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DOE OSTI2017

Linear and Nonlinear Constitutive Model for Piezoelectricity in ALEGRA-FE

This report develops and documents linear and nonlinear constitutive relations implemented in ALEGRA-FE (ferroelectric). A thermodynamic framework is created to describe the electromechanical system in the form of a free energy functional. Constitutive relations are derived by taking series expansions of the free energy functional with respect to the independent fields. First order expansion terms yield linear constitutive relations and higher order expansion terms yield non-linear constitutive relations. This document serves as supplement to Section 4 of Sandia Report SAND2013-7363, Rev 3. Methods for implementation of kinematic relations of piezoelectric models and rotation of material principal axes are covered in the supplemented report. Additional discussion on phase velocity calculation is also presented.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Transforming our understanding of chloroplast-associated genes through comprehensive characterization of protein localizations and protein-protein interactions

Bioenergy crops are a renewable source of fuels and are a critical base for building a carbon-neutral economy. Rational engineering of bioenergy crops has the potential to enhance the yields. However, our ability to engineer plants is limited because the functions of most genes remain unknown. Systematic characterization of gene function in plants thus has the potential to greatly accelerate bioenergy research. Here, we focus on the chloroplast, an underexplored energy-producing organelle that is a hallmark of plants. The chloroplast is one of the promising targets of biofuel crop engineering efforts because of its central role in photosynthesis, metabolism, and intracellular signaling. However, the protein composition of the chloroplast and the functions of most of its proteins remain poorly characterized. At the core of this project, we sought to comprehensively determine the localization of chloroplast-associated proteins and generate a spatially defined protein-protein interaction network for chloroplast. For this purpose, we used the leading model alga Chlamydomonas reinhardtii, which greatly increased experimental speed and throughput. We illustrated the value of our findings to land plants by determining the localization of Arabidopsis thaliana land plant homologs of the Chlamydomonas proteins. Altogether, we were successful in determining the localization of 1,034 chloroplast-associated proteins in Chlamydomonas. The localizations provide numerous insights into the spatial organization of chloroplasts and how they function to support photosynthesis. The localization patterns of distinct proteins revealed new chloroplast structures and revealed new spatial organization inside the chloroplast. We also identified new components of known chloroplast structures, such as the chloroplast envelope, nucleoid, plastoglobuli, and pyrenoid. We identified these new components by investigating the interacting partners of known proteins. Many proteins localized in both the chloroplast and other cellular structures, thereby hinting at new functions and communication between cellular structures. We also applied machine learning on the atlas to generate predictions for the location of all of the proteins in Chlamydomonas. This enabled us to assign putative functions to many uncharacterized proteins based on their cellular location. Altogether, this research establishes a rich resource that opens new avenues of investigation and guides future work in deciphering and manipulating chloroplast function. Next, we developed an extensive protein-protein interaction network for the chloroplast by performing affinity purification-mass spectrometry on ~1,150 tagged chloroplast-associated proteins, the first such large-scale study in any photosynthetic organism. This dataset reveals 4,694 high-confidence protein-protein interactions, offering insights into the functions of thousands of conserved poorly-characterized chloroplast proteins. This systematic identification of protein-protein interactions in the chloroplast also provides multiple exciting new research directions and a detailed blueprint of the chloroplast's operation. This research lays the groundwork to decipher the inner workings of the chloroplast, the cell structure at the heart of photosynthesis. The spatial atlas and protein-protein interactions reveal chloroplast organizational features that would not have been accessible with traditional approaches. The localization mapping, insights into the function, and research materials generated further provide a rich resource for the research community to advance the understanding of how the chloroplast is organized to enable engineering of enhanced photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Many-Body Effects in FeN4 Center Embedded in Graphene

