SEARCH · Search NASA

Results for “analyzable function”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗

DOE OSTI2022

Self-consistency in GWΓ formalism leading to quasiparticle-quasiparticle couplings

Within many-body perturbation theory, Hedin's formalism offers a systematic way to iteratively compute the self-energy Σ of any dynamically correlated interacting system, provided one can evaluate the interaction vertex Γ exactly. This is, however, impossible, in general, for it involves the functional derivative of Σ with respect to the Green's function. Here, we analyze the structure of this derivative, splitting it into four contributions and outlining the type of quasiparticle interactions that each of them generate. Moreover, we show how, in the implementation of self-consistency, the action of these contributions can be classified into two: A quantitative renormalization of previously included interaction terms and the inclusion of qualitatively distinct interaction terms through successive functional derivatives of Γ itself. Implementing this latter type of self-consistency can extend the validity of perturbative approximations based on Hedin's equations toward the high interaction limit, as we show in the example of the Hubbard dimer. Furthermore, our analysis also provides a unifying perspective on the perturbation theory landscape, showing how the T-matrix approach is completely contained in Hedin's formalism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Interpretable machine learning study of the many-body localization transition in disordered quantum Ising spin chains

We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy E is bounded by a bandwidth W = E max – E min . The transition takes place on a phase diagram spanned by the energy density ε = 2(E – E min )/W and the disorder strength δJ of the spin interaction uniformly distributed within [ – δJ, δJ], formally parallel to the mobility edge in Anderson localization. In our paper, we use the labeled probability density of eigenstate wave functions belonging to the deeply localized and thermal regimes at two different energy densities (ε's) as the training set, i.e., providing labeled data at four corners of the phase diagram. Then we employ the trained SVM to predict the whole phase diagram. The obtained phase boundary qualitatively agrees with previous work using entanglement entropy to characterize these two phases. We further analyze the decision function of the SVM to interpret its physical meaning and find that it is analogous to the inverse participation ratio in configuration space. Our findings demonstrate the ability of the SVM to capture potential quantities that may characterize the many-body localization phase transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Ionizing Radiation Sensing with Functionalized and Copper-Coated SWCNT/PMMA Thin Film Nanocomposites

This paper studies the ionizing radiation effects on functionalized single-walled carbon nanotube (SWCNT)/poly(methyl methacrylate) (PMMA) thin-film nanocomposites [SWNT/PMMA]. The functionalized thin-film devices are made of ferrocene-doped SWCNTs, SWCNTs functionalized with carboxylic acid (COOH), and SWCNTs coated/ modified with copper. The nanocomposite was synthesized by the solution blending method and the resulting nanocomposite was spin-cast on interdigitated electrodes (IDEs). A 160 kV X-ray source was used to irradiate the thin film and changes in the electrical resistance of the nanocomposites due to X-rays were measured using a semiconductor device analyzer. Carboxylic acid functionalized and copper-coated SWCNT/PMMA nanocomposite showed a reduced response to X-rays compared to unfunctionalized SWCNT/PMMA nanocomposite. Ferrocene-doped SWCNT showed a higher sensitivity to X-rays at lower dose rates. This is in contrast to a previous study that showed that similar nanocomposites using functionalized multi-walled CNTs (MWCNTs) had demonstrated an improved response to X-rays ionizing radiation compared to unfunctionalized MWCNTs for all dose rates. Electrical measurements were also performed using the Arduino Nano microcontroller. The result showed that a relatively economical, lightweight-designed prototype radiation sensor based on SWCNT/PMMA thin-film devices could be produced by interfacing the devices with a modest microcontroller. This work also shows that by encapsulating the SWCNT/PMMA thin-film device in a plastic container, the effect of ambient humidity can be reduced and the device can still be used to detect X-ray radiation. This study further shows that the sensitivity of SWCNT to X-rays was dependent on both the functionalization of the SWCNT and the dose rate.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Real-time evolution of Anderson impurity models via tensor network influence functionals

