Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Chemically driven flow”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An experimental database of cell performance for vanadium redox flow battery

The continual growth in energy demand has resulted in the deployment of renewable energy generators to reduce the impact of fossil fuel dependence. However, these generators often suffer from intermittency and require energy storage when there is over-generation and the subsequent release of this stored energy at high demand. One promising energy storage technology which can provide a solution to improve energy management and grid stability, is the redox flow battery. Among the numerous flow battery systems, vanadium redox flow battery is the most iconic solution to large scale energy storage, giving a more efficient link between energy production, especially from renewables, and energy demand. The aim of the current database is to characterize the performance of the cell design and to provide training/validation data for physical model or data-driven model. The database includes hundreds of experimental cell performance data of vanadium redox flow battery with various current densities for multiple charge-discharge cycles. All the cell parameters, chemical parameters, material parameters, operation parameters and thermodynamic parameters of the cell system are listed. Coulomb, voltaic and energy efficiencies are also provided. The database will be helpful for researchers in the field of redox flow batteries.

Gao, Peiyuan↗
DOE OSTI2023

Using Co-Optimized Machine Learned Manifolds for Modeling Chemically Reacting Flows

Chemically reacting flows play a key role in a wide range of engineered systems, from chemical and polymer processing to combustion-based energy conversion technologies. Simulations of these flows involve solving a coupled set of partial differential equations for mass, momentum, energy, and all relevant chemical species in the system. Chemical reaction pathways may be extremely complex and involve hundreds or more intermediate species, with reactions that occur over timescales varying by several orders of magnitude - presenting a significant numerical stiffness challenge. The combination of these factors makes simulation of chemically reacting flows vastly more expensive than nonreactive simulations, and often makes direct solution of the governing equations intractable. It is necessary to apply lower-fidelity models in place of the detailed governing equations in order to reduce computational cost to enable reacting flow simulation tools to be used in the engineering design process. Many of the models employed for this purpose are based on reducing the dimension of the thermochemical state, motivated by the observation that the observed thermochemical states in a system lie on a low-dimensional manifold in thermochemical state space. This behavior occurs due to the fast equilibration of certain reactive and transport processes, and physics-based manifold models rely on idealized assumptions about the balance of timescales and the way in which chemistry and transport are coupled. In this work, we apply a novel method for data-driven manifold-based modeling that can leverage data from high-fidelity reacting flow simulations to improve model accuracy in cases where the physics-based modeling assumptions break down. The approach is designed to be broadly applicable across chemically reacting flow systems but is applied here to turbulent combustion modeling.

machine learning↗
NASA NTRS1993

Models of thermal/chemical boundary layer convection: Potential application to Venus

The upper boundary layer of Venus is comprised of at least two distinct chemical components, mantle and crust. Fluid dynamical models of convection within Venus' mantle were primarily of the thermal boundary layer type. Models assessing the ability of convective mantle flows to deform the crust were undertaken, but models exploring the effects of a variable thickness crust on mantle convection were largely lacking. A Venusian crust of variable thickness could couple back into, and alter, the mantle flow patterns that helped create it, leading to deformation mechanisms not predicted by purely thermal boundary layer convection models. This possibility is explored through a finite element model of thermal/chemical boundary layer convection. Model results suggest that a crust of variable thickness can serve as a mantle flow driver by perturbing lateral temperature gradients in the upper mantle. Resulting mantle flow is driven by the combination of free convective and nonuniform crustal distribution. This combination can lead to a flow instability manifest in the occurrence of episodic mantle lithosphere subduction initiated at the periphery of a crustal plateau. The ability of a light, near surface, chemical layer to potentially alter mantle flow patterns suggest that mantle convection and the creation and/or deformation of such a chemical layer may be highly nonseparable problems on time scales of 10(exp 8) years.

