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At least 397 records · Page 22

Downwelling Far-Infrared Emission Spectra Measured by FIRST at Cerro Toco, Chile and Table Mountain Facility, CA

The Far-Infrared Spectroscopy of the Troposphere (FIRST) instrument is a fourier transform spectrometer developed to measure the far-infrared portion of the Earth's longwave spectrum. Specifically, the purpose is measurement of the important, yet under-investigated 100 to 1000 cm-1 band. Presented here are measurements made by FIRST at two successful deployments in a ground-based configuration to measure downwelling longwave radiation. The initial deployment was to Cerro Toco, Chile. FIRST operated from August to October, 2009 as part of the Radiative Heating in Underexplored Bands Campaign (RHUBC-II) campaign. After recalibration, FIRST was deployed to the Table Mountain Facility from August to October, 2012. Dry days for both campaigns were chosen for analysis ? 09/24/2009 and 10/19/2012. Also available from both deployments are coincident radiosonde temperature and water vapor vertical profiles used as inputs to radiance calculations performed by two platforms, the AER Line-by-Line Radiative Transform Model (using the AER line database), and a research platform, MRTA utilizing HITRAN 2012. Thus, we have three streams of data for the closure studies, and results of the comparisons are presented showing good agreement in the optically thick regions of 200-400 cm-1 and 600-800 cm-1. Differences between measured and coincident calculated spectra between 400 and 600 cm-1 are less than 10 mW/m^2/sr/cm-1. Uncertainties accounted for in this study include uncertainty from multiple detectors, water vapor, temperature, line strength and width as presented in HITRAN 2012, and due to internal heating caused by black bodies. The residuals fall within the root-sum-square envelope of the uncertainties.

J Mast↗

Rework Recipe Development, Analysis and Results of Select 9-Cell Cavities for LCLS-II

The SLAC National Accelerator Laboratory is currently constructing a major upgrade to its accelerator, the Linac Coherent Light Source II (LCLS-II). Several Department of Energy laboratories, including the Thomas Jefferson National Accelerator Facility (JLab) and Fermi National Accelerator Laboratory (FNAL), are collaborating in this project. The cryomodules for this project each consist of eight 1.3-GHz cavities produced by two vendors, Research Instruments GmbH in Germany (RI*) and Ettore Zanon S.p.a. in Italy (EZ*), using niobium cell material from Tokyo Denkai Co., Ltd. (TD) and Ningxia Orient Tantalum Industry Co., Ltd. (OTIC/NX)). During the initial production run, cavity performance from one of the vendors (Vendor A) was far below expectation. All the cavities had low Q0, later attributed to minimal EP as well as high-flux-trapping NX material, early quench behaviour below 18 MV/m, with many having Q0 roll-off at 12-16 MV/m. Production was stopped multiple times over the following 6 months, with test batches of cavities being made to ascertain the root cause of the problem. The final root cause of the problem was found to be inappropriate grinding of the RF surface prior to welding which left normal conducting inclusions in the surface. In addition, most cavities showed internal and external weld spatter which required post weld grinding and a very rough surface from operating the electropolishing machine in an etching rather than polishing regime. All issues have been corrected on new cavities and rework is underway on the originally effected cavities.

Macha, Kurt M.↗

Detection of sub-500-μm cracks in multicrystalline silicon wafer using edge-illuminated dark-field imaging to enable thin solar cell manufacturing