In this work, we present and analyze two tensor network-based influence functional approaches for simulating the real-time dynamics of quantum impurity models such as the Anderson model. Via comparison with recent numerically exact simulations, we show that such methods accurately capture the long-time nonequilibrium quench dynamics. The two parameters that must be controlled in these tensor network influence functional approaches are a time discretization (Trotter) error and a bond dimension (tensor network truncation) error. We show that the actual numerical uncertainties are controlled by an intricate interplay of these two approximations, which we demonstrate in different regimes. Our work opens the door to using these tensor network influence functional methods as general impurity solvers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Unlocking the Future of Aircraft Manufacturing: The Environmental Benefits of Laser Patterning for Surface Enhancement of Aircraft-Certified Alloys

Surface protection and functional modification of aircraft-certified aluminum alloys are essential for corrosion resistance, durability, and long-term airworthiness. At the same time, increasingly restrictive environmental regulations motivate the development of alternatives to legacy wet-chemical surface treatments. This study presents an integrated assessment of ultrafast femtosecond laser surface texturing as a surface functionalization approach for Aluminum 6061 alloys within an aerospace manufacturing and sustainability context. Ultrashort-pulse laser processing enables controlled micro- and nano-scale surface topographical modification with limited thermal impact, allowing adjustment of wettability and surface functionality while preserving bulk material integrity. As a dry and contactless process, femtosecond laser treatment eliminates the use of hazardous chemicals, reduces consumable inputs, and generates minimal secondary waste. A streamlined cradle-to-gate life cycle assessment conducted in accordance with ISO 14040/14044 indicates a lower global-warming potential per functional unit compared with conventional surface treatments, including anodization, plasma-assisted coatings, and organic coating systems. Complementary qualitative analyses addressing environmental health and safety, supply-chain risk, and ESG alignment indicate potential advantages related to occupational safety, regulatory compliance, waste management, and end-of-life recyclability. The investigation is performed on planar Aluminum 6061 reference surfaces with a treated area of 25 mm 2 , providing a controlled laboratory-scale basis for analyzing process behavior, functional surface modification, and associated environmental metrics. Within this defined scope, the results support further evaluation of femtosecond laser surface texturing as a surface engineering option for future aerospace manufacturing.

corrosion resistance↗

DOE OSTI2021

Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation

Abstract We consider the problem of learning the level set for which a noisy black-box function exceeds a given threshold. To efficiently reconstruct the level set, we investigate Gaussian process (GP) metamodels. Our focus is on strongly stochastic simulators, in particular with heavy-tailed simulation noise and low signal-to-noise ratio. To guard against noise misspecification, we assess the performance of three variants: (i) GPs with Student- t observations; (ii) Student- t processes (TPs); and (iii) classification GPs modeling the sign of the response. In conjunction with these metamodels, we analyze several acquisition functions for guiding the sequential experimental designs, extending existing stepwise uncertainty reduction criteria to the stochastic contour-finding context. This also motivates our development of (approximate) updating formulas to efficiently compute such acquisition functions. Our schemes are benchmarked by using a variety of synthetic experiments in 1–6 dimensions. We also consider an application of level set estimation for determining the optimal exercise policy of Bermudan options in finance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

On the emergent scale of bedrock groundwater contribution to headwater mountain streams

We investigated the contribution of bedrock groundwater to streamflow as a function of catchment scale in a headwater stream. Synoptic surveys were conducted during hydrologically important periods of the year using multiple environmental tracers in stream water, soil water, and bedrock groundwater, along a first-order montane stream, in west-central Montana. Sampled analytes included 222 Rn, used to constrain total subsurface flux, and major and minor elements, used in end-member mixing analysis (EMMA) to identify the contributions of soil and bedrock groundwater to the stream. Partitioning between soil-derived and bedrock-derived groundwater was then analyzed as a function of the incremental and accumulated sub-catchment sizes. Radon results indicated that subsurface water contributions accounted for the majority of streamflow at all surveyed times. EMMA results revealed that the bedrock groundwater contribution to streamflow varied between 26% during peak snowmelt and 44% during late summer. Streamflow generation was dominated by soil groundwater contribution along the entire reach, but the bedrock groundwater contribution increased consistently with accumulated sub-catchment size. However, groundwater contributions were not well-correlated with incremental sub-catchment size. The scale at which increased bedrock groundwater discharge can be correlated with sub-catchment size appears to be >1 km 2 for our study. Our results are consistent with a conceptual model where streamflow is predominantly generated by a 3D subsurface nested flow system. Local subsurface heterogeneities control the stream source at local scales but begin to average out at scales >2 km 2 . Our study indicates that, while soil groundwater is the dominant source, bedrock groundwater remains an important and predictable contributor to streamflow throughout the year, even in a snow-dominated, mountainous headwater catchment.

