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At least 1,747 records · Page 97

Wee1 Kinase Inhibitor AZD1775 Radiosensitizes Hepatocellular Carcinoma Regardless of TP53 Mutational Status Through Induction of Replication Stress

Purpose: Wee1 kinase inhibitors are effective radiosensitizers in cells lacking a G{sub 1} checkpoint. In this study we examined the potential effect of Wee1 kinase inhibition on inducing replication stress in hepatocellular carcinoma (HCC). Methods and Materials: Five independent datasets from the Oncomine database comparing gene expression in HCC compared to normal tissue were combined and specific markers associated with Wee1 sensitivity were analyzed. We then performed a series of in vitro experiments to study the effect of Wee1 inhibition on irradiated HCC cell lines with varying p53 mutational status. Clonogenic survival assays and flow cytometry using anti-γH2AX and phospho-histone H3 antibodies with propidium iodide were performed to study the effect of AZD1775 on survival, cell cycle, and DNA repair. Additionally, nucleoside enriched medium was used to examine the effect of altering nucleotide pools on Wee1 targeted radiation sensitization. Results: Our analysis of the Oncomine database found high levels of CDK1 and other cell cycle regulators indicative of Wee1 sensitivity in HCC. In our in vitro experiments, treatment with AZD1775 radiosensitized and chemosensitized Hep3B, Huh7, and HepG2 cell lines and was associated with delayed resolution of γH2AX foci and the induction of pan-nuclear γH2AX staining. Wee1 inhibition attenuated radiation-induced G{sub 2} arrest in the Hep3B (TP53 null) and Huh7 (TP53 mutant) cell lines but not in the TP53 wild-type cell line HepG2. Supplementation with nucleosides reversed the radiation-sensitizing effect of AZD1775 and reduced the amount of cells with pan-nuclear γH2AX staining after radiation. Conclusions: Radiation sensitization with Wee1 inhibition occurs in cells regardless of their p53 mutational status. In this study we show for the first time that replication stress via the overconsumption of nucleotides plays an important role in AZD1775-induced radiation sensitization.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Evaluation of a Machine-Learning Algorithm for Treatment Planning in Prostate Low-Dose-Rate Brachytherapy

Purpose: This work presents the application of a machine learning (ML) algorithm to automatically generate high-quality, prostate low-dose-rate (LDR) brachytherapy treatment plans. The ML algorithm can mimic characteristics of preoperative treatment plans deemed clinically acceptable by brachytherapists. The planning efficiency, dosimetry, and quality (as assessed by experts) of preoperative plans generated with an ML planning approach was retrospectively evaluated in this study. Methods and Materials: Preimplantation and postimplantation treatment plans were extracted from 100 high-quality LDR treatments and stored within a training database. The ML training algorithm matches similar features from a new LDR case to those within the training database to rapidly obtain an initial seed distribution; plans were then further fine-tuned using stochastic optimization. Preimplantation treatment plans generated by the ML algorithm were compared with brachytherapist (BT) treatment plans in terms of planning time (Wilcoxon rank sum, α = 0.05) and dosimetry (1-way analysis of variance, α = 0.05). Qualitative preimplantation plan quality was evaluated by expert LDR radiation oncologists using a Likert scale questionnaire. Results: The average planning time for the ML approach was 0.84 ± 0.57 minutes, compared with 17.88 ± 8.76 minutes for the expert planner (P=.020). Preimplantation plans were dosimetrically equivalent to the BT plans; the average prostate V150% was 4% lower for ML plans (P=.002), although the difference was not clinically significant. Respondents ranked the ML-generated plans as equivalent to expert BT treatment plans in terms of target coverage, normal tissue avoidance, implant confidence, and the need for plan modifications. Respondents had difficulty differentiating between plans generated by a human or those generated by the ML algorithm. Conclusions: Prostate LDR preimplantation treatment plans that have equivalent quality to plans created by brachytherapists can be rapidly generated using ML. The adoption of ML in the brachytherapy workflow is expected to improve LDR treatment plan uniformity while reducing planning time and resources.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Radical Cystectomy Compared to Combined Modality Treatment for Muscle-Invasive Bladder Cancer: A Systematic Review and Meta-Analysis

