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At least 127 records · Page 7

Mechanical Design of a UHV Non-magnetic Kappa Diffractometer

A UHV non-magnetic kappa geometry diffractometer has been designed for the resonant soft X-ray scattering (RSXS) branch of the Intermediate Energy X-ray (IEX) beamline at the Advanced Photon Source (APS), Argonne National Laboratory. The kappa geometry allows for a large q-range and space for a sample environment (electric or magnetic fields). To avoid distorting the sample environment field, non-magnetic SmarAct, GmbH stages are used for the 4)-axis, X, Y, and Z linear stages. The ic and 0 axes are controlled by high-precision UHV compatible Physik Instrumente (PI) GmbH & Co. rotation stages. The design goal was to achieve a 50 gm sphere of confusion. To achieve this, iterative designs were developed using FEA and commercial stages were chosen that had minimal wobble, eccentricity, and flatness errors.

X-ray diffractometer↗

Solvent selection for biphasic extraction of 5-hydroxymethylfurfural via multiscale modeling and experiments

We introduce a comprehensive conceptual framework for selecting solvents for reactive extraction in biphasic organic-water systems and demonstrate it for the separation of HMF (5-hydroxylmethylfurfural), a platform chemical produced in the acid-catalyzed dehydration of hexoses. We first perform in silico screening of ~2500 solvents, from the ADFCRS-2018 database using the ADF COSMO-RS implementation, and classification, based on the solvent partition coefficient. We then determine experimentally the partition coefficients for HMF, fructose, and products of HMF rehydration (levulinic acid (LA), and formic acid (FA)), the mutual water-organic solvent solubilities, and the separation factors in >50 select solvents spanning multiple homologous series at room temperature and a typical reaction temperature with in situ sampling. We find that COSMO-RS is excellent for screening purposes (typical error in most cases within a factor of ~2). Increased temperatures lead to significant reduction in partitioning, and room temperature measurements are clearly inadequate for solvent selection. Upon down selecting classes of solvents based on separation performance, we perform experimental thermal stability and reaction compatibility studies of a small set of solvents at relevant reactive-extraction temperatures. We discover that many substituted phenols exhibit an order-of-magnitude increase in partitioning compared to conventional solvents due chiefly to hydrogen bond interactions and show the necessary stability but retain a significant fraction of water and LA, factors that need to be considered in technoeconomic analysis. In contrast, anilines, aldehydes, and acids are good to excellent regarding separation but incompatible with this specific reaction medium. Furthermore, this multifaceted framework can be extended to other biomass-derived products and processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-F-J-158: Respiratory Motion Resolved, Self-Gated 4D-MRI Using Rotating Cartesian K-Space Sampling

Purpose: Dynamic MRI has been used to quantify respiratory motion of abdominal organs in radiation treatment planning. Many existing 4D-MRI methods based on 2D acquisitions suffer from limited slice resolution and additional stitching artifacts when evaluated in 3D{sup 1}. To address these issues, we developed a 4D-MRI (3D dynamic) technique with true 3D k-space encoding and respiratory motion self-gating. Methods: The 3D k-space was acquired using a Rotating Cartesian K-space (ROCK) pattern, where the Cartesian grid was reordered in a quasi-spiral fashion with each spiral arm rotated using golden angle{sup 2}. Each quasi-spiral arm started with the k-space center-line, which were used as self-gating{sup 3} signal for respiratory motion estimation. The acquired k-space data was then binned into 8 respiratory phases and the golden angle ensures a near-uniform k-space sampling in each phase. Finally, dynamic 3D images were reconstructed using the ESPIRiT technique{sup 4}. 4D-MRI was performed on 6 healthy volunteers, using the following parameters (bSSFP, Fat-Sat, TE/TR=2ms/4ms, matrix size=500×350×120, resolution=1×1×1.2mm, TA=5min, 8 respiratory phases). Supplemental 2D real-time images were acquired in 9 different planes. Dynamic locations of the diaphragm dome and left kidney were measured from both 4D and 2D images. The same protocol was also performed on a MRI-compatible motion phantom where the motion was programmed with different amplitude (10–30mm) and frequency (3–10/min). Results: High resolution 4D-MRI were obtained successfully in 5 minutes. Quantitative motion measurements from 4D-MRI agree with the ones from 2D CINE (<5% error). The 4D images are free of the stitching artifacts and their near-isotropic resolution facilitates 3D visualization and segmentation of abdominal organs such as the liver, kidney and pancreas. Conclusion: Our preliminary studies demonstrated a novel ROCK 4D-MRI technique with true 3D k-space encoding and respiratory motion self-gating. The technique leads to high-resolution and artifacts-free 4D images for improved abdominal organ motion studies. K.S acknowledges funding support from NIH R01CA188300.