Lenardic, A.↗
DOE OSTI2024

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Magnetized, radiofrequency-driven hollow cathode chemical-vapor deposition of ultrathick hydrogenated amorphous carbon

Amorphous carbon is an attractive material for next-generation inertial confinement fusion (ICF) ablators due to its amorphous structure, tunable density, compatibility with dopants, chemical inertness, and mechanical robustness. Ablators are typically deposited as ultrathick (10–200 μm) coatings on removable spherical templates. The deposition of such thick amorphous carbon films is challenging due to high intrinsic compressive stress, which causes film buckling and delamination. Here, we study the deposition of amorphous carbon films by magnetized, radiofrequency-driven hollow cathode chemical vapor deposition with a custom-designed source in Ne plasmas. Emphasis is on the hollow-cathode source design and effects of the plasma discharge power and the precursor flow rate on film properties. We demonstrate deposition rates of >1 μm/h for films with hydrogen content of ∼40 at. %, densities of 1.1–1.7 g/cm 3 , and trace quantities of oxygen impurities. In conclusion, we also demonstrate the feasibility of depositing thick hydrogenated amorphous carbon films (∼30 μm) for ICF applications.

Carbon based materials↗
NASA NTRS2004

Novel Microstructures for Polymer-Liquid Crystal Composite Materials

There are a number of interface-dominated composite materials that contain a liquid crystalline (LC) phase in intimate contact with an isotropic phase. For example, polymer- dispersed liquid crystals, used in the fabrication of windows with switchable transparency, consist of micron size LC droplets dispersed in an isotropic polymer matrix. Many other types of liquid crystal composite materials can be envisioned that might have outstanding optical properties that could be exploited in novel chemical sensors, optical switches, and computer displays. This research project was based on the premise that many of these potentially useful LC composite materials can only be fabricated under microgravity conditions where gravity driven flows are absent. In the ground-based research described below, we have focused on a new class of LC composites that we call thermotropic- lyotropic liquid crystal systems (TLLCs). TLLCs consist of nanosize droplets of water dispersed in an LC matrix, with surfactants at the interface that stabilize the structure. By varying the type of surfactant one can access almost an infinite variety of unusual LC composite microstructures. Due to the importance of the interface in these types of systems, we have also developed molecular simulation models for liquid crystals at interfaces, and made some of the first measurements of the interfacial tension between liquid crystals and water.

Magda, Jules J.↗
NASA NTRS2013

Atomic Force Microscope Mediated Chromatography

The atomic force microscope (AFM) is used to inject a sample, provide shear-driven liquid flow over a functionalized substrate, and detect separated components. This is demonstrated using lipophilic dyes and normal phase chromatography. A significant reduction in both size and separation time scales is achieved with a 25-micron-length column scale, and one-second separation times. The approach has general applications to trace chemical and microfluidic analysis. The AFM is now a common tool for ultra-microscopy and nanotechnology. It has also been demonstrated to provide a number of microfluidic functions necessary for miniaturized chromatography. These include injection of sub-femtoliter samples, fluidic switching, and sheardriven pumping. The AFM probe tip can be used to selectively remove surface layers for subsequent microchemical analysis using infrared and tip-enhanced Raman spectroscopy. With its ability to image individual atoms, the AFM is a remarkably sensitive detector that can be used to detect separated components. These diverse functional components of microfluidic manipulation have been combined in this work to demonstrate AFM mediated chromatography. AFM mediated chromatography uses channel-less, shear-driven pumping. This is demonstrated with a thin, aluminum oxide substrate and a non-polar solvent system to separate a mixture of lipophilic dyes. In conventional chromatographic terms, this is analogous to thin-layer chromatography using normal phase alumina substrate with sheardriven pumping provided by the AFM tip-cantilever mechanism. The AFM detection of separated components is accomplished by exploiting the variation in the localized friction of the separated components. The AFM tip-cantilever provides the mechanism for producing shear-induced flows and rapid pumping. Shear-driven chromatography (SDC) is a relatively new concept that overcomes the speed and miniaturization limitations of conventional liquid chromatography. SDC is based on a sliding plate system, consisting of two flat surfaces, one of which has a recessed channel. A fluid flow is produced by axially sliding one plate past another, where the fluid has mechanical shear forces imposed at each point along the channel length. The shear-induced flow rates are very reproducible, and do not have pressure or voltage gradient limitations. SDC opens up a new range of enhanced separation kinetics by permitting the sample confinement with submicron dimensions. Small, highly confined liquid is advantageous for chromatographic separation because the separation rate is known to scale according to the square of the confined sample diameter. In addition, because shear-driven flows are not limited by fluid velocity, shear-driven liquid chromatography may provide up to 100,000 plate efficiency.