Purpose: To perform a comprehensive comparison of overall survival (OS), disease-specific survival (DSS), progression-free survival (PFS), and treatment-related complications between radical cystectomy (RC) and combined modality treatment (CMT—radiation therapy, concurrent chemotherapy, and maximal transurethral resection of bladder tumor) in the setting of muscle-invasive bladder cancer. Methods and Materials: We searched 7 databases (PubMed, Scopus, EMBASE, Proquest, CINAHL, and (ClinicalTrials.gov)) for randomized, controlled trials and prospective and retrospective studies directly comparing RC with CMT from database inception to March 2016. We conducted meta-analyses evaluating OS, DSS, and PFS with hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Nineteen studies evaluating 12,380 subjects were selected. For the 8 studies encompassing 9554 subjects eligible for meta-analyses, we found no difference in OS at 5 years (HR 0.96, favoring CMT, 95% CI 0.72-1.29; P=.778) or 10 years (HR 1.02, favoring cystectomy, 95% CI 0.73-1.42; P=.905). No difference was observed in DSS at 5 years (HR 0.83, favoring radiation, 95% CI 0.54-1.28; P=.390) or 10 years (HR 1.17, favoring cystectomy, 95% CI 0.89-1.55; P=.264), or PFS at 10 years (HR 0.85, favoring CMT, 95% CI 0.43-1.67; P=.639). The cystectomy arms had higher rates of early major complications, whereas rates of minor complications were similar between the 2 treatments. Conclusion: Current meta-analysis reveals no differences in OS, DSS, or PFS between RC and CMT. Further randomized, controlled trials are necessary to identify the optimal treatment for specific patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Postmastectomy Radiation Therapy Is Associated With Improved Survival in Node-Positive Male Breast Cancer: A Population Analysis

Purpose: Because of its rarity, there are no randomized trials investigating postmastectomy radiation therapy (PMRT) in male breast cancer. This study retrospectively examines the impact of PMRT in male breast cancer patients in the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database. Methods and Materials: The SEER database 8.3.2 was queried for men ages 20+ with a diagnosis of localized or regional nonmetastatic invasive ductal/lobular carcinoma from 1998 to 2013. Included patients were treated by modified radical mastectomy (MRM), with or without adjuvant external beam radiation. Univariate and multivariate analyses evaluated predictors for PMRT use after MRM. Kaplan-Meier overall survival (OS) curves of the entire cohort and a case-matched cohort were calculated and compared by the log-rank test. Cox regression was used for multivariate survival analyses. Results: A total of 1933 patients were included in the unmatched cohort. There was no difference in 5-year OS between those who received PMRT and those who did not (78% vs 77%, respectively, P=.371); however, in the case-matched analysis, PMRT was associated with improved OS at 5 years (83% vs 54%, P<.001). On subset analysis of the unmatched cohort, PMRT was associated with improved OS in men with 1 to 3 positive nodes (5-year OS 79% vs 72% P=.05) and those with 4+ positive nodes (5-year OS 73% vs 53% P<.001). On multivariate analysis of the unmatched cohort, independent predictors for improved OS were use of PMRT: HR=0.551 (0.412-0.737) and estrogen receptor–positive disease: HR=0.577 (0.339-0.983). Predictors for a survival detriment were higher grade 3/4: HR=1.825 (1.105-3.015), larger tumor T2: HR=1.783 (1.357-2.342), T3/T4: HR=2.683 (1.809-3.978), higher N-stage: N1 HR=1.574 (1.184-2.091), N2/N3: HR=2.328 (1.684-3.218), black race: HR=1.689 (1.222-2.336), and older age 81+: HR=4.164 (1.497-11.582). Conclusions: There may be a survival benefit with the addition of PMRT for male breast cancer with node-positive disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Individualized Selection of Beam Angles and Treatment Isocenter in Tangential Breast Intensity Modulated Radiation Therapy