High capital expenditures associated with manufacturing thin silicon wafers make it difficult for the industry to scale up and prevent novel technologies from entering the market. Thin wafers fail largely due to breakage during solar cell processing and handling. One of the root causes for breakage is sub-mm edge cracks in the silicon wafer, and these cracks cannot be reliably detected by most commercially-available crack detection tools. In this work, we first investigate the correlation between wafer thickness and critical crack length, and explain the importance of detecting sub-500-μm edge cracks as the wafer thickness is reduced. Secondly, we extend our previous work of micro-crack detection to demonstrate an edge illumination technique using a near-infrared laser to image edge cracks less than 500 μm in length in multicrystalline silicon. Thirdly, we investigate two fundamental edge illumination mechanisms based on dark-field imaging; namely, direct and vicinal illumination. We will then compare these methods to a state-of-the-art rear illumination method. The advantages and disadvantages of both illumination methods are presented and provide an in-depth analysis of light-crack interaction. In particular, we find that the robustness of vicinal illumination is due to diffuse reflectance. The diffuse reflectance has less dependence on crack configurations, while direct illumination has more dependence on the crack configurations because it utilizes specular reflectance. Our results show that our proposed prototype can detect sub-mm edge cracks in multicrystalline silicon wafers, which is an important step in enabling thin silicon wafer manufacturing.

14 SOLAR ENERGY↗

Analysis of F/A-18 Tail Buffet Data Acquired in the 80- by 120-Foot Wind Tunnel

Tail buffet studies were conducted on a full-scale, production, F/A-18 fighter aircraft in the 80- by 120-Foot Wind Tunnel of the National Full-Scale Aerodynamic Complex at NASA Ames Research Center at Moffett Field, California. Tail buffet data were acquired over an angle-of-attack range of +20 deg to +40 deg, a side-slip range of -16 deg to + 16 deg, and at wind speeds up to 100 knots. The maximum speed corresponds to a Reynolds number of l2.3 x l0(exp 6) based on mean aerodynamic chord and a Mach number of 0. 15. The port, vertical tail fin was instrumented with ninety-six surface-pressure transducers, arranged in six by eight arrays, on each side of the fin. ne aircraft was also equipped with a removable Leading-Edge Extension (LEX) fence whose purpose is to reduce tail-buffet loads. Current analysis methods for the unsteady aerodynamic pressures and loads are described. Only results for the zero side-slip condition are to be presented, both with and without the LEX fence. Results of the time-averaged, power-spectral analysis are presented for the tail fin bending moments which are derived from the integrated pressure field. Local wave velocities on the tail surfaces are calculated from pressure correlations. It was found that the LEX fence significantly reduces the magnitude of the root-mean-square pressures and bending moments. Scaling and repeatability issues are addressed by comparing the present full scale results for pressures at the 60%-span and 45%-chord location with previous full-scale F/A-18 tail-buffet test in the 80- by 120- Foot Wind Tunnel, and with several small-scale tests. The comparisons show that the tail buffet frequency scales very well with tail chord and free-stream velocity, and that there is good agreement with the previous full-scale test. Root-mean-square pressures and power spectra do not scale as well as the frequency results. Addition of a LEX fence caused tail-buffet loads to be reduced at all model scales.

James, Kevin D.↗

Quantitative Electroluminescence Imaging Analysis for Performance Estimation of PID-Influenced PV Modules

An empirical method for estimating relative power losses caused by potential-induced degradation (PID) for p-type solar cells and modules using quantitative electroluminescence (EL) analysis (QELA) is presented. First, EL images are corrected for camera- and perspective distortion. The relative power loss map is then calculated from the logarithmic ratio of two EL images, taken either before and after PID degradation or at different applied currents. Only the cell average of the resulting power loss map is evaluated. The highest power loss across each string is averaged to obtain the overall power loss. Consequently, for modules with three strings, three cells are averaged. The resulting power loss depends on the current applied. The conversion to equivalent irradiance allows for comparison of measured and estimated device performance. The analysis of roughly 2000 EL images and related current-voltage (I-V) curves indicates a good agreement between flash-test-measured and performance estimated using QELA. A relative root mean square error of 1-3% can be achieved.

