC performed well at field scale and improved estimates of peak streamflows. Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping‐bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new submodel, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long‐term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high‐flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale.
THE ROLE OF NITROGEN IN TITAN’S UPPER ATMOSPHERIC HYDROCARBON CHEMISTRY OVER THE SOLAR CYCLE
Titan’s thermospheric photochemistry is primarily driven by solar radiation. Similarly to other planetary atmospheres, such as Mars’, Titan’s atmospheric structure is also directly affected by variations in the solar extreme-UV/UV output in response to the 11-year-long solar cycle. Here, we investigate the influence of nitrogen on the vertical production, loss, and abundance profiles of hydrocarbons as a function of the solar cycle. Our results show that changes in the atmospheric nitrogen atomic density (primarily in its ground state N({sup 4}S)) as a result of photon flux variations have important implications for the production of several minor hydrocarbons. The solar minimum enhancement of CH{sub 3}, C{sub 2}H{sub 6}, and C{sub 3}H{sub 8}, despite the lower CH{sub 4} photodissociation rates compared with solar maximum conditions, is explained by the role of N({sup 4}S). N({sup 4}S) indirectly controls the altitude of termolecular versus bimolecular chemical regimes through its relationship with CH{sub 3}. When in higher abundance during solar maximum at lower altitudes, N({sup 4}S) increases the importance of bimolecular CH{sub 3} + N({sup 4}S) reactions producing HCN and H{sub 2}CN. The subsequent remarkable CH{sub 3} loss and decrease in the CH{sub 3} abundance at lower altitudes during solar maximum affects the overall hydrocarbon chemistry.
Flux divergence of thermal radiation within stratiform clouds
A longwave radiative transfer model based on the narrow-band transmission functions of Lowtran 6 has been developed to investigate the profile of radiative flux divergence at the tops of stratiform clouds. The model has a vertical resolution of 1 m and a spectral resolution of 20/cm. These features are shown to permit modeling of broadband radiative transfer in the presence of a cloud top inversion and finite liquid water gradient. Radiative cooling rates in excess of 40 K/hr are shown to be possible for extreme conditions, with values of 10 K/hr being representative of more typical conditions. The values obtained are shown to be strongly influenced by the magnitude of liquid water concentration, by the gradient of liquid water in the top 50 m, and by the strength of the temperature inversion.
Effects of heat stress on baroreflex function in humans
INTRODUCTION: Heat stress significantly reduces orthostatic tolerance in humans. The mechanism(s) causing this response remain unknown. The purpose of this review article is to present data pertaining to the hypothesis that reduced orthostatic tolerance in heat stressed individuals is a result of heat stress induced alterations in baroflex function. METHODS: In both normothermic and heat stressed conditions baroreflex responsiveness was assessed via pharmacological and non-pharmacological methods. In addition, the effects of heat stress on post-synaptic vasoconstrictor responsiveness were assessed. RESULTS: Generally, whole body heating did not alter baroreflex sensitivity defined as the gain of the linear portion of the baroreflex curve around the operating point. However, whole body heating shifted the baroreflex curve to the prevailing (i.e. elevated) heart rate and muscle sympathetic nerve activity. Finally, the heat stress impaired vasoconstrictor responses to exogenous administration of adrenergic agonists. CONCLUSION: Current data do not support the hypothesis that reduced orthostatic tolerance associated with heat stress in humans is due to impaired baroreflex responsiveness. This phenomenon may be partially due to the effects of heat stress on reducing vasoconstrictor responsiveness.
Analytical and Experimental Studies of Leak Location and Environment Characterization for the International Space Station
The International Space Station program is developing a robotically-operated leak locator tool to be used externally. The tool would consist of a Residual Gas Analyzer for partial pressure measurements and a full range pressure gauge for total pressure measurements. The primary application is to detect NH3 coolant leaks in the ISS thermal control system. An analytical model of leak plume physics is presented that can account for effusive flow as well as plumes produced by sonic orifices and thruster operations. This model is used along with knowledge of typical RGA and full range gauge performance to analyze the expected instrument sensitivity to ISS leaks of various sizes and relative locations ("directionality"). The paper also presents experimental results of leak simulation testing in a large thermal vacuum chamber at NASA Goddard Space Flight Center. This test characterized instrument sensitivity as a function of leak rates ranging from 1 lb-mass/yr. to about 1 lb-mass/day. This data may represent the first measurements collected by an RGA or ion gauge system monitoring off-axis point sources as a function of location and orientation. Test results are compared to the analytical model and used to propose strategies for on-orbit leak location and environment characterization using the proposed instrument while taking into account local ISS conditions and the effects of ram/wake flows and structural shadowing within low Earth orbit.