environmental tracers↗

DOE OSTI2025

Impact of U-10Mo HALEU fuel element tolerances on the Massachusetts Institute of Technology reactor safety and operational performance – Thermal hydraulics

The U.S. is coordinating efforts for the conversion of six U.S. High Performance Research Reactors (USHPRR) including one critical facility from highly enriched uranium (HEU) to low-enriched uranium (LEU). In order to continue the mission of these reactors, including the Massachusetts of Institute of Technology Reactor (MITR), and achieve similar performance, high-assay low-enriched uranium (HALEU) with a high-density metallic alloy of uranium with 10 wt% molybdenum (U-10Mo) is being evaluated. The impact of the fabrication specification and tolerances was assessed following the preliminary design of the MITR LEU fuel elements using the U-10Mo monolithic alloy. This research focuses on the analysis of fabrication specification impact on thermal hydraulics (TH) characteristic of the MITR LEU core as a function of the variation of the relevant fuel specification parameters (e.g., coolant channel gap thickness, fuel plate thickness, etc.). The analyses are performed based on an all-fresh LEU fuel conversion plan identified in a preliminary safety analysis report submitted to the Nuclear Regulatory Commission. The reactor power margin to the onset of nucleate boiling (ONB) is assessed under the limiting safety system settings (LSSS), where a scram occurs, to ensure there is sufficient margin to the reactor safety limit, which is defined by the onset of flow instability that occurs after the ONB. The best estimate plus uncertainty approach is employed to analyze this TH characteristic, which yields realistic results while maintaining adequate conservatism, utilizing a statistical uncertainty propagation method with the STAT7 code. The TH characteristic is analyzed as a function of the variability of the specification parameters resulting from the fabrication process. The main findings of this study show that the MITR core can meet the TH safety and operational requirements at the all-LEU initial core startup (cycle 1), selected transition cycles (most reactive cycle and most limiting cycle: cycle 3 and 5, respectively) and equilibrium (cycle 14) cores under all limiting fabrication parameter combinations considered. In addition, the analyses show that the dependency of the core power margin to ONB on those specification parameters that have the most direct impact on TH performance is non-linear but monotonically decreasing within the specification tolerances. The third order polynomial fit curves are reported in detail for selected limiting cases and can serve as a powerful tool for future MITR fuel management in cases such as when HALEU supply is established that may allow additional cycle length or other operational benefits.

Conversion↗

DOE OSTI2023

Improved quasiparticle self-consistent electronic band structure and excitons in β – LiGaO 2

The band structure of β–LiGaO 2 is calculated using the quasiparticle self-consistent QSGWˆ method where the screened Coulomb interaction Wˆ is evaluated including electron-hole interaction ladder diagrams and G is the one-electron Green's function. Improved convergence compared to previous calculations leads to a significantly larger band gap of about 7.0 eV. However, exciton binding energies are found to be large and lead to an exciton gap of about 6.0 eV if also a zero-point-motion correction of about –0.4 eV is included. Furthermore, these results are in excellent agreement with recent experimental results on the onset of absorption. Besides the excitons observed thus far, the calculations indicate the existence of a Rydberg-like series of exciton excited states, which is however modified from the classical Wannier exciton model by the anisotropies of the material and the more complex mixing of Bloch states in the excitons resulting from the Bethe-Salpeter equation. The exciton fine structure and the exciton wave functions are visualized and analyzed in various ways.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Isospin composition of fission barriers

We employ a microscopic method to study how isospin affects the fission potential of 240 Pu. Our approach uses constrained Hartree-Fock theory (CHF) which allows us to separately investigate the isoscalar and isovector properties of the nuclear energy density functional (EDF). By analyzing the isoscalar and isovector components of the EDF along the fission path we can assess the isovector contribution to fission barriers. Here, we study this effect for the fully adiabatic path to scission. The isovector component of the fission potential is found to increase in magnitude as the nucleus evolves towards scission, exemplifying the importance of stringent constraints on the isovector sector of the nuclear EDF for reliable predictions of fission properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Edge Segregated Polymorphism in 2D Molybdenum Carbide

