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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Overview of the Subscale RAVEN Flight Controls and Modeling Testbed

The Research Aircraft for eVTOL Enabling TechNologies (RAVEN) Subscale Wind-Tunnel and Flight Test (SWFT) model is a subscale aircraft built for flight dynamics and controls research demonstrated in wind-tunnel and flight-test experiments. The intent of this paper is to provide a summary of past, current, and future efforts being pursued by the RAVEN-SWFT project. Initially, vehicle development guidelines were crafted by a multidisciplinary team to ensure that the RAVEN-SWFT vehicle was well suited for research in multiple areas, including aero-propulsive modeling, flight controls, and autonomy, among others. The vehicle has been used to obtain extensive wind-tunnel data, enabling aero-propulsive model development across the transition flight envelope and validation of computational tools. The vehicle will be used to conduct flight testing in order to evaluate modeling strategies and flight control logic. The RAVEN-SWFT model also serves as a risk reduction activity for a conceptual, full-scale vehicle in the 1000-lb class. The next steps in the project are to successfully demonstrate free flight in hover, transition, forward flight, and the reverse thereof, utilizing custom control laws integrated onto the RAVEN-SWFT avionics hardware. The project intends to publicize all of the geometry, data, and methods in future reports.

eVTOL↗
DOE OSTI2025

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

Scheduling Accessory Assists Patients with Cognitive Disorders

Recom Technologies Inc. received initial funding from NASA to research the commercial potential of an artificially intelligent planning reaction model to serve as a tool to help individuals suffering from various forms and levels of brain impairment. In 1993, the chief of the Artificial Intelligence Research Branch at Ames Research Center suggested collaborative research with Santa Clara Valley Medical Center. This partnership led to further development of the technology and funding to support clinical research from the U.S. Department of Education's National Institute on Disability and Rehabilitation Research. In 1996, Attention Control Systems Inc. was founded to market the finished device, called the Planning and Execution Assistant and Trainer (PEAT). PEAT is a pocket-sized PDA-like device with a graphical display, touchscreen controls, an electronic calendar, an address book, and a built-in phone, that cues users to start or stop scheduled activities, monitors their progress, and adjusts schedules as necessary in response to delays or calendar changes. It uses an automatic planning model developed for NASA to adjust daily plans when a situation changes. PEAT is sold as a complete system that includes software, hardware, documentation, and technical support. In addition to the flagship Pocket PEAT device, there is PEAT Phone, PC PEAT, and PEAT Link. Clinical studies of PEAT continue at Santa Clara Valley Medical Center

Source record↗
NASA NTRS2006

Solar Sails

The Solar Sail Propulsion investment area has been one of the three highest priorities within the In-Space Propulsion Technology (ISPT) Project. In the fall of 2003, the NASA Headquarters' Science Mission Directorate provided funding and direction to mature the technology as far as possible through ground research and development from TRL 3 to 6 in three years. A group of experts from government, industry, and academia convened in Huntsville, Alabama to define technology gaps between what was needed for science missions to the inner solar system and the current state of the art in ultra1ightweight materials and gossamer structure design. This activity set the roadmap for development. The centerpiece of the development would be the ground demonstration of scalable solar sail systems including masts, sails, deployment mechanisms, and attitude control hardware and software. In addition, new materials would be subjected to anticipated space environments to quantify effects and assure mission life. Also, because solar sails are huge structures, and it is not feasible to validate the technology by ground test at full scale, a multi-discipline effort was established to develop highly reliable analytical models to serve as mission assurance evidence in future flight program decision-making. Two separate contractor teams were chosen to develop the SSP System Ground Demonstrator (SGD). After a three month conceptual mission/system design phase, the teams developed a ten meter diameter pathfinder set of hardware and subjected it to thermal vacuum tests to compare analytically predicted structural behavior with measured characteristics. This process developed manufacturing and handling techniques and refined the basic design. In 2005, both contractor teams delivered 20 meter, four quadrant sail systems to the largest thermal vacuum chamber in the world in Plum Brook, Ohio, and repeated the tests. Also demonstrated was the deployment and articulation of attitude control mechanisms. In conjunction with these tests, the stowed sails were subjected to launch vibration and ascent vent tests. Other investments studied radiation effects on the solar sail materials, investigated spacecraft charging issues, developed shape measuring techniques and instruments, produced advanced trajectory modeling capabilities, and identified and resolved gossamer structure dynamics issues. Technology validation flight and application to a He1iophysics science mission is on the horizon.