Using Mylar-Insulated Cryopumping Panels to Improve Vacuum Level During Warm Temperature Testing at JSC's Large Thermal Vacuum Facilities
Johnson Space Center’s Space Environment Simulation Lab (SESL) has both Chamber A, the world’s largest purpose-built thermal vacuum chamber capable of creating deep space conditions, and Chamber B, the largest human rated thermal vacuum chamber. A unique design feature of these chambers is the gaseous helium cryopumping panels within the liquid nitrogen shroud. This shroud is used to bring the chamber to cryogenic temperatures while the cryopumping panels trap gasses on its surface area to create a high vacuum environment of 5*10-6 Torr. In preparation for the James Webb Space Telescope (JWST) flight test, a series of functionals required the chamber to run at higher temperatures, and therefore did not need active cooling from the liquid nitrogen shroud. During testing, cryopumping panels were used to mitigate contamination during this main shroud warm-up. One of the cryopumping panels in Chamber A was covered with several layers of aluminized mylar to thermally protect the zone from the warmed shroud. This strategy was effective and became part of operations during JWST testing. Currently, Chamber B has requests for both commercial and NASA space suit tests at both high and low temperatures to validate thermal models. High temperature tests could benefit from reduced heater demand with an insulated shroud while still sustaining the high vacuum environment provided by the cryopumping panels. This paper will quantitatively define the thermal loads on the panels used in previous Chamber A warm up sequences. Additionally, this report will perform thermal analyses to assess the feasibility of adding layers of aluminized mylar to the cryopumping panels of Chamber B.
Atmospheric turbulence affects wind turbine nacelle transfer functions
Despite their potential as a valuable source of individual turbine power performance and turbine array energy production optimization information, nacelle-mounted anemometers have often been neglected because complex flows around the blades and nacelle interfere with their measurements. This work quantitatively explores the accuracy of and potential corrections to nacelle anemometer measurements to determine the degree to which they may be useful when corrected for these complex flows, particularly for calculating annual energy production (AEP) in the absence of other meteorological data. Using upwind meteorological tower measurements along with nacelle-based measurements from a General Electric (GE) 1.5sle model, we calculate empirical nacelle transfer functions (NTFs) and explore how they are impacted by different atmospheric and turbulence parameters. This work provides guidelines for the use of NTFs for deriving useful wind measurements from nacelle-mounted anemometers. Corrections to the nacelle anemometer wind speed measurements can be made with NTFs and used to calculate an AEP that comes within 1% of an AEP calculated with upwind measurements. We also calculate unique NTFs for different atmospheric conditions defined by temperature stratification as well as turbulence intensity, turbulence kinetic energy, and wind shear. During periods of low stability as defined by the Bulk Richardson number ( R B ), the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of high stability at some wind speed bins below rated speed, leading to a steeper NTF during periods of low stability. Similarly, during periods of high turbulence, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of low turbulence at most wind bins between cut-in and rated wind speed. Based on these results, we suggest different NTFs be calculated for different regimes of atmospheric stability and turbulence for power performance validation purposes.
Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers
Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.
Single-Molecule Interfacial Electron Transfer
This project is focused on the use of single-molecule high spatial and temporal resolved techniques to study molecular dynamics in condensed phase and at interfaces, especially, the complex reaction dynamics associated with electron and energy transfer rate processes. The complexity and inhomogeneity of the interfacial ET dynamics often present a major challenge for a molecular level comprehension of the intrinsically complex systems, which calls for both higher spatial and temporal resolutions at ultimate single-molecule and single-particle sensitivities. Combined single-molecule spectroscopy and electrochemical atomic force microscopy approaches are unique for heterogeneous and complex interfacial electron transfer systems because the static and dynamic inhomogeneities can be identified and characterized by studying one molecule at a specific nanoscale surface site at a time. The goal of our project is to integrate and apply these spectroscopic imaging and topographic scanning techniques to measure the energy flow and electron flow between molecules and substrate surfaces as a function of surface site geometry and molecular structure. We have been primarily focusing on studying interfacial electron transfer under ambient condition and electrolyte solution involving both single crystal and colloidal TiO 2 and related substrates. The resulting molecular level understanding of the fundamental interfacial electron transfer processes will be important for developing efficient light harvesting systems and broadly applicable to problems in fundamental chemistry and physics. We have made significant advancement on deciphering the underlying mechanism of the complex and inhomogeneous interfacial electron transfer dynamics in dyesensitized TiO 2 nanoparticle systems that strongly involves with and regulated by molecule-surface interactions. We have studied interfacial electron transfer on TiO 2 nanoparticle surfaces by using ultrafast single-molecule spectroscopy and electrochemical AFM metal tip scanning microscopy, focusing on understanding the interfacial electron transfer dynamics at specific nanoscale electron transfer sites with high-spatially and temporally resolved topographic-and-spectroscopic characterization at individual molecule basis, characterizing single-molecule rate processes, reaction driving force, and molecule-substrate electronic coupling. One of the most significant characteristics of our new approach is that we are able to interrogate the complex interfacial electron transfer dynamics by actively pin-point energetic manipulation of the surface interaction and electronic couplings, beyond the conventional excitation and observation.