Purpose and Objective: Propose a novel method for individualized selection of beam angles and treatment isocenter in tangential breast intensity modulated radiation therapy (IMRT). Methods and Materials: For each patient, beam and isocenter selection starts with the fully automatic generation of a large database of IMRT plans (up to 847 in this study); each of these plans belongs to a unique combination of isocenter position, lateral beam angle, and medial beam angle. The imposed hard planning constraint on patient maximum dose may result in plans with unacceptable target dose delivery. Such plans are excluded from further analyses. Owing to differences in beam setup, database plans differ in mean doses to organs at risk (OARs). These mean doses are used to construct 2-dimensional graphs, showing relationships between: (1) contralateral breast dose and ipsilateral lung dose; and (2) contralateral breast dose and heart dose (analyzed only for left-sided). The graphs can be used for selection of the isocenter and beam angles with the optimal, patient-specific tradeoffs between the mean OAR doses. For 30 previously treated patients (15 left-sided and 15 right-sided tumors), graphs were generated considering only the clinically applied isocenter with 121 tangential beam angle pairs. For 20 of the 30 patients, 6 alternative isocenters were also investigated. Results: Computation time for automatic generation of 121 IMRT plans took on average 30 minutes. The generated graphs demonstrated large variations in tradeoffs between conflicting OAR objectives, depending on beam angles and patient anatomy. For patients with isocenter optimization, 847 IMRT plans were considered. Adding isocenter position optimization next to beam angle optimization had a small impact on the final plan quality. Conclusion: A method is proposed for individualized selection of beam angles in tangential breast IMRT. This may be especially important for patients with cardiac risk factors or an enhanced risk for the development of contralateral breast cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Multicenter Evaluation of Biochemical Relapse–Free Survival Outcomes for Intraoperatively Planned Prostate Brachytherapy Using an Automated Delivery System

Purpose: To report biochemical recurrence in prostate cancer treated with intraoperatively planned low-dose-rate prostate brachytherapy using an automated delivery system (IO-LDRB). Methods and Materials: Between 2003 and 2013, 2608 patients from 3 centers were treated with IO-LDRB as single-modality treatment for low or low-tier intermediate-risk prostate cancer. Databases from the 3 centers have been analyzed. These independent databases were collected prospectively. Patient, tumor, and treatment characteristics were then compared, Kaplan-Meier survival estimates of biochemical relapse–free survival (bRFS) were generated, and the Cox proportional hazards model was used to determine factors predicting for relapse. Results: A total of 2608 patients with a median follow-up of 4.7 (interquartile range, 3.1-6.9) years were analyzed. Median age was 64 (range, 42-84) years. In these patients, median initial prostate-specific antigen was 5.5 ng/mL, 74% were T1, and 26% were T2; 73% were Gleason 6, and 25% Gleason 7. Median percentage of biopsy cores positive was 33%, and median gland volume was 34.2 cm{sup 3}. Eleven percent of patients received hormones for a median of 3.0 months before implantation. Median seed activity was 0.437 mCi, D90 (dose covering 90% of the prostate volume) was 186.7 Gy, and V100 was 99.37%. Biochemical relapse was observed in 124 patients (4.8%), and median time to failure was 4.0 years. Predicted bRFS was 93% at 7 years. On Cox regression bRFS was dependent only on D90 at the time of implantation and prostate-specific antigen density. Conclusions: This study demonstrates that IO-LDRB is an effective treatment option for patients with low and low-tier intermediate-risk prostate cancer. Rates of biochemical relapse remain low several years after treatment. These results compared favorably to published manual preplan technique results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Normal Tissue Injury Induced by Photon and Proton Therapies: Gaps and Opportunities

