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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

African land-cover classification using satellite data

Data from the advanced very high resolution radiometer sensor on the National Oceanic and Atmospheric Administration's operational series of meteorological satellites were used to classify land cover and monitor vegetation dynamics for Africa over a 19-month period. There was a correspondence between seasonal variations in the density and extent of green leaf vegetation and the patterns of rainfall associated with the movement of the Intertropical Convergence Zone. Regional variations, such as the 1983 drought in the Sahel of western Africa, were observed. Integration of the weekly satellite data with respect to time for a 12-month period produced a remotely sensed estimate of primary production based upon the density and duration of green leaf biomass. Eight of the 21-day composited data sets covering an 11-month period were used to produce a general land-cover classification that corresponded well with those of existing maps.

Tucker, C. J.↗
NASA NTRS2000

A Sea-Surface Radiation Data Set for Climate Applications in the Tropical Western Pacific and South China Sea

The sea-surface shortwave and longwave radiative fluxes have been retrieved from the radiances measured by Japan's Geostationary Meteorological Satellite 5. The surface radiation data set covers the domain 40S-40N and 90E-170W. The temporal resolution is 1 day, and the spatial resolution is 0.5 deg x 0.5 deg latitude-longitude. The retrieved surface radiation have been validated with the radiometric measurements at the Atmospheric Radiation Measuring (ARM) site on Manus island in the equatorial western Pacific for a period of 15 months. It has also been validated with the measurements at the radiation site on Dungsha island in the South China Sea during the South China Sea Monsoon Experiment (SCSMEX) Intensive Observing Period (May and June 1998). The data set is used to study the effect of El Nino and East Asian Summer monsoon on the heating of the ocean in the tropical western Pacific and the South China Sea. Interannual variations of clouds associated with El Nino and the East Asian Summer monsoon have a large impact on the radiative heating of the ocean. It has been found that the magnitude of the interannual variation of the seasonal mean surface radiative heating exceeds 40 W/sq m over large areas. Together with the Clouds and the Earth's Radiant Energy System (CERES) shortwave fluxes at top of the atmosphere and the radiative transfer calculations of clear-sky fluxes, this surface radiation data set is also used to study the impact of clouds on the solar heating of the atmosphere. It is found that clouds enhance the atmospheric solar heating by approx. 20 W/sq m in the tropical western Pacific and the South China Sea. This result is important for evaluating the accuracy of solar flux calculations in clear and cloudy atmospheres.

Chou, Ming-Dah↗
NASA NTRS2023

Mesospheric and Upper Stratospheric Temperatures From OMPS-LP

We report the development of a temperature profile data set from the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) instrument on the Suomi NPP satellite. The data set covers a roughly 10 year period from 2012 to 2022, and temperatures are provided in the altitude range between 35 and 70 km. The algorithm uses daytime Rayleigh scattered radiation near 350 nm to estimate atmospheric density profiles, which are vertically integrated using the hydrostatic equation to estimate atmospheric pressure. Temperature profiles are then derived using the ideal gas law. Spectral structures in the OMPS-LP radiances are a source of systematic errors that limit the absolute accuracy to ±2 K. However, since the systematic errors do not change significantly over time, the relative accuracy is better than ±1 K. Our temperature data set has been designed to supplement global temperature maps produced by assimilation of data from traditional meteorological sensors, including GNSS radio occultation sensors, that provide high quality atmospheric temperature profiles up to 40–55 km. We show comparisons to other co-located temperature datasets to validate our product.

Observations of Mesospheric and Upper Stratospheri↗
NASA NTRS2018

The Harmonized Landsat and Sentinel-2 Surface Reflectance Data Set

The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a VirtualConstellation (VC) of surface reflectance (SR) data acquired by the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) aboard Landsat 8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, bidirectional reflectance distribution function normalization and spectral bandpass adjustment. Three products are derivedfrom the HLS processing chain: (i) S10: full resolution MSI SR at 10 m, 20 m and 60 m spatial resolutions; (ii)S30: a 30 m MSI Nadir BRDF (Bidirectional Reflectance Distribution Function)-Adjusted Reflectance (NBAR);(iii) L30: a 30 m OLI NBAR. All three products are processed for every Level-1 input products from Landsat 8/OLI (L1T) and Sentinel-2/MSI (L1C). As of version 1.3, the HLS data set covers 10.35 million km2 and spans from first Landsat 8 data (2013); Sentinel-2 data spans from October 2015. The L30 and S30 show a good consistency with coarse spatial resolution products, in particular MODIS Collection 6 MCD09CMG products (overall deviations do not exceed 11%) that are used as a reference for quality assurance. The spatial co-registration of the HLS is improved compared to original Landsat 8 L1T and Sentinel 2A L1C products, for which misregistration issues between multi-temporal data are known. In particular, the resulting computed circular errors at 90% for the HLS product are 6.2 m and 18.8 m, for S10 and L30 products, respectively. The main known issue of the current data set remains the Sentinel-2 cloud mask with many cloud detection omissions. The cross-comparison with MODIS was used to flag products with most evident non-detected clouds. A time series outlier filtering approach is suggested to detect remaining clouds. Finally, several time series are presented to highlight the high potential of the HLS data set for crop monitoring.