Anderson, Mark S.↗
NASA NTRS1988

Convection and mass-transport in laser-induced chemical vapor deposition

Gas flow and energy and species transport in laser-induced chemical vapor deposition (LICVD) of amorphous silicon films by silane pyrolysis are analyzed by finite element analysis of a two-dimensional model for the process. Spatial nonuniformity of the deposited film is shown to result from diffusion controlled transport of products between the beam and substrate. Deposition profiles are affected by buoyancy-driven convection only at increased gas pressures. Horizontal orientation of the reactor with respect to gravity is optimal because the stagnation-like flow, that results adjacent to the substrate, enhances mixing, and smoothes the film profile.

Patnaik, S.↗
DOE OSTI2021

A priori examination of reduced chemistry models derived from canonical stirred reactors using three-dimensional direct numerical simulation datasets

Data-driven approaches to construct reduced chemical kinetic models, that rely heavily on thermo-chemical datasets with full chemical kinetics, have been gaining popularity. Datasets from direct numerical simulations (DNS) under three-dimensional (3-D) realistic turbulent flow conditions are desirable but limited to carefully designed parametric conditions due to the computational cost. Constructing datasets from a large ensemble of zero-dimensional stirred reactors like perfectly stirred reactor (PSR) and partially stirred reactor (PaSR) is a computationally efficient solution to consider the turbulence-chemistry interactions and cover a broad range of parametric conditions. In this paper, we derive reduced chemistry models from solutions of a large number of PSR and PaSR reactors using autoencoder (AE) neural networks and principal component analysis (PCA), and conduct a priori examination of the reduced models in three temporally evolving 3-D DNS jet flames featuring local extinction and re-ignition. The results show that the reduced models derived from PaSR datasets, i.e., AE-PaSR and PCA-PaSR, generally show significant improvement over the ones derived from PSR datasets. Among all the reduced models, AE-PaSR shows the best agreement with DNS results on the reconstruction accuracy and the representation of temporally evolving local extinction and re-ignition events.

Zhang, Pei↗
NASA NTRSDate not supplied

Demonstration of in-Situ Resource Utilization of Lunar Regolith for Plant Growing Systems Through Scaled Capillary Models

The development of reliable and bioregenerative crop growth production systems is vital for human exploration into deep space. As the National Aeronautics and Space Administration (NASA) prepares for the Artemis missions, scientists need to find a way to provide consistent and sufficient water delivery for all stages of a plant’s life cycle. NASA has been able to successfully model passive flow through felt material, to mimic the water uptake and transport through a plant, in microgravity. However, more studies need to be conducted to adapt the model for a substrate-based system and incorporate how flow will change during each stage of plant growth. For future missions, payload requirements to support crop production systems will need to be limited, leading to the use of available resources, such as lunar regolith. Although numerous lunar regolith simulants are commercially available, few have been evaluated for their suitability in agricultural applications. First, a base regolith simulant will need to be identified based on its physical and chemical properties. Then, additional amendments to improve the properties of the simulants to support plant growth will be identified. The design and composition of the substrate will be based on water transport requirements for different stages of plant growth. Scaled capillary models can be utilized to study surface-tension driven flows through various designer substrates to modify the physical properties of the selected regolith simulant. These models can accurately represent how flow will act in a reduced gravity environment, which can be used to design a full-scale facility for surface missions. This project will aid space researchers in the design of future crop production systems for surface missions by creating a refined model that can be used at all stages of plant growth and utilize in situ resources.

Fluids↗
DOE OSTI2021

Seasonal changes in the drivers of water physico-chemistry variability of a small freshwater tidal river