60 APPLIED LIFE SCIENCES↗

CCSI Toolset 3.19 Release

CCSI Toolset 3.19 Release Highlights A gradient generation tool was developed to support GENN models in FOQUS. Certain machine learning tools train gradient-enhanced neural network (GENN) models which can be more accurate for complex datasets given a priori knowledge of model derivatives. However, the derivatives must be known beforehand and are not often available for process data. This tool automatically predicts the gradients for a training dataset in a form usable by common GENN trainers, such as Surrogate Modeling Toolbox. Support was added for Surrogate Modeling Toolbox GENN models in FOQUS, including updates to the run methods, node properties, test framework, documentation and optional dependencies list. Users can train/save Surrogate Modeling Toolbox gradient-enhanced neural network (GENN) models with custom objects and produce .pkl files compatible with the Machine Learning/Artificial Intelligence Plugin in FOQUS. A simpler implementation of the ordering algorithm in the Sequential Design of Experiments (SDOE) module was included. The SDOE examples documentation was updated. The Optimality-Based Design of Experiments was updated to improve the error handling when the results are None.

AS↗

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗

Study of the agreement between binary neutron star ejecta models derived from numerical relativity simulations

Neutron star mergers have recently become a tool to study extreme gravity, nucleosynthesis, and the chemical composition of the Universe. To date, there has been one joint gravitational and electromagnetic observation of a binary neutron star merger, GW170817, as well as a solely gravitational observation, GW190425. In order to accurately identify and interpret electromagnetic signals of neutron star mergers, better models of the matter outflows generated by these mergers are required. We compare a series of ejecta models to see where they provide strong constraints on the amount of ejected mass expected from a system, and where systematic uncertainties in current models prevent us from reliably extracting information from observed events. We also examine 2396 neutron star equations of state compatible with GW170817 to see whether a given ejecta mass could be reasonably produced with a neutron star of said equation of state, and whether different ejecta models provide consistent predictions. We find that the difference between models is often comparable to or larger than the error generally assumed for these models, implying better constraints on the models are needed. In conclusion, we also note that the extrapolation of outflow models outside of their calibration window, while commonly needed to analyze gravitational wave events, is extremely unreliable and occasionally leads to completely unphysical results.

79 ASTRONOMY AND ASTROPHYSICS↗

Key materials of vanadium flow batteries: electrolytes

Electrolytes not only dictates the device performance, but also the major part of VRFB system cost, making it as main focus of extensive research efforts in this field. Most research efforts directed towards finding an optimal supporting electrolyte and/or additive materials, which can increase the vanadium cations solubility and stability. Current research efforts were mostly trial and error methods, yielding marginal improvements in chemical/thermal stability while potentially compromising on other functional properties such as conductivity and viscosity. In addition, any supporting electrolyte and/or additives used to enhance vanadium solubility or cell potential will eventually diffuse across the membrane making it necessary to be compatible with both half-cell reactions to ensure long battery life. Another aspect of ensuring longer battery life cycle with minimum self-discharge of VRFB would be the additive/supporting electrolyte should exhibit prolonged thermal and chemical stability, typically over 30 days at battery operating temperature of -5 to 50 C. These practical requirements may limit the implementation of many additives currently under investigation. Despite extensive research, identifying the optimal material for stabilizing the vanadium electrolyte has been rather slow owing to the widely used empirical approach.