Despite technological advances in radiation therapy (RT) and cancer treatment, patients still experience adverse effects. Proton therapy (PT) has emerged as a valuable RT modality that can improve treatment outcomes. Normal tissue injury is an important determinant of the outcome; therefore, for this review, we analyzed 2 databases: (1) clinical trials registered with ClinicalTrials.gov and (2) the literature on PT in PubMed, which shows a steady increase in the number of publications. Most studies in PT registered with ClinicalTrials.gov with results available are nonrandomized early phase studies with a relatively small number of patients enrolled. From the larger database of nonrandomized trials, we listed adverse events in specific organs/sites among patients with cancer who are treated with photons and protons to identify critical issues. The present data demonstrate dosimetric advantages of PT with favorable toxicity profiles and form the basis for comparative randomized prospective trials. A comparative analysis of 3 recently completed randomized trials for normal tissue toxicities suggests that for early stage non-small cell lung cancer, no meaningful comparison could be made between stereotactic body RT and stereotactic body PT due to low accrual (NCT01511081). In addition, for locally advanced non-small cell lung cancer, a comparison of intensity modulated RT with passive scattering PT (now largely replaced by spot-scanned intensity modulated PT), PT did not provide any benefit in normal tissue toxicity or locoregional failure over photon therapy. Finally, for locally advanced esophageal cancer, proton beam therapy provided a lower total toxicity burden but did not improve progression-free survival and quality of life (NCT01512589). The purpose of this review is to inform the limitations of current trials looking at protons and photons, considering that advances in technology, physics, and biology are a continuum, and to advocate for future trials geared toward accurate precision RT that need to be viewed as an iterative process in a defined path toward delivering optimal radiation treatment. A foundational understanding of the radiobiologic differences between protons and photons in tumor and normal tissue responses is fundamental to, and necessary for, determining the suitability of a given type of biologically optimized RT to a patient or cohort.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

59 BASIC BIOLOGICAL SCIENCES↗

MjCyc: Rediscovering the pathway-genome landscape of the first sequenced archaeon, Methanocaldococcus (Methanococcus) jannaschii

The genome of Methanocaldococcus (Methanococcus) jannaschii DSM 2661 was the first Archaeal genome to be sequenced in 1996. Subsequent sequence-based annotation cycles led to its first metabolic reconstruction in 2005. Leveraging new experimental results and function assignments, we have now re-annotated M. jannaschii, creating an updated resource with novel information and testable predictions in a pathway-genome database available at BioCyc.org. This reannotation effort has resulted in 652 function assignments with enzyme roles, accounting for a third of the total protein-coding entries for this genome. The updated resource includes 883 reactions, 540 enzymes, and 142 individual pathways. Despite notable progress in computational genomics, more than a third of the genome remains functionally uncharacterized. The publicly available MjCyc pathway-genome database holds great potential for the wider community to conduct research on the biology of methanogenic Archaea.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrogen losses in fueling station operation

This paper describes an engineering approach for hydrogen accounting from production to dispensing at Cal State Los Angeles Hydrogen Research and Fueling Facility, equipped with an electrolyzer for on-site production. Particularly, the accounting process has been carried out by taking an in-depth look at current practices and databases, and its analysis has been based on data from quarterly reports of hydrogen production and dispensing related parameters and from its data acquisition system. It is described how the station addressed this analysis investigating several station areas. Following there is an assessment of the possible critical points, flanked by considerations, calculations, mathematical modeling and analysis of the database. The analysis led to a marked improvement on the station operation know-how. For most of the analyzed months the current average percentage of losses was found to be between 2 and 10%, whereas before it was between 30 and 35%. This current range of percentage (2–10)% includes all experiments done, defueling the buffer tanks, rebooting the dispenser, venting the lines, the uncertainty of the mass flow meter inside the dispenser (±5%) and the inherent uncertainty of Faraday’s law for hydrogen production estimate. Among all areas analyzed, maintenance activities revealed themselves as the most critical ones, leading to data mismatching in hydrogen accounting. The paper aims also to provide a guideline with recommended practices based on our experience, deduced for station operators and builders, including several steps for leakage monitoring, prevention, and troubleshooting.