We introduce a computational approach to study porphyrin-like transition metal complexes, bridging density functional theory and exact many-body techniques, such as the density matrix renormalization group (DMRG). We first derive a multi-orbital Anderson impurity Hamiltonian starting from first principles considerations that qualitatively reproduce generalized gradient approximation (GGA)+U results when ignoring inter-orbital Coulomb repulsion U ′ and Hund exchange J. An exact canonical transformation is used to reduce the dimensionality of the problem and make it amenable to DMRG calculations, including all many-body terms (both intra- and inter-orbital), which are treated in a numerically exact way. We apply this technique to FeN 4 centers in graphene and show that the inclusion of these terms has dramatic effects: as the iron orbitals become single occupied due to the Coulomb repulsion, the inter-orbital interaction further reduces the occupation, yielding a non-monotonic behavior of the magnetic moment as a function of the interactions, with maximum polarization only in a small window at intermediate values of the parameters. Furthermore, U ′ changes the relative position of the peaks in the density of states, particularly on the iron d z 2 orbital, which is expected to affect the binding of ligands greatly.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Spin Splitting Energy of Transition Metals: A New, More Affordable Wave Function Benchmark Method and Its Use to Test Density Functional Theory

Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe 2+ , Fe 3+ , and Co 3+ , including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. Furthermore, we find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method—in terms of computational cost and in terms of accuracy on monatomic systems—and therefore we chose this method for molecular benchmarks. Then Kohn–Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF 2 , FeCl 2 , and CoF 2 . We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Efficient method for estimation of fission fragment yields of $\textit{r}$-process nuclei

Background: More than half of all the elements heavier than iron are made by the rapid neutron capture process (or $\textit{r}$ process). For very-neutron-rich astrophysical conditions, such at those found in the tidal ejecta of neutron stars, nuclear fission determines the $\textit{r}$-process endpoint, and the fission-fragment yields shape the final abundances of 110 ≤ $\textit{A}$ ≤ 170 nuclei. The knowledge of fission-fragment yields of hundreds of nuclei inhabiting very-neutron-rich regions of the nuclear landscape is thus crucial for the modeling of heavy-element nucleosynthesis. Purpose: In this study, we propose a model for the fast calculation of fission-fragment yields based on the concept of shell-stabilized prefragments defined with help of the nucleonic localization functions. Methods: To generate realistic potential-energy surfaces and nucleonic localizations, we apply Skyrme density-functional theory. In this work, the distribution of the neck nucleons among the two prefragments is obtained by means of a statistical model. Results: We benchmark the method by studying the fission yields of 178 Pt, 240 Pu, 254 Cf, and 254,256,258 Fm and show that it satisfactorily explains the experimental data. We then make predictions for 254 Pu and 290 Fm as two representative cases of fissioning nuclei that are expected to significantly contribute during the $\textit{r}$-process nucleosynthesis occurring in neutron-star mergers. Conclusions: The proposed framework provides an efficient alternative to microscopic approaches based on the evolution of the system in a space of collective coordinates all the way to scission. It can be used to carry out global calculations of fission-fragment distributions across the $\textit{r}$-process region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Type 2 diabetes mellitus correlates with systolic function during myocardial stress perfusion scanning with Nitrogen-13 ammonia PET