Murugesan, Vijayakumar↗

Dispersive optical systems for scalable Raman driving of hyperfine qubits

Hyperfine atomic states are among the most promising candidates for qubit encoding in quantum information processing. In atomic systems, hyperfine transitions are typically driven through a two-photon Raman process by a laser field which is amplitude modulated at the hyperfine qubit frequency. Here we introduce a method for generating amplitude modulation by phase modulating a laser and reflecting it from a highly dispersive optical element known as a chirped Bragg grating. This approach is passively stable, offers high efficiency, and is compatible with high-power laser sources, enabling large Rabi frequencies and improved quantum coherence. We benchmark this approach by globally driving an array of approximately 300 neutral 87 Rb atomic qubits trapped in optical tweezers and obtain Rabi frequencies of 2 MHz with photon-scattering error rates of less than 2×10 -4 per π pulse. This robust approach can be directly integrated with local addressing optics in both neutral atom and trapped ion systems to facilitate high-fidelity single-qubit operations for quantum information processing.

74 ATOMIC AND MOLECULAR PHYSICS↗

ON THE ACCURACY OF THE DIFFERENTIAL EMISSION MEASURE DIAGNOSTICS OF SOLAR PLASMAS. APPLICATION TO SDO/AIA. I. ISOTHERMAL PLASMAS

Differential emission measure (DEM) analysis is a major diagnostic tool for stellar atmospheres. However, both its derivation and its interpretation are notably difficult because of random and systematic errors, and the inverse nature of the problem. We use simulations with simple thermal distributions to investigate the inversion properties of SDO/AIA observations of the solar corona. This allows a systematic exploration of the parameter space, and using a statistical approach the respective probabilities of all the DEMs compatible with the uncertainties can be computed. Following this methodology, several important properties of the DEM inversion, including new limitations, can be derived and presented in a very synthetic fashion. In this first paper, we describe the formalism and we focus on isothermal plasmas as building blocks to understand the more complex DEMs studied in the second paper. The behavior of the inversion of AIA data being thus quantified, and we provide new tools to properly interpret the DEM. We quantify the improvement of the isothermal inversion with six AIA bands compared to previous EUV imagers. The maximum temperature resolution of AIA is found to be 0.03 log T{sub e} , and we derive a rigorous test to quantify the compatibility of observations with the isothermal hypothesis. However, we demonstrate limitations in the ability of AIA alone to distinguish different physical conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterizing spatiotemporal information loss in sparse-sampling-based dynamic MRI for monitoring respiration-induced tumor motion in radiotherapy