Young, Roy↗
DOE OSTI2025

Hydrodynamic characterization of the coastal pioneer array ocean observing system

Ocean observation buoys require relatively small amounts of power, yet traditionally necessitate costly resupply trips for battery replacement. With the offshore location of the buoys and small power requirements, wave energy may be an effective solution for providing consistent and reliable power to support the buoy instrumentation. The US National Science Foundation Ocean Observatories Initiative (OOI) includes arrays of point absorber-like buoy systems used for ocean observation that have been deployed at multiple locations including the Southern Mid-Atlantic Bight. A study is currently underway to design a pitch resonator wave energy converter to supplement existing renewable energy generation for powering observation instrumentation. This paper details field measurements from surface moorings of the OOI Coastal Pioneer Array, which informs the subsequent development of a numerical model for the moored observation system. The model is developed in Wave Energy Converter Simulator (WEC-Sim), which leverages the Simscape multibody solver within the MATLAB/Simulink framework and linear potential flow theory to simulate the hydrodynamic interactions and multibody dynamics in 6 degrees of freedom. Multiple tuning variables are considered to produce a model for the system that matches well with empirical data (about 8% error). In conclusion, the WEC-Sim model will serve as a platform for integrating the pitch resonator wave energy converter concept and deployment preparation (detailed design including power take-off and control systems, response evaluation, etc.).

hydrodynamic modeling↗
DOE OSTI2026

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗
DOE OSTI2026

Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process‐Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process-based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data-constrained representation of the sterile triploid Miscanthus (IL clone) within the process-based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam-derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO 2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field-measured biomass. Building on the calibrated operating state, parameter-response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post-calibration GPP R 2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R 2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

ecosys↗
DOE OSTI2021

Anion Exchange Ionomers: Impact of Chemistry on Thin-Film Properties

Ionomer thin-films (i.e., 20–100 nm) on supports serve as model systems to understand ionomer-catalyst interfacial behavior as well as the confinement-driven deviation in properties from bulk membranes. While ionomer thin-films have been examined for proton exchange ionomers, the thin-film properties of anion exchange ionomers (AEIs) remain largely unexplored. More importantly, delineating the convoluted impact of chemistry and confinement on thin-film morphology and hydration is of interest to advancing the field on functional ionic interfaces. In this work, these aspects are studied by using AEIs of different backbones (perfluorinated, aliphatic, and aromatic) and side chains (various lengths, and single versus dual functional groups). Quartz-crystal microbalance and spectroscopic ellipsometry are used to analyze density and coupled with calculated free volume fraction of thin-films to provide insights on their gas transport properties. AEI side-chain's chemical character plays a key role in how confinement modulates hydration (in thin-film versus bulk). Overall, the results elucidate the effects of backbone, side-chain chemistry versus anion/cation type in the confinement-driven changes in thin-film morphology and swelling. This study also provides new insights for tuning AEI transport functionalities at interfaces via chemistry, which can benefit the design and development of electrode-ionomers for alkaline membrane-based energy systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling salt adsorption in electrical double layer for capacitive deionization

Abstract This work presents an electrical double layer (EDL) model for capacitive deionization (CDI) by intercorrelating the salt adsorption, the electrode voltage, and the surface charge density. The counterion condensation is considered a crucial contribution to salt adsorption because of the high surface charge density in the charged micropores. The counterions condense when the surface charge density exceeds a critical value, which is predicted by the counterion condensation theory. The EDL model accurately correlates the NaCl salt adsorption and electrode voltage with various surface charge densities and well predicts the salt adsorption in a wide range of external salt concentrations. The EDL model reproduces the non‐monotonic relationship between the salt adsorption and the specific surface area observed in experiments and provides an explanation from the modeling perspective. Exhibiting superior accuracy and predictability for salt adsorption, the EDL model could serve as an enabling tool contributing to the development of CDI processes.

Lin, Yu‐Jeng↗
DOE OSTI2021

Evolution of eggshell structure in relation to nesting ecology in non-avian reptiles

Amniotic eggs are multifunctional structures that enabled early tetrapods to colonize the land millions of years ago, and are now the reproductive mode of over 70% of all terrestrial amniotes. Eggshell morphology is at the core of animal survival, mediating the interactions between embryos and their environment, and has evolved into a massive diversity of forms and functions in modern reptiles. These functions are critical to embryonic survival and may serve as models for new antimicrobial and/or breathable membranes. However, we still lack critical data on the basic structural and functional properties of eggs, particularly of reptiles. Here, we first characterized egg shape, shell thickness, porosity, and mineralization of eggs from 91 reptile species using optical images, scanning electron microscopy, and micro computed tomography, and collected data on nesting ecology from the literature. We then used comparative analyses to test hypotheses on the selective pressures driving their evolution. We hypothesized that eggshell morphology has evolved to protect shells from physical damage and desiccation, and, in support, found a positive relationship between thickness and precipitation, and a negative relationship between porosity and temperature. Although mineralization varied extensively, it was not correlated with nesting ecology variables. Ancestral state reconstructions show thinning and increased porosity over evolutionary time in squamates, but the opposite in turtles and crocodilians. Egg shape, size, porosity and calcification were correlated, suggesting potential structural or developmental tradeoffs. This study provides new data and insights into the morphology and evolution of reptile eggs, and raises numerous questions for additional research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Meshfree simulation and experimental validation of extreme thermomechanical conditions in friction stir extrusion