14 SOLAR ENERGY↗

A Change Impact Analysis to Characterize Evolving Program Behaviors

Change impact analysis techniques estimate the potential effects of changes made to software. Directed Incremental Symbolic Execution (DiSE) is an intraprocedural technique for characterizing the impact of software changes on program behaviors. DiSE first estimates the impact of the changes on the source code using program slicing techniques, and then uses the impact sets to guide symbolic execution to generate path conditions that characterize impacted program behaviors. DiSE, however, cannot reason about the flow of impact between methods and will fail to generate path conditions for certain impacted program behaviors. In this work, we present iDiSE, an extension to DiSE that performs an interprocedural analysis. iDiSE combines static and dynamic calling context information to efficiently generate impacted program behaviors across calling contexts. Information about impacted program behaviors is useful for testing, verification, and debugging of evolving programs. We present a case-study of our implementation of the iDiSE algorithm to demonstrate its efficiency at computing impacted program behaviors. Traditional notions of coverage are insufficient for characterizing the testing efforts used to validate evolving program behaviors because they do not take into account the impact of changes to the code. In this work we present novel definitions of impacted coverage metrics that are useful for evaluating the testing effort required to test evolving programs. We then describe how the notions of impacted coverage can be used to configure techniques such as DiSE and iDiSE in order to support regression testing related tasks. We also discuss how DiSE and iDiSE can be configured for debugging finding the root cause of errors introduced by changes made to the code. In our empirical evaluation we demonstrate that the configurations of DiSE and iDiSE can be used to support various software maintenance tasks

Rungta, Neha Shyam↗

Causal relationships of vegetation productivity with root zone water availability and atmospheric dryness at the catchment scale

Abstract. This study explores the causal relationships between catchment water availability, vapor pressure deficit, and gross primary productivity (GPP) across 341 catchments in the contiguous US. Seasonal climatic, hydrological, and vegetation characteristics were represented using the Horton index, ecological aridity index, evaporative fraction index, and carbon uptake efficiency. Statistical methods, including circularity statistics, correlation analysis, and causality tests, were employed to determine the complex interactions between catchment wetness, atmospheric dryness, and vegetation carbon uptake. The results revealed a maximum lag of 2 months in the intra-annual variability of catchment water supply–productivity and atmospheric water demand–productivity relationships, with hysteresis patterns varying with the catchment's hydrological characteristics. In catchments not permanently under water-limited or energy-limited conditions, vegetation experiences hydrological stress during the peak growing period, coinciding with the highest gross primary productivity and carbon uptake efficiency being out of phase with the Horton index and in phase with the evaporative fraction index. Causality analysis highlights strong temporal continuity in GPP seasonal characteristics, with a cause–effect relationship between catchment water supply, atmospheric demand, and vegetation productivity spanning a maximum of 2 months. These findings underscore the need for a comprehensive functional framework that integrates catchment water supply, atmospheric demand, and vegetation productivity to enhance our understanding and predictive capabilities with regard to ecosystem responses to climate change.

54 ENVIRONMENTAL SCIENCES↗

Excess nutrients in hydroponic solutions alter nutrient content of rice, wheat, and potato

Environment has significant effects on the nutrient content of field-grown crop plants. Little is known, however, about compositional changes caused by controlled environments in which plants receive only artificial radiation and soilless, hydroponic culture. This knowledge is essential for developing a safe, nutritious diet in a Controlled Ecological Life-Support System (CELSS). Three crops that are candidates for inclusion in a CELSS (rice, wheat, and white potato) were grown both in the field and in controlled environments where the hydroponic nutrient solution, photosynthetic photon flux (PPF), and CO2 level were manipulated to achieve rapid growth rates. Plants were harvested at maturity, separated into discrete parts, and dried prior to analysis. Plant materials were analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate, minerals, and amino-acid composition. The effect of environment on nutrient content varied by crop and plant part. Total N and nonprotein N (NPN) contents of plant biomass generally increased under controlled-environment conditions compared to field conditions, especially for leafy plant parts and roots. Nitrate levels were increased in hydroponically-grown vegetative tissues, but nitrate was excluded from grains and tubers. Mineral content changes in plant tissue included increased phosphorus and decreased levels of certain micronutrient elements under controlled-environment conditions. These findings suggest that cultivar selection, genetic manipulation, and environmental control could be important to obtain highly nutritious biomass in a CELSS.