Purpose: Sparse-sampling and reconstruction techniques represent an attractive strategy to achieve faster image acquisition speeds, while maintaining adequate spatial resolution and signal-to-noise ratio in rapid magnetic resonance imaging (MRI). The authors investigate the use of one such sequence, broad-use linear acquisition speed-up technique (k-t BLAST) in monitoring tumor motion for thoracic and abdominal radiotherapy and examine the potential trade-off between increased sparsification (to increase imaging speed) and the potential loss of “true” information due to greater reliance on a priori information. Methods: Lung tumor motion trajectories in the superior–inferior direction, previously recorded from ten lung cancer patients, were replayed using a motion phantom module driven by an MRI-compatible motion platform. Eppendorf test tubes filled with water which serve as fiducial markers were placed in the phantom. The modeled rigid and deformable motions were collected in a coronal image slice using balanced fast field echo in conjunction with k-t BLAST. Root mean square (RMS) error was used as a metric of spatial accuracy as measured trajectories were compared to input data. The loss of spatial information was characterized for progressively increasing acceleration factor from 1 to 16; the resultant sampling frequency was increased approximately from 2.5 to 19 Hz when the principal direction of the motion was set along frequency encoding direction. In addition to the phantom study, respiration-induced tumor motions were captured from two patients (kidney tumor and lung tumor) at 13 Hz over 49 s to demonstrate the impact of high speed motion monitoring over multiple breathing cycles. For each subject, the authors compared the tumor centroid trajectory as well as the deformable motion during free breathing. Results: In the rigid and deformable phantom studies, the RMS error of target tracking at the acquisition speed of 19 Hz was approximately 0.3–0.4 mm, which was smaller than the reconstructed pixel resolution of 0.67 mm. In the patient study, the dynamic 2D MRI enabled the monitoring of cycle-to-cycle respiratory variability present in the tumor position. It was seen that the range of centroid motion as well as the area covered due to target motion during each individual respiratory cycle was underestimated compared to the entire motion range observed over multiple breathing cycles. Conclusions: The authors’ initial results demonstrate that sparse-sampling- and reconstruction-based dynamic MRI can be used to achieve adequate image acquisition speeds without significant information loss for the task of radiotherapy guidance. Such monitoring can yield spatial and temporal information superior to conventional offline and online motion capture methods used in thoracic and abdominal radiotherapy.

60 APPLIED LIFE SCIENCES↗

Serpentine: Finite Difference Methods for Wave Propagation in Second Order Formulation

Wave propagation phenomena are important in many DOE applications such as nuclear explosion monitoring, geophysical exploration, estimating ground motion hazards and damage due to earthquakes, non-destructive testing, underground facilities detection, and acoustic noise propagation. There are also future applications that would benefit from simulating wave propagation, such as geothermal energy applications and monitoring sites for carbon storage via seismic reflection techniques. In acoustics and seismology, it is of great interest to increase the frequency bandwidth in simulations. In seismic exploration, greater frequency resolution enables shorter wave lengths to be included in the simulations, allowing for better resolution in the seismic imaging. In nuclear explosion monitoring, higher frequency seismic waves are essential for accurate discrimination between explosions and earthquakes. When simulating earthquake induced motion of large structures, such as nuclear power plants or dams, increased frequency resolution is essential for realistic damage predictions. Another example is simulations of micro-seismic activity near geothermal energy plants. Here, hydro-fracturing induces many small earthquakes and the time scale of each event is proportional to the square root of the moment magnitude. As a result, the motion is dominated by higher frequencies for smaller seismic events. The above wave propagation problems are all governed by systems of hyperbolic partial differential equations in second order differential form, i.e., they contain second order partial derivatives of the dependent variables. Our general research theme in this project has been to develop numerical methods that directly discretize the wave equations in second order differential form. The obvious advantage of working with hyperbolic systems in second order differential form, as opposed to rewriting them as first order hyperbolic systems, is that the number of differential equations in the second order system is significantly smaller. Another issue with re-writing a second order system into first order form is that compatibility conditions often must be imposed on the first order form. These (Saint-Venant) conditions ensure that the solution of the first order system also satisfies the original second order system. However, such conditions can be difficult to enforce on the discretized equations, without introducing additional modeling errors. This project has previously developed robust and memory efficient algorithms for wave propagation including effects of curved boundaries, heterogeneous isotropic, and viscoelastic materials. Partially supported by internal funding from Lawrence Livermore National Laboratory, many of these methods have been implemented in the open source software WPP, which is geared towards 3-D seismic wave propagation applications. This code has shown excellent scaling on up to 32,768 processors and has enabled seismic wave calculations with up to 26 Billion grid points. The WPP calculations have resulted in several publications in the field of computational seismology, e.g.. All of our current methods are second order accurate in both space and time. The benefits of higher order accurate schemes for wave propagation have been known for a long time, but have mostly been developed for first order hyperbolic systems. For second order hyperbolic systems, it has not been known how to make finite difference schemes stable with free surface boundary conditions, heterogeneous material properties, and curvilinear coordinates. The importance of higher order accurate methods is not necessarily to make the numerical solution more accurate, but to reduce the computational cost for obtaining a solution within an acceptable error tolerance. This is because the accuracy in the solution can always be improved by reducing the grid size h. However, in practice, the available computational resources might not be large enough to solve the problem with a low order method.