Abstract Friction stir extrusion (FSE) is a novel solid-phase processing technique that consolidates and extrudes metal powders, flakes, chips, or billets into high-performance parts by plastic deformation, which has the potential to save substantial processing time and energy. Currently, most studies on FSE are experimental and only a few numerical models have been developed to explain and predict the complex physics of the process. In this work, a meshfree simulation framework based on smoothed particle hydrodynamics (SPH) was developed for FSE. Unlike traditional grid-based methods, SPH is a Lagrangian particle-based method that can handle severe material deformations, capture moving interfaces and surfaces, and monitor the field variable histories explicitly without complicated tracking schemes. These aspects of SPH make it attractive for the FSE process, where in situ evolution of field variables is difficult to observe experimentally. To this end, a 3-D, fully thermomechanically coupled SPH model was developed to simulate the FSE of aluminum wires. The developed model was thoroughly validated by comparing the numerically predicted material flow, strain, temperature history, and extrusion force with experimental results for a certain set of process parameters. The validated SPH model can serve as an effective tool to predict and better understand the extreme thermomechanical conditions during the FSE process.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Thermal characterization of the build chamber in electron beam melting

Electron beam powder bed fusion, commonly termed electron beam melting (EBM), offers great versatility in multiple-part processes and can produce high quality as-built components due to low residual stresses. The EBM process is complex and requires careful thermal management, including uniform and consistent preheating of the powder bed, in order to ensure quality and consistency of the product. However, most of the simulations in the literature focus on the selective melting stage of the process. As of today, optimal conditions for initial pre-heating temperatures are only available for specific materials. Thus, in order to extend the EBM technology to other desired build materials, a much better understanding of the pre-heating stages is required. In this work, numerical and experimental approaches are combined in order to investigate the effects and sensitivities of heat removal from the build plate during EBM pre-heating stages. For this purpose, a carefully reconstructed numerical model of the build chamber of an ARCAM Q20 + machine is developed. It includes all main parts of the chamber and all relevant heat transfer mechanisms, whereas special attention is paid to radiation heat exchange between various bodies. In order to validate the model, dedicated experiments are performed, in which a system of thermocouples is installed in the build chamber, allowing direct measurement of the local temperatures of the start-plate and heat shields. A good agreement between the simulation and experimental findings is achieved, leading to a better understanding of the thermal processes characteristic to the pre-heating stages. This basic analysis is followed by a representative pre-heating case, where a powder bed is also considered. The energy required to obtain the desired pre-heating temperatures is evaluated, and the role of the powder bed in heat transfer within the chamber is assessed. The pre-heating stage, simulated in the present work, is supposed to create proper conditions for sintering and consequent melting of the powder, which are highly dependent on the local temperatures and heat transfer features. Thus, the findings of the reported work present a step towards a better understanding of the thermal processes that characterize EBM. The reported model can be further used to provide realistic boundary condition inputs for other meso- or macro-scale models as a function of time and geometry. The model can serve also for verification of machine settings, i.e., jump-safe and melt-safe ones which actually provide desired preheat, and for development of settings for new powders.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Renewable diesel and bio-aromatics production from waste cooking oil using ethanol as a hydrogen donor in deoxygenation reaction