A Comprehensive Understanding of the Aging Effects of Extreme Fast Charging on High Ni NMC Cathode
As the battery industry shifts toward high Ni content cathodes, such as LiNi 0.8 Mn 0.1 Co 0.1 O 2 [NMC811], a complete understanding of the degradation mechanisms of NMC811 under extreme fast charging (XFC) (XFC, ≤10–15 min charging) conditions is needed. Such comprehensive understanding would identify the most critical materials gaps that need to be addressed for enabling XFC long-life cells for electric vehicles. This study maps out the key aging mechanisms for NMC811 cycled at different XFC conditions (between 1C and 9C) for up to 1000 cycles. To acquire a fundamental understanding of utilization and degradation, cells are evaluated using a range of electrochemical techniques, and multimodal and multiscale microscopy techniques to quantify chemical, structural, and crystallographic degradation as a function of cycling conditions for the NMC cathode. When comparing NMC811 to NMC532, it is observed that NMC811 has a greater subsurface crystallographic degradation and displays a similar magnitude of subparticle cracking. However, the NMC811 maintains superior performance despite those advanced degradations. Here, the superior cycle life performance is attributed to the NMC811 particles having radially oriented grains and improved transport properties. NMC811 shows between 4.6× and 3.15× reduction in capacity fade than NMC532 for charging rates between 4C (e.g., 15-min charging) and 6C (10-min charging).
Flow simulation and analysis of high-power flow batteries
The cost of a flow battery system can be reduced by increasing its power density and thereby reducing its stack area. If per-pass utilizations are held constant, higher battery power densities can only be achieved using higher flow rates. Here, a 3D computational fluid dynamics model of a flow battery flow field and electrode is used to analyze the implications of increasing flow rates to high power density operating conditions. Interdigitated and serpentine designs, and cell sizes ranging from 10 cm 2 to 400 cm 2 , are simulated. The results quantify the dependence of pressure loss on cell size and design, demonstrating that the details of the passages that distribute flow between individual channels and the inlet and outlet have a major impact on pressure losses in larger cells. Additionally, in-cell flow behavior is analyzed as a function of cell size and design. Flow structures are interrogated to show how and where electrode parameters influence pressure drops, and how regions where transport is slow are correlated with the presence of experimentally observed cell degradation.
Simultaneous occupancy of Cu C and Cu D in the ammonia monooxygenase active site
Ammonia monooxygenase (AMO), a copper-dependent membrane enzyme, catalyzes the first and rate-limiting step of nitrification: the oxidation of ammonia to hydroxylamine. Despite its central role in the global nitrogen cycle and its biotechnological relevance, structural characterization of AMO has lagged behind that of its homolog, particulate methane monooxygenase (pMMO), due to the slow growth rates of ammonia-oxidizing bacteria and the instability of AMO upon purification. Recent cryoEM studies of Nitrosomonas europaea AMO and Methylococcus capsulatus (Bath) pMMO in native membranes revealed new structural features, including two adjacent copper-binding sites in the transmembrane region, Cu C and Cu D , believed to constitute the active site. Although multiple structures were determined under various conditions, simultaneous occupancy of Cu C and Cu D was never observed, leaving their potential functional interplay unresolved. Here we report the 2.6 Å resolution cryoEM structure of AMO from Nitrosospira briensis C-128 in isolated native membranes. This structure reveals the first instance of simultaneous copper occupancy of the Cu C and Cu D sites, along with occupancy of the periplasmic Cu B site. Electron paramagnetic resonance (EPR) spectroscopic data indicate that the Cu B site is primarily occupied by Cu(II), while Cu C and Cu D are primarily occupied by diamagnetic ions, presumably Cu(I). Notably, a lipid molecule is bound between the Cu C and Cu D sites, separating them by ∼8.0 Å. The results underscore the importance of studying these enzymes in their native environments across species to resolve conserved and divergent molecular features.
Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications
Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.