15 GEOTHERMAL ENERGY↗

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13 C Metabolic Flux Analysis ( 13 C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13 C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13 C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13 C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in “non-gaussian” situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13 C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13 C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P- 13 C MOMA and P- 13 C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗

CHANDRA OBSERVATIONS OF FIVE INTEGRAL SOURCES: NEW X-RAY POSITIONS FOR IGR J16393-4643 AND IGR J17091-3624

The Chandra High Resolution Camera observed the fields of five hard X-ray sources in order to help us obtain X-ray coordinates with subarcsecond precision. These observations provide the most accurate X-ray positions known for IGR J16393-4643 and IGR J17091-3624. The obscured X-ray pulsar IGR J16393-4643 lies at R.A. (J2000) = 16{sup h}39{sup m}05.{sup s}47, and decl. = -46 Degree-Sign 42'13.''0 (error radius of 0.''6 at 90% confidence). This position is incompatible with the previously proposed counterpart 2MASS J16390535-4642137, and it points instead to a new counterpart candidate that is possibly blended with the Two Micron All Sky Survey star. The black hole candidate IGR J17091-3624 was observed during its 2011 outburst providing coordinates of R.A. = 17{sup h}09{sup m}07.{sup s}59, and decl. = -36 Degree-Sign 24'25.''4. This position is compatible with those of the proposed optical/IR and radio counterparts, solidifying the source's status as a microquasar. Three targets, IGR J14043-6148, IGR J16358-4726, and IGR J17597-2201, were not detected. We obtained 3{sigma} upper limits of, respectively, 1.7, 1.8, and 1.5 Multiplication-Sign 10{sup -12} erg cm{sup -2} s{sup -1} on their 2-10 keV fluxes.

79 ASTRONOMY AND ASTROPHYSICS↗

ASCEND: Asymptotically compatible strong form foundations for nonlocal discretization

Nonlocal models naturally handle a range of physics of interest to SNL, but discretization of their underlying integral operators poses mathematical challenges to realize the accuracy and robustness commonplace in discretization of local counterparts. This project focuses on the concept of asymptotic compatibility, namely preservation of the limit of the discrete nonlocal model to a corresponding well-understood local solution. We address challenges that have traditionally troubled nonlocal mechanics models primarily related to consistency guarantees and boundary conditions. For simple problems such as diffusion and linear elasticity we have developed complete error analysis theory providing consistency guarantees. We then take these foundational tools to develop new state-of-the-art capabilities for: lithiation-induced failure in batteries, ductile failure of problems driven by contact, blast-on-structure induced failure, brittle/ductile failure of thin structures. We also summarize ongoing efforts using these frameworks in data-driven modeling contexts. This report provides a high-level summary of all publications which followed from these efforts.