Biofuels offer a promising solution in the fight against climate change. With a global increase in waste cooking oil, this research investigated the production of bio-hydrogenated diesel (BHD) from waste cooking oil, using ethanol as a hydrogen donor in the deoxygenation process. A hydrolyzed waste cooking oil model compound served as the feedstock, and the deoxygenation was performed at 300–400 °C. The catalysts used in the experiments were 2.6 wt% Ni and 7.8 wt% Mo (2.6Ni-7.8Mo) and 10 wt% Ni and 5 wt% Mo (10Ni-5Mo) on γ-Al 2 O 3 . The results showed that ethanol is an effective hydrogen donor for biofuel production without the need for external hydrogen at an elevated pressure. The increasing temperature enhanced the free fatty acid (FFA) conversion and n-alkane selectivity in the oil product, with the highest FFA conversion and alkane selectivity of 100 % and 46 %, respectively, observed at 400 °C for the sulfided 10Ni-5Mo catalyst. On the other hand, 2.6Ni-7.8Mo offers 100 % FFA conversion with a lower n-alkane selectivity of 35 % at identical temperatures. The total acid number (TAN) of the oil products decreased from 174.03 mg KOH/g of feedstock to 9.43 and 8.67 mg KOH/g with the sulfided 2.6Ni-7.8Mo and 10Ni-5Mo catalysts, respectively. Both the catalysts achieved similar heating values (~43 MJ/kg) at 400 °C. This is a significant improvement to the HHV of the feedstock, which was 36.02 MJ/kg. Additionally, aromatic compounds, mainly BTXE (benzene, toluene, xylene, and ethylbenzene), were also produced. Compared to glycerol as a hydrogen donor, ethanol more effectively increased n-alkane selectivity due to its higher effective hydrogen-to-carbon ratio (H/C eff ). Conversely, glycerol was more advantageous for achieving greater selectivity towards BTXE compounds due to its lower H/C eff , which potentially leads to coke formation. Since aromatic compounds are intermediates in coke production, glycerol provides higher aromatic selectivity than ethanol. Finally, this study presents an alternative pathway for producing diesel fuel from waste cooking oil using ethanol as a hydrogen donor.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CFD modeling of crystallization fouling with CO 2 desorption incorporated for a falling-film evaporator in thermal desalination

Seawater flowing around horizontal tubes in falling-film evaporators is a common configuration for thermal desalination. Heat is transferred from in-tube steam condensation to the shell-side seawater by conduction through the tube wall and scaling layer, and conduction and convection to the evaporating liquid film. CO 2 is simultaneously released from seawater and mixed with the produced vapor. Fouling coupled with CO 2 desorption has deleterious impacts on both evaporation and condensation. The evaluation of spatiotemporal dependent crystallization fouling and CO 2 desorption is vital to selecting optimal operating conditions. Here, in this work, a CO 2 desorption model is integrated into CFD modeling for predictions of coupled heat and mass transfer, to understand and predict scale formation and CO 2 desorption with local and transient profiles of temperature, carbonate species concentrations, pH, and total alkalinity. The porosity of the scale layer is experimentally determined as 67.7% and invoked in the calculation of effective thermal conductivity. The simulation results reveal that high steam temperatures increase seawater total alkalinity and accelerate scale formation. The scale thickness on the bottom tube reaches 0.30 μm and 5.24 μm for steam temperatures of 60 °C and 80 °C, respectively. High salinity leads to a large CO 2 desorption rates. The CO 2 desorption rate increases 43% when the seawater salinity increases from 35 to 55 g/kg. The effects of operating conditions on carbonate speciation and pH have been compared and analyzed. This model can serve as a comprehensive tool for the design of thermal desalination systems and optimal operation.

42 ENGINEERING↗
DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗
DOE OSTI2020

Helicity-dependent extension of the McLerran–Venugopalan model

We construct a generalization of the McLerran-Venugopalan (MV) model including helicity effects for a longitudinally polarized target (a proton or a large nucleus). The extended MV model can serve as the initial condition for the helicity generalization of the JIMWLK evolution equation constructed in our previous paper, as well as for calculation of helicity-dependent observables in the quasi-classical approximation to QCD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Dynamic Barriers to Crystallization of Calcium Barium Carbonates

Metastable carbonates play important roles in geochemistry, biomineralization and serve as model systems for nonclassical theories of nucleation and growth. Balcite (Ca 0.5 Ba 0.5 CO 3 ) is a remarkable carbonate phase that is isostructural with a high-temperature modification of calcite (CaCO 3 ), yet can be synthesized at ambient conditions. Here, we investigate crystallization pathways in the Ba-Ca-CO 3 -H 2 O system, with a focus on the transformation of amorphous calcium barium carbonate (ACBC) to balcite and subsequent decomposition into the equilibrium calcite (CaCO3) and witherite (BaCO 3 ) phases. Density functional theory calculations show that balcite is an unstable solid solution (Ca 1-x BaxCO 3 , R 3¯ m) in the range 0.17 < x < 0.5, but is accessible through the amorphous ACBC precursor for x ≲ 0.5, and predict its decomposition into calcite and witherite. We confirm this pathway experimentally but found demixing to proceed slowly and remain incomplete even after 9 months. Nucleation kinetics of balcite from ACBC was assessed using a microfluidic assay, where increasing barium content led to a surprising increase in the balcite nucleation rate, despite decreasing thermodynamic driving force. We attribute crystallization rates that dramatically accelerate with time to changes in interfacial structure and composition during coarsening of the amorphous precipitate. By carefully quantifying the thermodynamic and kinetic contributions in the multistep crystallization of a metastable carbonate, we produce insights that allow us to better interpret the formation and persistence of metastable minerals in natural and synthetic environments.

36 MATERIALS SCIENCE↗