Arsenate removal using titanium dioxide-doped cementitious composites: Mixture design, mechanisms, a
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Liu, Zhuo↗
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Green and durable engineered cementitious composites (GD-ECC) with recycled PE fiber, desert sand, and carbonation curing: Mixture design, durability performance, and life-cycle analysis
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Construction & Building Technology↗
Performance of concrete under accelerated physical salt attack and carbonation
Conventional testing of physical salt attack (PSA) on concrete does not consider concomitant factors that may exist in service and alter the mechanisms and kinetics of PSA. This study adopted a combined testing approach where concrete was concurrently investigated under accelerated PSA and carbonation, simulating elements serving in heavy traffic and industrial zones, while implementing ambient conditions similar to that in geographic locations with previous cases of PSA. Based on the tested mixture design parameters [water-to-binder ratio, cement type, and supplementary cementitious materials], potential performance improvement and risks were identified. Thermal, mineralogical, and microscopy analyses elucidated the co-occurrence of complex degradation processes in concrete subjected to accelerated PSA and carbonation, which were distinctive from that induced by the single-factor PSA exposure. The synoptic results from this study may informatively improve guidance on mixture design of concrete when dual exposure to PSA and carbonation is expected in the field.
36 MATERIALS SCIENCE↗
Molten Salt Electrolytes: Computational Analysis of Transport, Electrochemical Properties and Designing New Mixtures
Electric aircraft propulsion has gained a traction over the last decade due to possible high-energy density electrochemistries with reasonable cycle life and identification of non-flammable chemistries that can guarantee much better safety. Commercial Li-ion batteries cannot reach such high capacities because of weight limitations that arise from the widely used intercalation electrodes. Also, use of organic electrolytes make them highly susceptible to fire on exposure to air and humidity. Currently, use of Lithium metal anode along with conversion electrochemistries such as Li-O2 and Li-S are being pursued to achieve such high energy densities. Safer inorganic solid-state electrolytes, recently discovered Water-in-Salt electrolytes, molten salt electrolytes are some of the alternatives being pursued for a safer/non-flammable battery. Of these safer alternatives, molten-salt electrolytes offer some attractive properties: liquid at operating temperatures resulting in better electrode-wetting, stable interface with Li-metal anodes and good ionic conductivity; their only drawback being high operating temperatures. In this talk, we will discuss some of the computational studies, driven via atomistic simulations, of the properties of molten-salt electrolytes including transport mechanism and interface stability. We will also discuss predicting electrochemical properties of these high-temperature electrolytes. Further, we will discuss a thermodynamic approach to predicting new molten-salt eutectics with lower melting points.
Molten Salt Electrolytes↗
Computational Tools to Design Molten Salt Electrolytes for High-Temperature Environments
Current Li-ion batteries are designed for a small operating window of 5 °C to 55 °C. Modifications to the electrolyte for operation in Mars atmosphere extended this range on the lower bound to ~ -40 °C. These operating-temperature ranges are far from those presented in high-temperature environments, such as the Venus surface, where temperatures are around 450 °C. Protecting the state-of-the-art Li-ion batteries require insulations that decreases the volumetric capacity and limiting the operational time-window. These unique challenges require a paradigm shift in materials used for designing high-temperature batteries. Molten salt electrolyte-based batteries offer a plausible route to designing high-temperature batteries. ZEBRA batteries are known to be one of the safest energy storage devices operating at 270-350 °C. Nitrate based eutectics, operating at 150 °C have also been used in Li-O2 batteries. In this study, we will examine molten-salt electrolyte transport and electrochemical properties using first-principles computations and benchmark against experiments. Further, we will present thermodynamics-based models for designing and predicting melting point of molten salt mixtures. Based on these computational tools, new molten salt mixtures designed with desired operating temperatures and electrochemical windows will be presented. Implications of these new eutectics in the context of high-temperature environment exploration will also be discussed.
Balachandran Radhakrishnan↗
Simulation of a hydrocarbon fueled scramjet exhaust
Exhaust nozzle flow fields for a fully integrated, hydrocarbon burning scramjet were calculated for flight conditions of M (undisturbed free stream) = 4 at 6.1 km altitude and M (undisturbed free stream) = 6 at 30.5 km altitude. Equilibrium flow, frozen flow, and finite rate chemistry effects are considered. All flow fields were calculated by method of characteristics. Finite rate chemistry results were evaluated by a one dimensional code (Bittker) using streamtube area distributions extracted from the equilibrium flow field, and compared to very slow artificial rate cases for the same streamtube area distribution. Several candidate substitute gas mixtures, designed to simulate the gas dynamics of the real engine exhaust flow, were examined. Two mixtures are found to give excellent simulations of the specified exhaust flow fields when evaluated by the same method of characteristics computer code.