97 MATHEMATICS AND COMPUTING↗

Phenomenology of Semileptonic B-Meson Decays with Form Factors from Lattice QCD

We study the exclusive semileptonic B-meson decays B→K(π)ℓ + ℓ - , B→K(π)νν¯, and B→πτν, computing observables in the Standard model using the recent lattice-QCD results for the underlying form factors from the Fermilab Lattice and MILC Collaborations. These processes provide theoretically clean windows into physics beyond the Standard Model because the hadronic uncertainties are now under good control. The resulting partially-integrated branching fractions for B→πμ + μ - and B→Kμ + μ - outside the charmonium resonance region are 1-2σ higher than the LHCb Collaboration's recent measurements, where the theoretical and experimental errors are commensurate. The combined tension is 1.7σ. Combining the Standard-Model rates with LHCb's measurements yields values for the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements |V td |=7.45(69)×10 -3 , |V ts |=35.7(1.5)×10 -3 , and |V td /V ts |=0.201(20), which are compatible with the values obtained from neutral B (s) -meson oscillations and have competitive uncertainties. Alternatively, taking the CKM matrix elements from unitarity, we constrain new-physics contributions at the electroweak scale. Furthermore, the constraints on the Wilson coefficients Re(C 9 ) and Re(C 10 ) from B→πμ + μ - and B→Kμ + μ - are competitive with those from B→K*μ + μ - , and display a 2.0σ tension with the Standard Model. Our predictions for B→K(π)νν¯ and B→πτν are close to the current experimental limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pion valence quark distribution at physical pion mass of N f = 2 + 1 + 1 lattice QCD

Abstract We present a state-of-the-art calculation of the unpolarized pion valence-quark distribution in the framework of large-momentum effective theory (LaMET) with improved handling of systematic errors as well as two-loop perturbative matching. We use lattice ensembles generated by the MILC collaboration at lattice spacinga≈ 0.09 fm, lattice volume 64 3 × 96,N f = 2 + 1 + 1 flavors of highly-improved staggered quarks and a physical pion mass. The LaMET matrix elements are calculated with pions boosted to momentumP z ≈ 1.72 GeV with high-statistics ofO(10 6 ) measurements. We study the pion PDF in both hybrid-ratio and hybrid-regularization-independent momentum subtraction (hybrid-RI/MOM) schemes and also compare the systematic errors with and without the addition of leading-renormalon resummation (LRR) and renormalization-group resummation (RGR) in both the renormalization and lightcone matching. The final lightcone PDF results are presented in the modified minimal-subtraction scheme at renormalization scaleμ= 2.0 GeV. We show that thex-dependent PDFs are compatible between the hybrid-ratio and hybrid-RI/MOM renormalization with the same improvements. We also show that systematics are greatly reduced by the simultaneous inclusion of RGR and LRR and that these methods are necessary if improved precision is to be reached with higher-order terms in renormalization and matching.

Physics↗

STELLAR ARCHAEOLOGY IN THE GALACTIC HALO WITH THE ULTRA-FAINT DWARFS. VI. URSA MAJOR II

We present a B, V color-magnitude diagram (CMD) of the Milky Way dwarf satellite Ursa Major II (UMa II), spanning the magnitude range from V {approx} 15 to V {approx} 23.5 mag and extending over an 18 Multiplication-Sign 18 arcmin{sup 2} area centered on the Galaxy. Our photometry goes down to about 2 mag below the Galaxy's main-sequence turnoff that we detected at V {approx} 21.5 mag. We have discovered a bona fide RR Lyrae variable star in UMa II, which we use to estimate a conservative dereddened distance modulus for the galaxy of (m - M){sub 0} = 17.70 {+-} 0.04 {+-} 0.12 mag, where the first error accounts for the uncertainties of the calibrated photometry, and the second reflects our lack of information on the metallicity of the star. The corresponding distance to UMa II is 34.7{sup +0.6}{sub -0.7}({sup +2.0}{sub -1.9}) kpc. Our photometry shows evidence of a spread in the Galaxy's subgiant branch, compatible with a spread in metal abundance in the range between Z = 0.0001 and Z = 0.001. Based on our estimate of the distance, a comparison of the fiducial lines of the Galactic globular clusters M68 and M5 ([Fe/H] = -2.27 {+-} 0.04 dex and -1.33 {+-} 0.02 dex, respectively), with the position on the CMD of spectroscopically confirmed Galaxy members, may suggest the existence of stellar populations of different metal abundance/age in the central region of UMa II.

79 ASTRONOMY AND ASTROPHYSICS↗

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↗