Molybdenum carbide (Mo 2 C), a class of unterminated MXene, is endowed with rich polymorph chemistry, but the growth conditions of the various polymorphs are not understood. Other than the most commonly observed T-phase Mo 2 C, little is known about other phases. Here, Mo 2 C crystals are successfully grown consisting of mixed polymorphs and polytypes via a diffusion-mediated mechanism, using liquid copper as the diffusion barrier between the elemental precursors of Mo and C. By controlling the thickness of the copper diffusion barrier layer, the crystal growth can be controlled between a highly uniform AA-stacked T-phase Mo 2 C and a “wedding cake” like Mo 2 C crystal with spatially delineated zone in which the Bernal -stacked Mo 2 C predominate. The atomic structures, as well as the transformations between distinct stackings, are simulated and analyzed using density functional theory (DFT)-based calculations. Bernal -stacked Mo 2 C has a d band closer to the Fermi energy, leading to a promising performance in catalysis as verified in hydrogen evolution reaction (HER).

36 MATERIALS SCIENCE↗

DOE OSTI2025

Imaging Photonic Resonances within an All‐Dielectric Metasurface via Photoelectron Emission Microscopy

Dielectric metasurfaces, through volume‐type photonic resonances, enable precise control of light‐matter interactions for applications including imaging, holography, and sensing. The application space of dielectric metasurfaces has extended from infrared to visible wavelengths by incorporating high refractive index materials, such as titanium dioxide (TiO 2 ). Understanding the fundamental and fabrication limits for these applications requires metrology with nanoscale resolution, sensitivity to electromagnetic fields within the meta‐atom volume, and far‐field excitation. In this work, photoelectron emission microscopy (PEEM) is used to image field distributions of photonic resonances in a TiO 2 metasurface excited with far‐field, visible‐wavelength illumination. The local volumetric field variations within the meta‐atoms are analyzed as a function of illumination angle and polarization by comparing photoelectron images to finite‐difference time‐domain simulations. This study determines the inelastic mean free path of very low‐energy (<1 eV) photoelectrons to be 35 ± 10 nm, which is comparable to the meta‐atom height thereby highlighting PEEM sensitivity to resonances within the volume. Additionally, the simulations reveal high sensitivity of PEEM images to an in‐plane component of the illumination k ‐vector. These results demonstrate that photoelectron imaging with subwavelength resolution offers unique advantages for examining light‐matter interactions in volume‐type (as opposed to surface) photonic modes within dielectric nanophotonic structures.

electron inelastic mean free path↗

DOE OSTI2022

Jet energy spectrum and substructure in $e^+e^–$ collisions at 91.2 GeV with ALEPH Archived Data

The first measurements of energy spectra and substructure of anti-k T jets in hadronic Z 0 decays in e + e – collisions are presented. The archived e + e – annihilation data at a center-of-mass energy of 91.2 GeV were collected with the ALEPH detector at LEP in 1994. In addition to inclusive jet and leading dijet energy spectra, various jet substructure observables are analyzed as a function of jet energy which includes groomed and ungroomed jet mass to jet energy ratios, groomed momentum sharing, and groomed jet radius. The results are compared with perturbative QCD calculations and predictions from the Sherpa, Herwig v7.1.5, Pythia6, Pythia8 and Pyquen event generators. The jet energy spectra agree with perturbative QCD calculations which include the treatment of logarithms of the jet radius and threshold logarithms. None of the event generators give a fully satisfactory description of the data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Doping Effect of Fe Ions on the Structural, Electrical, and Magnetic Properties of SrTiO{sub 3} Nanoceramic Matrix

In the present investigation, strontium titanate nanoceramic was synthesized by incorporating iron (Fe) ion with general formula SrTi{sub 1−x}Fe{sub x}O{sub 3} (x = 0.0, 0.1, 0.2, and 0.4) using sol-gel autocombustion method. The effect of Fe ions on the structural, morphological, electrical, dielectric, and magnetic properties of the prepared matrix has been investigated by various characterization techniques with the appropriate formulation. The structural properties such as phase space, crystallite size (D), and lattice parameter (a) of prepared matrix are calculated by X-ray diffraction (XRD) technique. The functional groups were analyzed by Fourier transform infrared spectroscopy (FT-IR). The surface morphology of the prepared nanoceramic matrix has been determined by using field emission scanning electron microscopy (FE-SEM) analysis. Calculation of average particle size and diffraction patterns was confirmed by using images from transmission electron microscopy (TEM) and selected area electron diffraction pattern (SAED), respectively. An energy dispersive spectrum analysis (EDS) confirmed the compositional stoichiometry in the investigated matrix. Electrical conductivity increased the prepared sample due to the increasing in the Fe concentration and temperature. The dielectric parameters in the frequency range of 30 Hz to 1 MHz were found higher at lower frequencies. The pure SrTiO{sub 3} matrix shows a paramagnetic nature at room temperature, but for a higher concentration of Fe doping was used to observe the weak ferromagnetic nature. Therefore, due to Fe ion concentration, the properties of the prepared matrix have been completely varied and enhancement in the magnetic properties was observed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2019