Landsat Sentinel-2↗
DOE OSTI2025

Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage

The goal of this project is to develop advanced methods for day-ahead net-load forecasting, by leveraging the state-of-the-art machine learning techniques. The developed models produce both point and probabilistic forecasts for a variety of use cases, and are versatile to work with different types of data sets. The innovation lies in the novel design of the architectures, leveraging the most recent advances in machine learning that have not been explored in power systems, accompanied by techniques in the broader artificial intelligence fields such as fuzzy systems. This project has achieved the following accomplishments: (1) preprocessing of over 10 data sets covering varying geographical regions, time horizons, and system levels, which form a robust foundation for training and evaluating forecasting models across a wide range of realistic grid scenarios; (2) development of an interactive web app that enables exploratory analysis of load and generation data, and supports better understanding of data trends, anomalies, and correlations, facilitating model development and stakeholder engagement; (3) implementation of over 10 benchmark models for point and probabilistic forecasting, which include a mix of conventional machine learning methods and state-of-the-art deep learning approaches, providing a comprehensive baseline for performance comparison and validation of the proposed models; (4) development of a fuzzy system based gradient boosting model, tailored for small (less than 3 years) data sets, which achieves a mean absolute percentage error (MAPE) of 4% for point forecasting and a 20% improvement in average pinball loss for probabilistic forecasting; (5) development of a Transformer (a state-of-the-art deep learning architecture) based neural network model, tailored for large (3 years or more) data sets, which achieves a MAPE of 2% for point forecasting and a 20% improvement in average pinball loss for probabilistic forecasting; (6) development of a methodology for quantifying DR potential, and extensions of the previous models for multi-target forecasting of net load and DR potential, which achieve a MAPE of 10% for DR potential.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Hubble Frontier Field Clusters and Their Parallel Fields: Photometric and Photometric Redshift Catalogs

We present a multiband analysis of the six Hubble Frontier Field clusters and their parallel fields, producing catalogs with measurements of source photometry and photometric redshifts. We release these catalogs to the public along with maps of intracluster light and models for the brightest galaxies in each field. This rich data set covers a wavelength range from 0.2 to 8 μm, utilizing data from the Hubble Space Telescope, Keck Observatories, Very Large Telescope array, and Spitzer Space Telescope. We validate our products by injecting into our fields and recovering a population of synthetic objects with similar characteristics to those in real extragalactic surveys. The photometric catalogs contain a total of over 32,000 entries, with 50% completeness at a threshold of mag AB ~ 29.1 for unblended sources and magAB ~ 29 for blended ones, in the IR-weighted detection band. Photometric redshifts were obtained by means of template fitting and have an average outlier fraction of 10.3% and scatter σ = 0.067 when compared to spectroscopic estimates. The software we devised, after being tested in the present work, will be applied to new data sets from ongoing and future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Investigations of medium wavelength magnetic anomalies in the Eastern Pacific using Magsat data

Processing continued on the data set covering the first three months of the mission. Orbits were selected over a specified range of longitude and latitude and those orbits falling within the geographical boundaries were stored on a disk and a listing made. To verify the quality of the data, plots were made showing altitude vs latitude, anomalous field vs latitude, and corrected anomalous field vs latitude. Results of the plotting showed that: (1) data from the first day of the mission are not usable because they are too noisy; (2) some orbits contain spikes, no doubt a processing error on the tape; (3) some orbits contain a 20 deg region in latitude, offset roughly 30 nT from the rest of the anomalous field profiles; and (4) the correlation between the adjacent orbits is poor. Even the new ring current coefficients provided with a later, corrected set of data tapes did not not yield the desired correlations.