Leng, J.↗
Statistically-driven Experimental Design to Improve Reference-free Quantification of Small Molecules by Liquid Chromatography-Mass Spectrometry
Non-targeted analysis of small molecules and metabolites in unknown, complex samples using liquid chromatography-tandem mass spectrometry remains challenging. One of the main bottlenecks is the extensive unannotated regions of metabolomics mass spectrometry data, resulting in knowledge gaps. Small molecule annotation in mass spectrometry data has conventionally relied on reference standards and libraries for compound identification and confirmation, which can constrain compound identification to those molecules already known, thus limiting the ability to discover new knowledge and new markers. Retention time prediction can facilitate and expedite unknown compound identification in non-targeted analysis of complex metabolomics samples. Additionally, accurate retention time predictions can also inform sample mixture design for LC-MS/MS analyses. However, current machine learning-based methods for retention time prediction are typically developed for specific chromatographic platforms and are not generalizable across scales. And while technologies and methods to improve reference-free metabolite identification for more comprehensive annotation of unknowns has received much attention, development of the same for quantitation without reference standards has been much more limited, despite its importance in toxicological, environmental, food safety, forensics, and clinical applications. We believe that a reference-free quantitation strategy that exploits mass spectrometry data already collected for reference-free identification can provide much more insight on unknowns, and move the metabolomics field for more complete unknowns characterization. As such, we pursue two efforts to improve upon current state-of-the-art methods in non-targeted analysis: (1) machine learning-based retention time prediction and (2) statistical design of experiments framework for reference-free quantitation. In this work, we develop and demonstrate (1) a generalizable retention time prediction capability across chromatographic conditions and scales, and (2) a statistical design-based framework for response factor contribution elucidation and reference-free quantitation. Evaluation of our retention time prediction model, PrediToR, showed approximately 24% improvement over current models, and we observed approximately 10X improvement in concentration estimation accuracy from our statistical design-based response factor model over a primarily ionization efficiency-based model. We expect that future efforts to improve upon these new capabilities will further advance non-targeted analysis of small molecules towards truly reference-free metabolomics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Limestone calcined clay cement and concrete: A state-of-the-art review
This article reviews the rapidly developing state-of-the-art literature available on the subject of the recently developed limestone calcined clay cement (LC{sup 3}). An introduction to the background leading to the development of LC{sup 3} is first discussed. The chemistry of LC{sup 3} hydration and its production are detailed. The influence of the properties of the raw materials and production conditions are discussed. The mixture design of concrete using LC{sup 3} and the mechanical and durability properties of LC{sup 3} cement and concrete are then compared with other cements. At the end the economic and environmental aspects of the production and use of LC{sup 3} are discussed. The paper ends with suggestions on subjects on which further research is required.
36 MATERIALS SCIENCE↗
Development of Transformative Preparation Methods to Push up High Q&G Performance of FRIB Spare HWR Cryomodule Cavities
The FRIB accelerator project construction, a top priority of US nuclear science, was completed in January 2022, and is now moving to user operation. The stable and reliable operation of the accelerating cryomodules is essential in achieving/fulfilling DOE and user expectations. So far, FRIB cryomodules meet all FRIB specifications for cavity performance. However, during the lifetime of machine operation, degradation of cryomodule performance is possible, as reported in similar operating facilities (CEBAF, SNS). If cryomodule degradation is observed at FRIB, the under-performing cryomodule will require replacement/maintenance. In effort to manage operational reliability, FRIB plans to construct a 0.53 half-wave cryomodule to serve as an active spare. In a parallel effort, FRIB will also work toward increasing operational Q and gradient of spare cryomodule cavities to gain an overall performance margin to support future operational reliability. The current FRIB cavity designs have a potential to operate at gradients higher than 8 MV/m, but are currently limited by field emission (FE) and/or high field Q slope (HFQS); known issue in buffered chemical polished (BCP) treated cavities. The proposal looks to develop transformative surface preparation treatments to improve the operational gradient of spare cryomodules higher than 10 MV/m while maintaining high Q. Thus, increasing operational margin by 30 - 50%. With the goal to improve operational reliability set, the proposal will investigate multiple objectives as possible paths forward to achieve an overall increase in cavity performance and gain a better understanding of SRF limiting mechanisms. The proposal will study the application of different chemical surface treatments to 0.53 half-wave cavities, with the addition of low temperature bakes (LTB), and measure their effects on accelerating performance. Proposed chemical treatments to be explored in this proposal include conventional EP acid mixtures, as well as innovated EP and BCP acid mixtures designed to simplify processing paths in migrating FE and HFQS. The proposed transformative treatment wet N-doping also has the potential to replicate recent advancements in SRF technology relating to nitrogen doping and high Q operation without the requirement for an ultra-high vacuum annealing furnace; currently being developed at FNAL and JLAB. In parallel, high Q performance relating to flux trapping will be investigated with the installation of a second layer of magnetic shielding in the vertical test Dewar. The research objectives presented in the proposal, and their corresponding effects on cavity performance, will provide essential knowledge and future guidance to the SRF community and provide possible paths for future SRF based projects and applications.