08 HYDROGEN↗

Gradient-based optimization for regression in the functional tensor-train format

Predictive analysis of complex computational models, such as uncertainty quantification (UQ), must often rely on using an existing database of simulation runs. In this paper we consider the task of performing low-multilinear-rank regression on such a database. Specifically we develop and analyze an efficient gradient computation that enables gradient-based optimization procedures, including stochastic gradient descent and quasi-Newton methods, for learning the parameters of a functional tensor-train (FT). We compare our algorithms with 22 other nonparametric and parametric regression methods on 10 real-world data sets and show that for many physical systems, exploiting low-rank structure facilitates efficient construction of surrogate models. Here, we use a number of synthetic functions to build insight into behavior of our algorithms, including the rank adaptation and group-sparsity regularization procedures that we developed to reduce overfitting. Finally we conclude the paper by building a surrogate of a physical model of a propulsion plant on a naval vessel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Entropy-based closure for probabilistic learning on manifolds

In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically consistent with an existing dataset construed as a realization from a non-Gaussian random vector. The manifold structure is learned using diffusion manifolds and the statistical sample generation is accomplished using a projected Itˆo stochastic differential equation. This probabilistic learning approach has been extended to polynomial chaos representation of databases on manifolds and to probabilistic nonconvex constrained optimization with a fixed budget of function evaluations. The methodology introduces an isotropic-diffusion kernel with hyperparameter ". Currently, " is more or less arbitrarily chosen. In this paper, we propose a selection criterion for identifying an optimal value of ", based on a maximum entropy argument. The result is a comprehensive, closed, probabilistic model for characterizing data sets with hidden constraints. This entropy argument ensures that out of all possible models, this is the one that is the most uncertain beyond any specified constraints, which is selected. Applications are presented for several databases.

97 MATHEMATICS AND COMPUTING↗

Boron and lithium aqueous thermochemistry to model crud deposition in pressurized water reactors

Here, a comprehensive database of boron and lithium aqueous thermochemistry has been developed for use at elevated temperatures. The Helgeson-Kirkham-Flowers (HKF) formalism provides a framework to describe thermodynamic properties over a broad range of temperatures and pressures. Accuracy at high temperatures is vital to modeling nickel oxide and ferrite fuel deposits that occur in pressurized water nuclear reactors (PWRs). CALPHAD (CALculation of PHAse Diagrams) calculations are performed at PWR crud conditions to predict the stability regions of the solid lithium metaborate (LiBO 2 ) and lithium tetraborate (Li 2 B 4 O 7 ) precipitates. In addition, similar calculations are performed using sodium and potassium instead of lithium in order to assess the thermodynamics associated with preventing the formation of such precipitates. This database contributes to understanding of crud formation and composition and will aid in the prediction of phenomena such as Crud-Induced Power Shifts (CIPS).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A hydrogeophysical framework to assess infiltration during a simulated ecosystem-scale flooding experiment