NASA Discipline Number 61-20↗

The Role of NASA Engineering & Safety Center (NESC) in Advancing NASA's Earth Science Missions (Past, Present, and Future)

The NASA Engineering & Safety Center (NESC) was established in 2003 to provide an independent technical resource for the resolution of challenging technical problems (through the use of studies, analysis, tests, etc.). Since its inception, NESC has completed nearly 1000 technical assessments for NASA’s Human Exploration and Operation Mission Directorate (HEOMD), Science Mission Directorate (SMD), Space Technology Mission Directorate (STMD), and Aeronautics Research Mission Directorate (ARMD). Of the SMD related assessments, several were for the resolution of technical problems, analysis, or studies related to NASA’s Earth science missions in various phases of the project from design to operation. Some of the recent examples of NESC technical support for NASA (or NOAA) Earth science missions have been for: Soil Moisture Active Passive (SMAP), Deep Space Climate Observatory (DSCOVR), Cyclone Global Navigation Satellite System (CYGNSS), Ice, Cloud, and Land Elevation Satellite (ICESat-II), Joint Polar Satellite System (JPSS), and the soon to be launched collaboration mission with India, NASA-ISRO Synthetic Aperture Radar (NISAR). In this paper, we outline some of the technical challenges faced by these Earth science missions and describe how NESC contributed to their resolution. The case studies cover a wide range of disciplines involving space lidars, radars, electronics, attitude control systems, as well as Micrometeoroid Orbital Debris (MMOD) risk assessment impact to NASA missions. The efforts include strategies for risk mitigation, technical resolution of challenging problems, and failure root cause investigations combined with lessons learned reports to advance discipline knowledge, enhance NASA capabilities, and avoid future problems.

NASA↗

Comparing the Electrical Modeling and Thermal Analysis Toolbox Simulation Data to Electrified Aircraft Propulsion Test Hardware Data

A model using the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), a National Aeronautics and Space Administration (NASA)-developed Simulink® model block library of electrical components, was developed to mirror the Hybrid Propulsion Emulation Rig (HyPER) hardware, a laboratory focused on Electrified Aircraft Propulsion (EAP) hardware tests. The goal of the model was to demonstrate the utility of the library by comparing the accuracy of the library models to the performance of real hardware, with the primary metrics being the simulation outputs matching physical test hardware data within 5% of full scale.The objective of this paper is to present the background, setup, testing and results of this comparison. It describes some of the adjustments that were necessary to match the system hardware, as well as next steps in verification and validation. The outputs of the model were compared to the results of several tests in HyPER, and in the process captured an additional torque loss that is still being analyzed for the root cause but has been confirmed in the hardware. Across all the test series, only one key model parameter was outside the target 5% full scale matching, and nearly 70% were within 1%.

Mark E Bell↗

Validation of density pump-out by pedestal-foot magnetic island formation prior to ELM suppression in KSTAR and DIII-D tokamaks

Abstract TM1 nonlinear two-fluid simulations reveal key characteristics of density pump-out caused by pedestal-foot island formation when applying resonant magnetic perturbation (RMP). These characteristics include a bifurcation in pump-out with a low RMP coil current threshold, a sensitivity of pump-out magnitude to q 95 , and the magnitude of pump-out scaling as the square root of the RMP coil current. Dedicated experiments are carried out in the KSTAR and DIII-D tokamaks to validate these features and show that: (1) a staircase bifurcation in density pump-out is observed when slowly ramping up the n = 1 RMP current, and the density fluctuations are found to be slightly decreased from the pedestal-foot to the pedestal-top; (2) the magnitude of density pump-out becomes weaker when decreasing q 95 from 5.5 to 4.9, and a partial recovery of density pump-out is observed when q 95 is ramped down to lower than 4.9; and (3) analysis of a DIII-D database of n = 3 RMP edge-localized mode control experiments finds that the magnitude of density pump-out is proportional to the square root of RMP coil current Δ n e / n e ∝ I RMP 0.5 . These experimental observations are consistent with TM1 simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparing the Electrical Modeling and Thermal Analysis Toolbox Simulation Data to Electrified Aircraft Propulsion Test Hardware Data