Where rivers meet the sea, tides can exert a physical and chemical influence on the lower reaches of a river. How tidal dynamics in these tidal river reaches interact with upstream hydrological drivers such as storm rainfall, which ultimately determines the quantity and composition of material transferred from watersheds to estuaries, is currently unknown. We monitored a small freshwater tidal river in the Pacific Northwest, USA in high resolution over one year to evaluate the relative importance of tides versus upstream hydrological flows (i.e., base flow and precipitation events) on basic physico-chemical parameters (pH, dissolved oxygen, turbidity, specific conductivity, and temperature), and how these interactions relate to the downstream estuary. Tidal variability and diurnal cycles (i.e. solar radiation) dominated water physico-chemical variability in the summer, but the influence of these drivers was overshadowed by storm-driven sharp pulses in river physico-chemistry during the remainder of the year. Within such events, we found incidences of counterclockwise hysteresis of pH, counterclockwise hysteresis of dissolved oxygen, and clockwise hysteresis of turbidity, although systematic trends were not observed across events. The dominance of storm rainfall in the river’s physico-chemistry dynamics, and similar pulses of decreased pH observed in adjacent estuarine waters, suggest that the linkage between tidal streams and the broader system is variable throughout the year. High-frequency monitoring of tidal river biogeochemistry is therefore crucial to enable the assessment of how the relative strength of these drivers may change with future sea level rise and altered precipitation patterns to modulate biogeochemical dynamics across the land-ocean-atmosphere continuum.

aquatic↗
NASA NTRS2008

Microfluidics, Chromatography, and Atomic-Force Microscopy

A Raman-and-atomic-force microscope (RAFM) has been shown to be capable of performing several liquid-transfer and sensory functions essential for the operation of a microfluidic laboratory on a chip that would be used to perform rapid, sensitive chromatographic and spectro-chemical analyses of unprecedentedly small quantities of liquids. The most novel aspect of this development lies in the exploitation of capillary and shear effects at the atomic-force-microscope (AFM) tip to produce shear-driven flow of liquids along open microchannels of a microfluidic device. The RAFM can also be used to perform such functions as imaging liquids in microchannels; removing liquid samples from channels for very sensitive, tip-localized spectrochemical analyses; measuring a quantity of liquid adhering to the tip; and dip-pen deposition from a chromatographic device. A commercial Raman-spectroscopy system and a commercial AFM were integrated to make the RAFM so as to be able to perform simultaneous topographical AFM imaging and surface-enhanced Raman spectroscopy (SERS) at the AFM tip. The Raman-spectroscopy system includes a Raman microprobe attached to an optical microscope, the translation stage of which is modified to accommodate the AFM head. The Raman laser excitation beam, which is aimed at the AFM tip, has a wavelength of 785 nm and a diameter of about 5 m, and its power is adjustable up to 10 mW. The AFM is coated with gold to enable tip-localized SERS.

Anderson, Mark↗
DOE OSTI2023

Leveraging the Polymer Glass Transition to Access Thermally Switchable Shear Jamming Suspensions

Suspensions of polymeric nano-and microparticles are fascinating stress-responsive material systems that, depending on their composition, can display a diverse range of flow properties under shear, such as drastic thinning, thickening, and even jamming (reversible solidification driven by shear). However, investigations to date have almost exclusively focused on nonresponsive particles, which do not allow in situ tuning of the flow properties. Polymeric materials possess rich phase transitions that can be directly tuned by their chemical structures, which has enabled researchers to engineer versatile adaptive materials that can respond to targeted external stimuli. Reported herein are suspensions of (readily prepared) micrometer-sized polymeric particles with accessible glass transition temperatures (T g ) designed to thermally control their non-Newtonian rheology. The underlying mechanical stiffness and interparticle friction between particles change dramatically near T g . Capitalizing on these properties, it is shown that, in contrast to conventional systems, a dramatic and nonmonotonic change in shear thickening occurs as the suspensions transition through the particles' T g . This straightforward strategy enables the in situ turning on (or off) of the system's ability to shear jam by varying the temperature relative to T g and lays the groundwork for other types of stimuli-responsive jamming systems through polymer chemistry.

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

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Warm-Based Glacial Landforms and Past Climate Signals: Icelandic Eskers as Proxies for Small Sinuous Ridges on Mars

The surface of Mars exhibits plentiful geomorphic evidence for glacial processes, but the history of the cryosphere on Mars remains debated [e.g., 1, 2]. Recent hydrological modeling predicts that warm-based ice sheets on Mars may have resulted in subglacial incised channels (e.g., valley networks) and eskers [3]. Evidence on Mars for warm-based glaciation includes candidate moraines, bedrock channels, and candidate eskers [e.g., 4-6]. Eskers are sinuous ridges comprising glaciofluvial sediments deposited by meltwater flowing through tunnels at the bed of warm-based large glaciers [e.g., 7, 8]. They provide direct evidence of basal melting of ice and preserve glaciofluvial sediments. Warm-based glacial transport is primarily driven by meltwater and can chemically weather the underlying bedrock. An alternative signature of past climate on Mars may thus be the geochemical record, due to alteration by interactions with glacial meltwater, preserved in esker sediments and strata. At present, the sedimentology and stratigraphy of terrestrial eskers is poorly understood. This study will combine sedimentology, geochemistry, and geomorphology to better constrain the unique properties of eskers resulting from warm-based glaciation on Mars-like substrates by leveraging a natural laboratory in Iceland.