This study presents a framework to quantify changes in soil saturation in response to flooding caused by extreme hydrologic perturbation on coastal ecosystems at the interfaces and transition between terrestrial and aquatic systems. Subsurface heterogeneity limits the use of in situ measurements to quantify subsurface flow during flooding due to the spatial discontinuity in the measured data. While geophysical methods, including time-lapse electrical resistivity imaging (ERI), are increasingly used to monitor soil hydrological processes, their abilities to parameterize flow models have been underutilized. This study combines background ERI, ground penetrating radar (GPR), time-lapse ERI, soil characterization, and a numerical flow model developed using an Advanced Terrestrial Simulator (ATS) code to quantify the infiltration pathway and describe the hydrological dynamics during a simulated flooding experiment. We assessed the use of two conceptual models developed using [1] ERI and GPR data that described the stratigraphic distribution, and time-lapse ERI that mapped permeability contrast, and [2] information from a national soil database for capturing changes in saturation. Combining the ERI and GPR results with soil core data revealed the stratigraphic heterogeneity at the site with a silty clay layer from 1 to 2 m between an overlying loamy topsoil and an underlying saturated silty sand. This silty clay layer could restrict deep infiltration. The time-lapse ERI showed up to a 35% decrease in resistivity, which correlated with soil moisture data (R 2 value > 0.53) and revealed preferential infiltration zones used to inform the flow model. Numerical simulation results from both the geophysics- and soil database-informed models quantified changes in soil saturation with calculated soil moistures that agreed with field data. The geophysics-informed model captured more of the system’s variability, reflective of shallow subsurface heterogeneities. The framework presented will serve as a precursor for a robust ecohydrological model that can describe the impacts of extreme events induced by climate change on coastal ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Low-temperature proton irradiation damage of isotropic nuclear grade IG-430 graphite

IG-430, a fine-grained, isotropic graphite grade is a promising candidate for the future Very High Temperature Reactors (VHTR). IG-430 which provides higher density, strength, and thermal conductivity, has already been developed as a graphite for next-generation HTGR, and is expected to be employed. This graphite grade, however, is lacking enough database that is needed for design. The present study aims to enhance the database with experimental data focusing on the low temperature regime (90–210 °C) by using 120–200 MeV protons to irradiate the IG-430 graphite to peak fluence of ~1.2 10 25 m –2 . It is anticipated that radiation-induced changes in the graphite properties and damage to be more pronounced in this low temperature regime than in elevated temperatures where damage annealing is taking place simultaneously. IG-430 graphite was characterized following irradiation for mechanical property changes (modulus and strength), dimensional stability and irradiation-induced growth as well as microstructural changes using high energy X-rays and different X-ray diffraction techniques. In assessing proton irradiation effects on the IG-430 graphite grade, comparison of radiation effects was made with the IG-43 grade, the un-purified version of IG-430, as well as other isotropic graphite grades. IG-430 was shown in this study to be better graphitized than other isotropic graphite grades. The study also revealed that during proton irradiation at low temperatures (~100 °C) the IG-430 exhibits stored energy release.

36 MATERIALS SCIENCE↗

Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems

Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗

Multispectrum analysis of the oxygen A-band

Retrievals of atmospheric composition from near-infrared measurements require measurements of airmass to better than the desired precision of the composition. The oxygen bands are obvious choices to quantify airmass since the mixing ratio of oxygen is fixed over the full range of atmospheric conditions. The OCO-2 mission is currently retrieving carbon dioxide concentration using the oxygen A-band for airmass normalization. The 0.25% accuracy desired for the carbon dioxide concentration has pushed the required state-of-the-art for oxygen spectroscopy. To measure O2 A-band cross-sections with such accuracy through the full range of atmospheric pressure requires a sophisticated line-shape model (Rautian or Speed-Dependent Voigt) with line mixing (LM) and collision induced absorption (CIA). Models of each of these phenomena exist, however, this work presents an integrated self-consistent model developed to ensure the best accuracy. It is also important to consider multiple sources of spectroscopic data for such a study in order to improve the dynamic range of the model and to minimize effects of instrumentation and associated systematic errors. The techniques of Fourier Transform Spectroscopy (FTS) and Cavity Ring-Down Spectroscopy (CRDS) allow complimentary information for such an analysis. We utilize multispectrum fitting software to generate a comprehensive new database with improved accuracy based on these datasets. As a result, the extensive information will be made available as a multi-dimensional cross-section (ABSCO) table and the parameterization will be offered for inclusion in the HITRANonline database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