Harrison, C. G. A.↗
DOE OSTI2011

A special issue on the RCPs

This paper provides an editors' introduction to the special issue of Climatic Change on the RCPs. Scenarios form a crucial element in climate change research. They allow researchers to explore the long-term consequences of decisions today, while taking account of the inertia in both the socio-economic and physical system. Scenarios also form an integrating element among the different research disciplines of those studying climate change, such as economists, technology experts, climate researchers, atmospheric chemists and geologists. In 2007, the IPCC requested the scientific community to develop a new set of scenarios, as the existing scenarios (published in the Special Report on Emissions Scenarios, (Nakicenovic and Swart 2000), and called the 'SRES scenarios') needed to be updated and expanded in scope (see Moss et al. (2010) for a detailed discussion). Researchers from different disciplines worked together to develop a process to craft these new scenarios, as summarized by Moss, et al. (2010). The Integrated Assessment Modeling Consortium (IAMC), founded in response to the IPCC call, played a key role in this process.1 The scenario development process aims to develop a set of new scenarios that facilitate integrated analysis of climate change across the main scientific communities. The process comprises 3 main phases: (1) an initial phase, developing a set of pathways for emissions, concentrations and radiative forcing, (2) a parallel phase, comprising both the development of new socio-economic storylines and climate model projections, and (3) an integration phase, combining the information from the first phases into holistic mitigation, impacts and vulnerability assessments. The pathways developed in the first phase were called 'Representative Concentration Pathways (RCPs)'. They play an important role in providing input for prospective climate model experiments, including both the decadal and long-term projections of climate change. The RCPs also provide an important reference point for new research within the integrated assessment modeling (IAM) community by standardizing on a common set of year-2100 conditions, and exploring alternative pathways and policies that could produce these outcomes. By design, the RCPs, as a set, cover the range of radiative forcing levels examined in the open literature and contain relevant information for climate model runs. This Special Issue documents the main assumptions and characteristics of the RCPs, and, in particular, the various steps that were involved in their development. A number of collaborative activities were initiated and finalized during the last 2-3 years to develop the RCPs. This required the cooperation of researchers from various disciplines involved in climate research, including emission experts, climate modelers, atmospheric chemistry modelers, land use modelers and experts involved in integrated assessment. The four RCPs together reflect the range of year-2100 radiative forcing values found in the literature, i.e. from 2.6 to 8.5 W/m{sup 2}. The papers in this Special Issue describe the individual RCPs, but also the various integrative steps that were necessary within the RCP development process to provide a harmonized set of pathways, that show a smooth transition from the past and extend far into the future for very long-term experiments. Important outcomes of this process included, for instance, the development of new emission inventories, new methods for the harmonization of spatial land use patterns, as well as extensions of the RCP trends beyond 2100. They briefly discuss the content of the individual papers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Simplex-stochastic collocation method with improved scalability

The Simplex-Stochastic Collocation (SSC) method is a robust tool used to propagate uncertain input distributions through a computer code. However, it becomes prohibitively expensive for problems with dimensions higher than 5. The main purpose of this paper is to identify bottlenecks, and to improve upon this bad scalability. In order to do so, we propose an alternative interpolation stencil technique based upon the Set-Covering problem, and we integrate the SSC method in the High-Dimensional Model-Reduction framework. In addition, we address the issue of ill-conditioned sample matrices, and we present an analytical map to facilitate uniformly-distributed simplex sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with up 85 compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Altogether, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Modeling Large Dust Aerosols in the Community Earth System Model Version 2 (CESM2)

Dust aerosols have a wide size distribution from less than 0.1 to over 100 μm and dominate Earth's atmospheric aerosol mass. However, most Earth system models (ESMs) inadequately represent dust aerosols larger than 10 μm in diameter, limiting the accuracy of the simulated dust cycle and climate impacts. Here, we introduce a new modeling framework that captures the full observed size distribution of dust aerosols, incorporating recent advances into a mineral-resolved version of the Community ESM, while addressing known issues in previous versions. Comprehensive evaluation against diverse observations of bulk dust and component minerals demonstrates that the model reproduces the observed dust cycle across particle sizes. Incorporating the previously unrepresented large-dust fractions substantially alters dust budget estimates, highlighting potential changes in simulated climate impacts and underscoring the importance of comprehensive size-resolved dust modeling. Despite these advancements, uncertainties persist. Our results indicate that a size-dependent reduction in settling velocity is required to reproduce the observed dust size distribution downwind of source regions. Specifically, in the new model, the gravitational settling velocity of dust particles larger than 10 μm in diameter must be reduced by as much as 85% to achieve agreement with observations. This empirical reduction serves as a constraint on physics-based models of dust settling. Future developments should address misrepresented physical processes that hinder accurate modeling of the large dust aerosol transport. Expanding observational data sets covering the full-size distribution is also essential to better constrain the dust cycle and improve the representation of dust optical properties and climate effects.