Background: The influence of type 2 diabetes mellitus (DM2) on systolic function is partially determined by the coronary vasodilator function, nevertheless, an independent effect is suspected. We evaluated the relationship between DM2 and systolic function considering PET quantitative myocardial perfusion. Methods: We analyzed 585 patients without a previous myocardial infarction referred to a rest and adenosine stress Nitrogen-13 ammonia PET. A bootstrapped multiple linear regression analysis was performed using DM2, stress myocardial blood flow (sMBF), myocardial perfusion reserve (MPR), and clinical risk factors as predictors and LVEF as the outcome variable; an interaction term was additionally investigated. Results: Two hundred and ninety male and 295 female patients (mean age 65.3 ± 9.9 and 67.4 ± 10 years, respectively) were included. 57.1% presented hypertension, 16% smoking, 37.6% hypercholesterolemia, 33.8% family history for CAD, and 15.2% DM2. The mean MPR was 2.13 ± 0.48 and 2.21 ± 0.60, mean sMBF was 2.01 ± 0.51 and 2.15 ± 0.54, and mean LVEF was 63% ± 10.4 and 67% ± 10.1 for diabetics and non-diabetics, respectively. A significant relation was detected for sMBF (B = 5.830 95% CI [3.505, 9.549], P = .001) and DM2 (B = −2.599 95% CI [−5.125, −0.119], P = .03) with LVEF. The interaction (DM2 × sMBF) yielded no significance (P = .512). Conclusion: DM2 influences PET-measured systolic function in patients without previous myocardial infarction independently from myocardial perfusion parameters. Our study supports the importance of DM2 as an independent risk factor for deteriorating systolic function.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Synthesis of Carboxyl-Rich Biosorbent by UV-Induced Graft Polymerization Method for High Efficiency Adsorption of Ce{sup 3+} from Aqueous Solution: Activation and Adsorption Mechanism

Developing a cost-effective and highly efficient sorbent for the recovery of rare-earth elements from aqueous solution is still an urgent need. In this study, a novel biosorbent, carboxyl-rich pine bark (CPB), was modified by UV-induced graft polymerization method to increase the carboxyl-containing functional groups and facilitate the adsorption of Ce{sup 3+}. The grafting process was examined by Fourier transform infrared (FTIR) spectroscopy and field emission scanning electron microscopy (FESEM), indicating that high-density carboxyl functional groups are present on the surface of pine bark and the grafting yield of surface polymer brushes reaches up to 128%. Interestingly, the maximum adsorption capacity of Ce{sup 3+} on CPB could reach up to 256.5 mg/g. The adsorption mechanism of Ce{sup 3+} by CPB has been determined by the adsorption models and x-ray photoelectron spectroscopy (XPS), which can be inferred from these results that the high performance of CPB is attributed to the surface coordination between Ce{sup 3+} and hydroxyl or carbonyl groups. This work suggests that engineered surface functional groups of biomass could have an opportunity for the development of high performance rare-earth element adsorbents.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Multiplicity-dependent jet modification from di-hadron correlations in pp collisions at $ \sqrt{s} $ = 13 TeV

Short-range correlations between charged particles are studied via two-particle angular correlations in pp collisions at $\sqrt{s}$ = 13 TeV. The correlation functions are measured as a function of the relative azimuthal angle ∆φ and the pseudorapidity separation ∆η for pairs of primary charged particles within the pseudorapidity interval |η| < 0.9 and the transverse-momentum range 1 < p T < 8 GeV/c. Near-side (|∆φ| < 1.3) peak widths are extracted from a generalised Gaussian fitted over the correlations in full pseudorapidity separation (|∆η| < 1.8), while the per-trigger associated near-side yields are extracted for the short-range correlations (|∆η| < 1.3). Both are evaluated as a function of charged-particle multiplicity obtained by two different event activity estimators. The width of the near-side peak decreases with increasing multiplicity, and this trend is reproduced qualitatively by the Monte Carlo event generators PYTHIA 8, AMPT, and EPOS. However, the models overestimate the width in the low transverse-momentum region (p T < 3 GeV/c). The per-trigger associated near-side yield increases with increasing multiplicity. Although this trend is also captured qualitatively by the considered event generators, the yield is mostly overestimated by the models in the considered kinematic range. The measurement of the shape and yield of the short-range correlation peak can help us understand the interplay between jet fragmentation and event activity, quantify the narrowing trend of the near-side peak as a function of transverse momentum and multiplicity selections in pp collisions, and search for final-state jet modification in small collision systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Emergence of Long-Range Angular Correlations in Low-Multiplicity Proton-Proton Collisions