A. M. Rutledge↗
NASA NTRS2007

Radiolytic Gas-Driven Cryovolcanism in the Outer Solar System

Water ices in surface crusts of Europa, Enceladus, Saturn's main rings, and Kuiper Belt Objects can become heavily oxidized from radiolytic chemical alteration of near-surface water ice by space environment irradiation. Oxidant accumulations and gas production are manifested in part through observed H2O2 on Europa. tentatively also on Enceladus, and found elsewhere in gaseous or condensed phases at moons and rings of Jupiter and Saturn. On subsequent chemical contact in sub-surface environments with significant concentrations of primordially abundant reductants such as NH3 and CH4, oxidants of radiolytic origin can react exothermically to power gas-driven cryovolcanism. The gas-piston effect enormously amplifies the mass flow output in the case of gas formation at basal thermal margins of incompressible fluid reservoirs. Surface irradiation, H2O2 production, NH3 oxidation, and resultant heat, gas, and gas-driven mass flow rates are computed in the fluid reservoir case for selected bodies. At Enceladus the oxidant power inputs are comparable to limits on nonthermal kinetic power for the south polar plumes. Total heat output and plume gas abundance may be accounted for at Enceladus if plume activity is cyclic in high and low "Old Faithful" phases, so that oxidants can accumulate during low activity phases. Interior upwelling of primordially abundant NH3 and CH4 hydrates is assumed to resupply the reductant fuels. Much lower irradiation fluxes on Kuiper Belt Objects require correspondingly larger times for accumulation of oxidants to produce comparable resurfacing, but brightness and surface composition of some objects suggest that such activity may be ongoing.

Cooper, John F.↗
NASA NTRS2009

Old Faithful Model for Radiolytic Gas-Driven Cryovolcanism at Enceladus

A new model is presented on how chemically driven cryovolcanism might contribute to episodic outgassing at the icy moon Enceladus and potentially elsewhere including Europa and Kuiper Belt Objects. Exposed water ices can become oxidized from radiolytic chemical alteration of near-surface water ice by space environment irradiation. In contact with primordially abundant reductants such as NH3, CH4, and other hydrocarbons, the product oxidants can react exothermically to produce volatile gases driving cryovolcanism via gas-piston forces on any subsurface liquid reservoirs. Radiolytic oxidants such as H2O2 and O2 can continuously accumulate deep in icy regoliths and be conveyed by rheological flows to subsurface chemical reaction zones over million-year time scales indicated by cratering ages for active regions of Enceladus and Europa. Surface blanketing with cryovolcanic plume ejecta would further accelerate regolith burial of radiolytic oxidants. Episodic heating from transient gravitational tides, radioisotope decay, impacts, or other geologic events might occasionally accelerate chemical reaction rates and ignite the exothermic release of cumulative radiolytic oxidant energy. The time history for the suggested "Old Faithful" model of radiolytic gas-driven cryovolcanism at Enceladus and elsewhere therefore consists of long periods of chemical energy accumulation punctuated by much briefer episodes of cryovolcanic activity. The most probable sequence for detection of activity in the current epoch is a long evolutionary phase of slow but continuous oxidant accumulation over billions of years followed by continuous but variable high activity over the past 10(exp 7)-10(exp 8) years. Detectable cryovolcanic activity could then later decline due to near-total oxidation of the rheologically accessible ice crust and depletion the accessible reductant abundances, as may have already occurred for Europa in the more intense radiation environment of Jupiter's magnetosphere. Astrobiological potential of Enceladus could correspondingly be higher than at Europa due to a less extreme state of oxidation and greater residual abundance of organics.

Cooper, John F.↗
DOE OSTI2025

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.

Tamura, Clara [Univ. of Washington, Seattle, WA (U↗