Li, Longlei [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2025

The imprint of cosmic voids from the DESI Legacy Survey DR9 Luminous Red Galaxies in the Planck 2018 lensing map through spectroscopically calibrated mocks

The cross-correlation of cosmic voids with the lensing convergence (κ) map of the Cosmic Microwave Background (CMB) fluctuations provides a powerful tool to refine our understanding of the current cosmological model. However, several studies have reported a moderate tension (up to ∼2σ) between the lensing imprint of cosmic voids on the observed CMB and the ΛCDM signal predicted by simulations. To address this “lensing-is-low” tension and to obtain new, precise measurements of the signal, we exploit the large DESI Legacy Survey Luminous Red Galaxy (LRG) data set, covering approximately 19 500 deg 2 of the sky and including about 10 million LRGs at z < 1.05. Our ΛCDM template was created using the Buzzard mocks, which we specifically calibrated to match the clustering properties of the observed galaxy sample by exploiting more than one million DESI spectra. We identified our catalogs of 3D voids in the range 0.35 < z < 0.95 and cross-correlated them through a stacking methodology, dividing the sample into bins according to the redshift and λv values of the voids. For the full void sample, we report a 14σ detection of the lensing signal, with A κ = 1.016 ± 0.054, which increases to 17σ when considering the void-in-void (A κ = 0.944 ± 0.064) and the void-in-cloud (A κ = 0.975 ± 0.060) populations individually, the highest detection significance for studies of this kind. We observe a full agreement between observations and ΛCDM mocks across all redshift bins, sky regions, and void populations considered. In addition to these findings, our analysis highlights the importance of accurately matching sparseness and redshift error distributions between mocks and observations, as well as the role of λ v in enhancing the signal-to-noise ratio through void population discrimination.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Polarization observables in the photoproduction of phi mesons with linearly polarized photons

Polarization observables from vector meson photoproduction by linearly-polarized photons can be expressed in terms of bilinear combinations of helicity amplitudes parameterized by the Spin Density Matrix Elements (SDMEs). These SDMEs, which are reconstructed from the measured polarization observables, give straightforward relations for understanding the nature of the parity exchange at threshold energies, as well as for extracting signatures of the Okubo-Zweig-Iizuka violation. This paper will show our measurements of the SDMEs for reaction {gamma}p {yields} {rho}p from the g8b experimental dataset taken with the CLAS detector in Hall B of Jefferson Lab. In particular, we have extracted polarization observables from two separate coherent peak settings covering the respective photon energy ranges: 1.7 to 1.9 GeV (momentum transfer squared t range of -1.2 to -0.25 GeV{sup 2}) and 1.9 to 2.1 GeV (t range of -1.4 to -0.25 GeV{sup 2}).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

On a framework for generating PoD curves assisted by numerical simulations

The Probability of Detection (PoD) curve method has emerged as an important tool for the assessment of the performance of NDE techniques, a topic of particular interest to the nuclear industry where inspection qualification is very important. The conventional experimental means of generating PoD curves though, can be expensive, requiring large data sets (covering defects and test conditions), and equipment and operator time. Several methods of achieving faster estimates for PoD curves using physics-based modelling have been developed to address this problem. Numerical modelling techniques are also attractive, especially given the ever-increasing computational power available to scientists today. Here we develop procedures for obtaining PoD curves, assisted by numerical simulation and based on Bayesian statistics. Numerical simulations are performed using Finite Element analysis for factors that are assumed to be independent, random and normally distributed. PoD curves so generated are compared with experiments on austenitic stainless steel (SS) plates with artificially created notches. We examine issues affecting the PoD curve generation process including codes, standards, distribution of defect parameters and the choice of the noise threshold. We also study the assumption of normal distribution for signal response parameters and consider strategies for dealing with data that may be more complex or sparse to justify this. These topics are addressed and illustrated through the example case of generation of PoD curves for pulse-echo ultrasonic inspection of vertical surface-breaking cracks in SS plates.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Detection and imaging of the oxygen deficiency in single crystalline YBa{sub 2}Cu{sub 3}O{sub 7−δ} thin films using a scanning positron beam