This Letter presents the measurement of near-side associated per-trigger yields, denoted ridge yields, from the analysis of angular correlations of charged hadrons in proton-proton collisions at s = 13 TeV . Long-range ridge yields are extracted for pairs of charged particles with a pseudorapidity difference of 1.4 < | Δ η | < 1.8 and a transverse momentum of 1 < p T < 2 GeV / c , as a function of the charged-particle multiplicity measured at midrapidity. This Letter extends the measurements of the ridge yield to the low multiplicity region, where in hadronic collisions it is typically conjectured that a strongly interacting medium is unlikely to be formed. The precision of the new low multiplicity results allows for the first direct quantitative comparison with the results obtained in e + e − collisions at s = 91 GeV and s = 183 – 209 GeV , where initial-state effects such as preequilibrium dynamics and collision geometry are not expected to play a role. In the multiplicity range 8 ≲ ⟨ N ch ⟩ ≲ 24 where the e + e − results have good precision, the measured ridge yields in p p collisions are substantially larger than the limits set in e + e − annihilations. Consequently, the findings presented in this Letter suggest that the processes involved in e + e − annihilations do not contribute significantly to the emergence of long-range correlations in p p collisions. © 2024 CERN, for the ALICE Collaboration 2024 CERN

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

The effect of radiation damage on the light yield and uniformity of candidate plastic scintillator tiles for the CMS hadron calorimeter upgrade

A study has been performed to understand the effects of radiation damage on various plastic scintillator tiles considered for a possible upgrade of the hadron calorimeter of the CMS detector. Measurements were made with unirradiated tiles and with tiles that had been irradiated in the CMS collision hall to a dose of 44 kGy. Results are presented for the tiles of different shapes in terms of the energy spectrum, efficiency as a function of the position at which each tile was hit, as well as light yield. All the tiles showed a light reduction of up to about 50%. The tiles with the shape currently used in the CMS detector did not see increased non-uniformity of light collection, while a significant disuniformity was observed for the tiles considered as alternatives.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

In Situ X-Ray Studies of Crystallization Kinetics and Ordering in Functional Organic and Hybrid Materials

In-Situ and time-resolved X-ray scattering and diffraction is dedicated to yielding the change of structural information as the materials are processed or grown in a controlled environment. In this chapter, we introduce the use of in situ and time-resolved X-ray techniques to understand molecular packing, crystal orientation, and phase transformation during the synthesis and processing of functional organic semiconductors, organic nanowires, and hybrid perovskite materials.

Yang, Bin↗

DOE OSTI2020

Aqueous solvation of the chloride ion revisited with density functional theory: impact of correlation and exchange approximations

The specificity of aqueous halide solvation is fundamental to a wide range of bulk and interfacial phenomena spanning from biology to materials science. Halide polarizability is thought to drive the ion specificity, and if so, it is essential to have an accurate description of the electronic properties of halide ions in water. To this end, the solvation of the chloride anion, Cl - has been reinvestigated with state-of-the-art density functional theory. Specifically, the PBE-D3, PBE0-D3, and SCAN functionals have been employed to probe the impact of correlation and exchange approximations. Anticipating the findings, adding exact exchange improves the electronic structure, but simultaneously significantly reduces the Cl - polarizability, resulting in an over-structured Cl–O radial distribution function (RDF) and longer water H-bond lifetimes to Cl - . SCAN does not yield as much improvement in the energetics of Cl - relative to bulk water, but does result in a smaller reduction of the polarizability and thus a less structured Cl–O RDF, which agrees better with experiment. Special consideration is therefore warranted in assessing the impact of exchange on the energy, charge density, and the charge density response when designing and testing hybrid functionals for aqueous halide solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Quantitative Evaluation of Head and Neck Cancer Treatment–Related Dysphagia in the Development of a Personalized Treatment Deintensification Paradigm

To test the hypothesis that quantifying swallow function with multiple patient-reported outcome (PRO) instruments is an important strategy to yield insights in the development of personalized deintensified therapies seeking to reduce the risk of head and neck cancer (HNC) treatment–related dysphagia (HNCTD).