43 PARTICLE ACCELERATORS↗
Process modeling guides operational variables that affect CO 2 utilization during the accelerated carbonation of concrete
Abstract Accelerated concrete carbonation is an expanding option for decarbonizing construction. Factors such as concrete mixture design and carbonation environment can influence the maximum CO 2 utilization that can be achieved during such a process. A carbonation process designed to utilize a water‐saturated dilute CO 2 source wherein 2 < CO 2 concentration (v/v%) < 16, was modeled in AspenPlus©. A regression model was developed to correlate CO 2 uptake, relative humidity (11%–100%), CO 2 concentration ([CO 2 ] = 2—16 v/v%), and temperature ( T = 11–74°C) conditions within a carbonation reactor. It was determined that [CO 2 ] was the most significant variable as higher concentrations enhanced CO 2 transport through the concrete. The energy use intensity per mass of CO 2 utilized (kWh/kgCO 2 ) was determined across a range of processing conditions. As a function of the operational conditions, accelerated carbonation provides a net CO 2 reduction of up to 28 kgCO 2 /tonne of concrete; a reduction of up to ~45% compared to typical formulations.
Prentice, Dale P.↗
Predicting the rheology of limestone calcined clay cements (LC 3 ): Linking composition and hydration kinetics to yield stress through Machine Learning
The physicochemical characteristics of calcined clay influence yield stress of limestone calcined clay cements (LC 3 ), but the independent influences the clay's physical and chemical characteristics as well as the effect of other variables on LC 3 rheology are less well-understood. Further, a relationship between LC 3 hydration kinetics and yield stress – important for informing mixture design – has not yet been established. Here, rheological properties were determined in pastes with varying water-to-solid ratio (w/s), constituent mass ratios (PC:metakaolin:limestone), limestone particle size and gypsum content. From these data, an ML model developed allowed the independent examination of the different mechanisms by which metakaolin fraction influences yield stress of LC 3 , identifying four predictors – packing index, Al 2 O 3 /SO 3 , total particle density and metakaolin fraction relative to limestone (MK/LS) – most significant for predicting LC 3 yield stress. A methodology based on kernel smoothing also identified hydration kinetics parameters best correlated with yield stress.
36 MATERIALS SCIENCE↗
Fluctuating hydrodynamics and the Rayleigh–Plateau instability
The Rayleigh–Plateau instability occurs when surface tension makes a fluid column become unstable to small perturbations. At nanometer scales, thermal fluctuations are comparable to interfacial energy densities. Consequently, at these scales, thermal fluctuations play a significant role in the dynamics of the instability. These microscopic effects have previously been investigated numerically using particle-based simulations, such as molecular dynamics (MD), and stochastic partial differential equation–based hydrodynamic models, such as stochastic lubrication theory. In this paper, we present an incompressible fluctuating hydrodynamics model with a diffuse-interface formulation for binary fluid mixtures designed for the study of stochastic interfacial phenomena. An efficient numerical algorithm is outlined and validated in numerical simulations of stable equilibrium interfaces. We present results from simulations of the Rayleigh–Plateau instability for long cylinders pinching into droplets for Ohnesorge numbers of Oh = 0.5 and 5.0. Both stochastic and perturbed deterministic simulations are analyzed and ensemble results show significant differences in the temporal evolution of the minimum radius near pinching. Short cylinders, with lengths less than their circumference, were also investigated. As previously observed in MD simulations, we find that thermal fluctuations cause these to pinch in cases where a perturbed cylinder would be stable deterministically. Finally, we show that the fluctuating hydrodynamics model can be applied to study a broader range of surface tension–driven phenomena.