A model using the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), a National Aeronautics and Space Administration (NASA)-developed Simulink® model block library of electrical components, was developed to mirror the Hybrid Propulsion Emulation Rig (HyPER) hardware, a laboratory focused on Electrified Aircraft Propulsion (EAP) hardware tests. The goal of the model was to demonstrate the utility of the library by comparing the accuracy of the library models to the performance of real hardware, with the primary metrics being the simulation outputs matching physical test hardware data within 5 percent of full scale. The objective of this paper is to present the background, setup, testing and results of this comparison. It describes some of the adjustments that were necessary to match the system hardware, as well as next steps in verification and validation. The outputs of the model were compared to the results of several tests in HyPER, and in the process captured an additional torque loss that is still being analyzed for the root cause but has been confirmed in the hardware. Across all the test series, only one key model parameter was outside the target 5 percent full scale matching, and nearly 70 percent were within 1 percent.

Mark E. Bell↗

Validation and Application of Satellite-Derived Sea Surface Temperature Gradients in the Bering Strait and Bering Sea

The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.

Arctic↗

New developments in calorimetric particle detection

In nuclear, particle and astroparticle physics experiments, calorimeters are used to measure the properties of particles with kinetic energies that range from a fraction of 1 eV to 10 20 eV or more. These properties are not necessarily limited to the energy carried by these particles, but may concern the entire four-vector, including the particle mass and type. In many modern experiments, large calorimeter systems play a central role, and this is expected to be no different for experiments that are currently being planned/designed for future accelerators. In this paper, the state of the art as well as new developments in calorimetry are reviewed. The latter are of course inspired by the perceived demands of future experiments, and/or the increasing demands of the current generation of experiments, as these are confronted with, for example, increased luminosity. These demands depend on the particles to be detected by the calorimeter. In electromagnetic calorimeters, radiation hardness of the detector components is a major concern. The generally poor performance of the current generation of hadron calorimeters is considered inadequate for future experiments, and a lot of the R&D in the past decade has focused on improving this performance. The root causes of the problems are investigated and different methods that have been exploited to remedy this situation are evaluated. Over the past two decades, experiments in astroparticle physics have started to make major contributions to our fundamental understanding of physics and of a variety of processes that are inaccessible in laboratory experiments here on Earth. These experiments typically make use of calorimetric particle detection. At the extreme low end of the energy spectrum, ingenious instruments are used to study phenomena involving energy transfers of the order of 1 eV using calorimetric methods. In separate sections, some salient aspects of this work are reviewed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of CMIP6 models in simulating the statistics of extreme precipitation over Eastern Africa

We report the Eastern Africa region experiences frequent extreme precipitation events that can cause destruction of property and environment, and loss of lives. Thus, there is a need to understand how these events may change in the future and how well the global climate models that are used to make projections can simulate precipitation extremes in this region before they can be used in downscaling or flood and drought impact assessment studies. In this work, we evaluated the ability of sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models to simulate present-day precipitation extremes over the Eastern Africa region during the two rainy seasons (March–May and September–November). We used nine extreme precipitation indices (including seven (one) indices of wet (dry) extremes) defined by the Expert Team on Climate Change Detection and Indices. The CMIP6 models were evaluated against two gridded observation datasets: Global Precipitation Climatology Project One-Degree Daily Dataset and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis 3B42. Three model performance metrics (percentage bias, normalized root-mean-square error, and pattern correlation coefficient) were employed to further assess the strengths and weakness of the models. Our results show that the multi-model ensemble mean generally provides a better representation of observed precipitation and related extremes compared to individual models when considering all metrics and seasons. Several consistent biases are evident across CMIP6 models, which tend to overestimate the total-wet day precipitation and consecutive wet days, and underestimate very wet days and maximum 5-day precipitation in both seasons. Furthermore, no single model consistently performs best, model performance varies with the season and index under consideration and is generally independent of horizontal resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Component-Level Electronic-Assembly Repair (CLEAR) Analysis of the Problem Reporting and Corrective Action (PRACA) Database of the International Space Station On-Orbit Electrical Systems