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Revisiting alkaline aerobic lignin oxidation

Lignin conversion to renewable chemicals is a promising means to improve the economic viability of lignocellulosic biorefineries. Alkaline aerobic oxidation of lignin has long been employed for production of aromatic compounds such as vanillin and syringaldehyde, but this approach primarily focuses on condensed substrates such as Kraft lignin and lignosulfonates. Conversely, emerging lignocellulosic biorefinery schemes enable the production of more native-like, reactive lignin. Here, we revisit alkaline aerobic oxidation of highly reactive lignin substrates to understand the impact of reaction conditions and catalyst choice on product yield and distribution. The oxidation of native poplar lignin was studied as a function of temperature, NaOH loading, reaction time, and oxygen partial pressure. Besides vanillin and syringaldehyde, other oxidation products include acetosyringone and vanillic, syringic, and p-hydroxybenzoic acids. Reactions with vanillin and syringaldehyde indicated that these compounds are further oxidized to non-aromatic carboxylic acids during alkaline aerobic oxidation, with syringaldehyde being substantially more reactive than vanillin. The production of phenolic compounds from lignin is favored by high NaOH loadings and temperatures, but short reaction times, as the products degrade rapidly, which is further exacerbated by the presence of oxygen. Under optimal conditions, a phenolic monomer yield of 30 wt% was obtained from poplar lignin. Testing a range of catalysts showed that Cu-containing catalysts, such as CuSO 4 and LaMn 0.8 Cu 0.2 O 3 , accelerate product formation; specifically, the catalyst does not increase the maximum yield, but expands the operating window in which high product yields are obtainable. We also demonstrate that other native and isolated lignin substrates that are significantly chemically modified are effectively converted to phenolic compounds. Finally, alkaline aerobic oxidation of native lignins was compared to nitrobenzene oxidation and reductive catalytic fractionation, as these methods constitute suitable benchmarks for lignin depolymerization. While nitrobenzene oxidation achieved a somewhat higher yield, similar monomer yields were obtained through RCF and alkaline aerobic oxidation, especially for lignins with a high guaiacyl- and/or p-hydroxyphenyl-content, as syringyl units are more unstable during oxidation. Overall, this study highlights the potential for aerobic lignin oxidation revisited on native-like lignin substrates.

09 BIOMASS FUELS↗

DOE OSTI2024

Investigation of Materials for Radio Frequency Antenna Plasma Facing Components

Here, the interaction of radio frequency (RF) sheaths with fusion reactor relevant materials (e.g., tungsten and titanium diboride) is being studied on the RF Plasma Interaction Experiment (RF PIE). The RF PIE consists of an electron cyclotron resonance (ECR) plasma source (2.45 GHz, 5 kW) with a biased and heated RF electrode that is used to simulate antenna surfaces in contact with the edge plasma. Helium plasmas (density of ~1e18/m 3 , electron temperature of 4–5 eV) are being used to explore sheath formation on material surfaces with biases up to 500 V. The erosion of a tungsten surface is being studied spectroscopically using a mirror-linked 1 m Czerny-Turner UV imaging spectrometer with a spectral resolution of 0.012 nm for measuring plasma emission in and near the sheath. Tungsten line emission intensity is higher for RF versus dc biasing for similar plasma conditions and average ion energy. RF biasing causes a broadening of the ion energy distribution function (IEDF) due to the RF sheath, as determined from the hPIC2 code, and results in enhanced sputtering. Calculations of the expected sputtering yield for dc and RF biasing are consistent with experimental observations of changes in the 400.9 nm tungsten line emission intensity as a function of ion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Connecting agriculture and renewable energy: insights into microclimatic changes, physiological, biochemical, and yield responses under agrivoltaics: a review