97 MATHEMATICS AND COMPUTING↗
Computational Design of Eutectic Molten Salt Mixtures: What Can Thermodynamic Models Do?
In the search for efficient energy storage battery technologies, designing stable electrolytes has been a long-standing challenge. Electrolytes based on molten salt eutectics are known for their stability with minimum parasitic reactions when compared to their widely used organic counterparts. However, the operating temperatures of these molten salt electrolyte-based batteries are dictated by the melting point of the eutectic mixtures. Design and high throughput screening of low melting temperature eutectic molten salt mixtures have been hindered by the lack of computational models. In this work, we develop thermodynamic models to predict the eutectic points of several molten salt mixtures. The framework of the COSMO-SAC model is used for the predictions and is compared with experimental data and other thermodynamic approaches. Rapid thermodynamics-based approaches, as shown in this study, can accelerate the discovery of new materials, complementing experimental techniques.
Ashwin Ravichandran↗
Population-based heteropolymer design to mimic protein mixtures
Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.
59 BASIC BIOLOGICAL SCIENCES↗
Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures
Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.
Thermodynamics↗
Design aspects of explosive mixtures in a vehcile interstage final report
Prevention and control of explosive mixture of hydrogen and oxygen within vehicle interstage
EXPLOSIVE↗
Rate and Gain Limitations of MSGC's and MGC's Combined with GEM and other Preamplification Structures
We have studied the rate and gain limits of diamond-coated Microstrip Gas Counters (MSGC's) and Micro-Gap Counters (MGC's) when combined with various preamplification structures: Gas Electron Multiplier (GEM), Parallel-Plate Avalanche Chamber (PPAC) or a MICROMEGAS-type structure. Measurements were done both with X rays and alpha particles with various detector geometries and in different gas mixtures at pressures from 0.05 to 10 atm. The results obtained varied significantly with detector design, gas mixture and pressure, but some general features can be identified. We found that in all cases, bare MSGC'S, MGC'S, PPAC's and MICROMEGAS, the maximum achievable gain drops with rate. The addition of preamplification structures significantly increases the gain of MSGC's and MGC'S, but this gain is still rate dependent. There would seem to be a general rate-dependent effect governing the usable gain of all these detectors. We speculate on possible mechanisms for this effect, and identify a safe, spark-free, operation zone for each system (detector + preamplification structure) in the rate-gain coordinate plane.
Fonte, P.↗
Designing a Block Copolymer Membrane for Selective Transport of Lactic Acid from Aqueous Mixtures
We report the design and synthesis of a triblock copolymer-based membrane for enabling selective transport of lactic acid from aqueous solutions. This is relevant to the production of polylactic acid, one of the few biodegradable and biobased polymers with sufficient mechanical strength for practical applications. The end blocks are positively charged with negatively charged lactate counterions. The middle block is polybutadiene (PBD). Due to microphase separation, the charged blocks form channels for transporting lactic acid. The mechanical integrity of the membrane is controlled by cross-linking the PBD block. Transport of lactic acid and water across the membrane was studied by placing the membrane between two chambers, a feed chamber containing aqueous lactic acid solutions, and a receiving chamber containing pure water. The lactic acid concentration in the receiving chamber was monitored as a function of time using conductivity, HPLC, and NMR. The corresponding flux of water from the receiving chamber to the feed chamber was measured using an NMR-based approach. The lactic acid and water permeabilities through our membrane were (1.12 ± 0.05) × 10–8 and (8.58 ± 0.75) × 10–9 cm2 s–1. To our knowledge, there are no reports of lactic acid permeabilities through any membrane in the literature. The separation factor of our membrane, αLA/water, 1.305 ± 0.123, is comparable to that of membranes used for selective transport of ethanol, despite the fact that lactic acid is a much larger molecule than ethanol. Selective transport of lactic acid in our membrane is governed mainly by differences in solubility; lactic acid is 18 times more soluble in the membrane than water.
Jana, Rounak↗