The NASA Constellation Program is investigating and developing technologies to support human exploration of the Moon and Mars. The Component-Level Electronic-Assembly Repair (CLEAR) task is part of the Supportability Project managed by the Exploration Technology Development Program. CLEAR is aimed at enabling a flight crew to diagnose and repair electronic circuits in space yet minimize logistics spares, equipment, and crew time and training. For insight into actual space repair needs, in early 2008 the project examined the operational experience of the International Space Station (ISS) program. CLEAR examined the ISS on-orbit Problem Reporting and Corrective Action database for electrical and electronic system problems. The ISS has higher than predicted reliability yet, as expected, it has persistent problems. A goal was to identify which on-orbit electrical problems could be resolved by a component-level replacement. A further goal was to identify problems that could benefit from the additional diagnostic and test capability that a component-level repair capability could provide. The study indicated that many problems stem from a small set of root causes that also represent distinct component problems. The study also determined that there are certain recurring problems where the current telemetry instrumentation and built-in tests are unable to completely resolve the problem. As a result, the root cause is listed as unknown. Overall, roughly 42 percent of on-orbit electrical problems on ISS could be addressed with a component-level repair. Furthermore, 63 percent of on-orbit electrical problems on ISS could benefit from additional external diagnostic and test capability. These results indicate that in situ component-level repair in combination with diagnostic and test capability can be expected to increase system availability and reduce logistics. The CLEAR approach can increase the flight crew s ability to act decisively to resolve problems while reducing dependency on Earth-supplied logistics for future Constellation Program missions.

Oeftering, Richard C.↗

Gearbox Reliability Collaborative Phase 3 Gearbox 3 Test Report

Many gearboxes in wind turbines do not achieve their expected design life; they do, however, commonly meet or exceed the design criteria specified in current standards in the gear, bearing, and wind turbine industry as well as third-party certification criteria. The cost of gearbox replacements and rebuilds, as well as the downtime associated with these failures, increases the cost of wind energy. In 2007, the U.S. Department of Energy established the National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC). Its goals are to understand the root causes of premature gearbox failures and to improve their reliability. The GRC is examining a hypothesis that the gap between design-estimated and actual wind turbine gearbox reliability is caused by underestimation of loads, inaccurate design tools, the absence of critical elements in the design process, or insufficient testing. This report describes the recently completed tests of GRC Gearbox 3 in the National Wind Technology Center dynamometer and documents any modifications to the original test plan. In this manner, it serves as a guide for interpreting the publicly released data sets with brief analyses to illustrate the data. The primary test objective was to measure the planetary load-sharing characteristics in the same conditions as the original GRC gearbox design. If the measured load-sharing characteristics are close to the design model, the projected improvement in planetary section fatigue life and the efficacy of preloaded TRBs in mitigating the planetary bearing fatigue failure mode will have been demonstrated. Detailed analysis of that test objective will be presented in subsequent publications.

17 WIND ENERGY↗

Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks

X-ray diffraction (XRD) data acquisition and analysis is among the most time-consuming steps in the development cycle of novel thin-film materials. We propose a machine-learning-enabled approach to predict crystallographic dimensionality and space group from a limited number of thin-film XRD patterns. We overcome the scarce-data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model-agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data. As a test case, 115 thin-film metal-halides spanning 3 dimensionalities and 7 space-groups are synthesized and classified. After testing various algorithms, we develop and implement an all convolutional neural network, with cross-validated accuracies for dimensionality and space-group classification of 93% and 89%, respectively. We propose average class activation maps, computed from a global average pooling layer, to allow high model interpretability by human experimentalists, elucidating the root-causes of misclassification. Finally, we systematically evaluate the maximum XRD pattern step size (data acquisition rate) before loss of predictive accuracy occurs, and determine it to be 0.16° 2θ, which enables an XRD pattern to be obtained and classified in 5.5 minutes or less.

36 MATERIALS SCIENCE↗