Single crystalline YBa{sub 2}Cu{sub 3}O{sub 7−δ} (YBCO) thin films were grown by pulsed laser deposition in order to probe the oxygen deficiency δ using a mono-energetic positron beam. The sample set covered a large range of δ (0.191 < δ < 0.791) yielding a variation of the critical temperature T{sub c} between 25 and 90 K. We found a linear correlation between the Doppler broadening of the positron electron annihilation line and δ determined by X-ray diffraction. Ab-initio calculations have been performed in order to exclude the presence of Y vacancies and to ensure the negligible influence of potentially present Ba or Cu vacancies to the found correlation. Moreover, scanning with the positron beam allowed us to analyze the spatial variation of δ, which was found to fluctuate with a standard deviation of up to 0.079(5) within a single YBCO film.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

A critical appraisal of the zero-multipole method: Structural, thermodynamic, dielectric, and dynamical properties of a water system

We performed extensive and strict tests for the reliability of the zero-multipole (summation) method (ZMM), which is a method for estimating the electrostatic interactions among charged particles in a classical physical system, by investigating a set of various physical quantities. This set covers a broad range of water properties, including the thermodynamic properties (pressure, excess chemical potential, constant volume/pressure heat capacity, isothermal compressibility, and thermal expansion coefficient), dielectric properties (dielectric constant and Kirkwood-G factor), dynamical properties (diffusion constant and viscosity), and the structural property (radial distribution function). We selected a bulk water system, the most important solvent, and applied the widely used TIP3P model to this test. In result, the ZMM works well for almost all cases, compared with the smooth particle mesh Ewald (SPME) method that was carefully optimized. In particular, at cut-off radius of 1.2 nm, the recommended choices of ZMM parameters for the TIP3P system are α ≤ 1 nm{sup −1} for the splitting parameter and l = 2 or l = 3 for the order of the multipole moment. We discussed the origin of the deviations of the ZMM and found that they are intimately related to the deviations of the equilibrated densities between the ZMM and SPME, while the magnitude of the density deviations is very small.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Multi-MHz time-of-flight electronic bandstructure imaging of graphene on Ir(111)

In the quest for detailed spectroscopic insight into the electronic structure at solid surfaces in a large momentum range, we have developed an advanced experimental approach. It combines the 3D detection scheme of a time-of-flight momentum microscope with an optimized filling pattern of the BESSY II storage ring. Here, comprehensive data sets covering the full surface Brillouin zone have been used to study faint substrate-film hybridization effects in the electronic structure of graphene on Ir(111), revealed by a pronounced linear dichroism in angular distribution. The method paves the way to 3D electronic bandmapping with unprecedented data recording efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A Look Inside the Black Box: Using graph-theoretical descriptors to interpret a Continuous-Filter Convolutional Neural Network (CF-CNN) trained on the global and local minimum energy structures of neutral water clusters

A Continuous Filter Convolutional Neural Network (CF-CNN) was trained to predict the potential energy of water cluster networks \ce{(H2O)_{\textit{N}}}, \textit{N}=10--30, corresponding to local minima lying within 5 kcal/mol from the putative minima taken from a newly published database containing over 5 million unique networks. The chemical sampling space of the database was characterized using chemical descriptors derived from graph theory, which led to the identification of important trends in the topology, connectivity, polygon structures associated with the various networks as a function of cluster size. The resulting graphs are available alongside the original database at \url{https://sites.uw.edu/wdbase/}. The CF-CNN trained on a subset of 500,000 networks for (\textit{N}=10, 30) yielded a mean absolute error of 0.002$\pm$0.002 kcal/mol per water molecule, giving the trained CF-CNN the highest accuracy of any neural network-based surrogate model to date. In addition, clusters of sizes not included in the training set exhibited errors of the same magnitude, indicating that the CF-CNN ptotocol is general enough to accurately predict energies of networks for both smaller and larger sizes than those used during training. The graph-theoretical descriptors were developed in order to analyze the properties of the full database and interpret the predictive power of the CF-CNN. Using topology measures, such as the Wiener index and the average shortest path length along with two similarity measures, we showed that all networks from the test set were within the range of the ones from the training set, suggesting that the training set covered the chemical space of interest quite well. Our graph analysis suggests that the mean degree and number of polygons for networks with larger errors tend to lie further from the mean than those with lower errors. The generality of the used CF-CNN was thus demonstrated, while the use of the graph-theoretical descriptors assisted in interpreting the predicted results.

Bilbrey, Jenna A.↗