Structural, Optical, Magnetic, and Dielectric Properties of Cr{sup 3+} Substituted Cobalt Aluminate Nanoparticles

The present study investigates the influence of Cr{sup 3+} substitution on structural, optical, dielectric, and magnetic properties of cobalt aluminates in the aluminates series CoAl{sub 2-x}Cr{sub x}O{sub 4}, 0.00 ≤ x ≤ 0.20. These series of nanoparticles are effectively synthesized using the co-precipitation method. The cubic spinel aluminate structure is confirmed by X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopic measurements. Transmission electron microscopy (TEM) analysis shows the formation of spherical nanoparticles, which are homogeneous in shape and size. The optical properties of the prepared samples have been investigated by means of optical absorbance spectra. The optical band gap E{sub opt}{sup i} and Urbach energy E{sub u} are estimated. At room temperature, the magnetization of undoped CoAl{sub 2}O{sub 4} reveals a weak ferromagnetic behavior. This ferromagnetism is increased for the sample with x = 0.05, and the samples with higher Cr{sup 3+} content have a tendency to be superparamagnetic on account of the formation of single-domain particles as a consequence of small particle size. Real part of dielectric constant (ε{sup ′}), dielectric loss (tanδ), ac conductivity (σ{sub ac}), real part of impedance (Z{sup ′}), and imaginary part of impedance (Z{sup ″}) are analyzed as a function of frequency and Cr{sup 3+} content. The results show that the dielectric loss (tanδ), dielectric permittivity (ε{sup ′}), and ac conductivity (σ{sub ac}) decrease with the increase in Cr{sup 3+} content, x = 0.05, and then increase with a further increase in Cr{sup 3+} content. The increase in these parameters has been explained on the basis of the hopping mechanism. From the Cole–Cole diagram, the value of the relaxation time τ can be calculated and it has been found to increase with increasing the Cr{sup 3+} content. Actually, a high dielectric constant makes these materials good for energy storage at high frequencies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

Origin of dislocation structures in an additively manufactured austenitic stainless steel 316L

In this experiment, the origin of dislocation structures in AM stainless steels was systematically investigated by controlling the effect of thermal stress through geometric constraints for the first time. Stainless steel 316L parts were produced in the form of “1D” rods, “2D” walls, and "3D" rectangular prisms to evaluate the effect of constraints to thermal expansion/shrinkage on the development of defect microstructures and to elucidate the origin of additively manufactured (AM) dislocation microstructures. Dislocation density, organization, chemical micro-segregation, precipitate structures, and misorientations were analyzed as a function of increasing constraints around solidifying material in 1D, 2D, and 3D components built using both directed energy deposition (DED) and powder-bed selective laser melting (SLM). In DED parts, the dislocation density was not dependent on local misorientations or micro-segregation patterns, but evolved from approximately ρ ⊥ = 10 12 m -2 in 1D parts to ρ ⊥ = 10 14 m -2 in 3D parts, indicating that it is primarily thermal distortions that produce AM dislocation structures. In DED 3D parts and SLM parts, dislocation densities were highest (ρ ⊥ ≈ 10 14 m -2 ) and corresponded to the formation of dislocation cells approximately 300-450 nm in diameter. Dislocation cells overlapped with dendrite micro-segregation in some but not all cases. The results illustrate that dendritic micro-segregation, precipitates, or local misorientations influence how the dislocations organize during processing, but are not responsible for producing the organized cell structures. Furthermore, this work shows that AM dislocation structures originate due to thermal distortions during printing, which are primarily dictated by constraints surrounding the melt pool and thermal cycling.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