Agrivoltaics, the synergistic integration of agriculture and solar energy production on the same piece of land, has emerged as a compelling dual-use solution that maximizes land productivity while simultaneously addressing the need for sustainable agricultural practices and renewable energy generation. Despite the growing global interest in this dual-use system, the microclimatic shifts created beneath solar panels and their consequences for crop performance remain insufficiently synthesized. This review highlights the intricate interactions between agrivoltaics systems and plant microclimates, discussing their impacts on various physiological processes, metabolic pathways, and overall yield responses in different crop species. Evidence indicates that moderated light intensity and altered microclimates can enhance water-use efficiency, stabilize photosynthetic function, and trigger beneficial metabolic adjustments; however, responses remain highly species-specific and strongly dependent on regional climate conditions and panel configuration. Yield outcomes vary widely among vegetables, cereals, pulses, and fruit crops, highlighting the necessity for tailored agronomic strategies and crop selection within agrivoltaic designs. A critical knowledge gap identified in this review concerns the limited understanding of molecular and omics-level responses underlying plant adaptation to agrivoltaic environments. We further provide a detailed and interdisciplinary overview of adaptive agronomic strategies, and optimal crop selection, tailored to agrivoltaic systems. Despite the benefits of land use efficiency and simultaneous food and energy production, challenges remain concerning initial investment, technological adaptation, social and legal barriers, and shade-induced yield penalties. Further research in this area will be critical to enhancing the agricultural, environmental, and economic sustainability of agrivoltaics while simultaneously augmenting their practical utility and appeal to farmers in the future.

14 SOLAR ENERGY↗

DOE OSTI2020

An error-in-constitutive equations strategy for topology optimization for frequency-domain dynamics

This paper presents a topology optimization formulation for frequency-domain dynamics to reduce solution dependence upon initial guess and considered loading conditions. Due to resonance phenomena in undamped steady-state dynamics, objectives measuring dynamic response possess many local minima that may represent poor solutions to a design problem, an issue exacerbated for design with respect to multiple frequencies. In this work, we propose an extension of the modified error-in-constitutive-equations (MECE) method, used previously in material identification inverse problems, as a new approach for frequency-domain dynamics topology optimization to mitigate these issues. The main idea of the proposed framework is to incorporate an additional penalty-like term in the objective function that measures the discrepancy in the constitutive relations between stresses and strains and between inertial forces and displacements. Then, the design problem is cast within a PDE-constrained optimization formulation in which we seek displacements, stresses, inertial forces, and a density-field solution that minimize our new objective subject to conservation of linear momentum plus some additional constraints. We show that this approach yields superior designs to conventional gradient-based optimization approaches that solely use a functional of displacements as the objective, while strictly enforcing the constitutive equations. The MECE strategy integrates into a density-based topology optimization scheme for void–solid or two-phase material structural design. We highlight the merits of our approach in a variety of scenarios for direct frequency response design, considering multiple frequency load cases and structural objectives.

42 ENGINEERING↗

DOE OSTI2023

pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radiation models, and validating irradiance datasets. However, lack of standardization in data formats and access interfaces across providers constitutes a major barrier to entry for new users. pvlib python’s iotools subpackage aims to solve this issue by providing standardized Python functions for reading local files and retrieving data from external providers. All functions follow a uniform pattern and return convenient data outputs, allowing users to seamlessly switch between data providers and explore alternative datasets. The pvlib package is community-developed on GitHub: https://github.com/pvlib/pvlib-python. As of pvlib python version 0.9.5, the iotools subpackage supports 12 different datasets, including ground measurement, reanalysis, and satellite-derived irradiance data. The supported ground measurement networks include the Baseline Surface Radiation Network (BSRN), NREL MIDC, SRML, SOLRAD, SURFRAD, and the US Climate Reference Network (CRN). Additionally, satellite-derived and reanalysis irradiance data from the following sources are supported: PVGIS (SARAH & ERA5), NSRDB PSM3, and CAMS Radiation Service (including McClear clear-sky irradiance).

14 SOLAR ENERGY↗