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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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At least 181 records · Page 10

Statistical analysis and degradation pathway modeling of photovoltaic minimodules with varied packaging strategies

Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power loss in these glass/backsheet PV minimodules. We show successful implementation of netSEM to elucidate the relationships between variables in PV systems and predict a specific service lifetime. The results from pairwise relationships and multiple regression show consistency. This work presents a greater opportunity to be expanded to other materials systems.

electrical measurements↗

Role of chemical production and depositional losses on formaldehyde in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM)

Abstract. Formaldehyde (HCHO) is an important air pollutant with direct cancer risk and ozone-forming potential. HCHO sources are complex because HCHO is both directly emitted and produced from oxidation of most gas-phase reactive organic carbon. We update the secondary production of HCHO in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) in the Community Multiscale Air Quality (CMAQ) model. Production of HCHO from isoprene and monoterpenes is increased, correcting an underestimate in the current version. Simulated June–August surface HCHO during peak photochemical production (11:00–15:00 LT, local time) increased by 0.6 ppb (32 %) over the southeastern USA and by 0.2 ppb (13 %) over the contiguous USA. The increased HCHO compares more favorably with satellite-based observations from the TROPOspheric Monitoring Instrument (TROPOMI) and from aircraft-based observations. Evaluation against hourly surface observations indicates a missing nighttime sink that can be improved by increased nighttime deposition, which reduces June–August nocturnal (20:00–04:00 LT) surface HCHO by 1.1 ppb (36 %) over the southeastern USA and 0.5 ppb (29 %) over the contiguous USA. The ability of CRACMM to capture peak levels of HCHO at midday is improved, particularly at sites in the northeastern USA, while peak levels at sites in the southeastern USA are improved, although still lower than observed. Using established risk assessment methods, lifetime exposure of the population in the contiguous USA (∼ 320 million) to ambient HCHO levels predicted here may result in 6200 lifetime cancer cases, with 40 % from controllable anthropogenic emissions of nitrogen oxides and reactive organic compounds. Chemistry updates will be available in CRACMM version 2 (CRACMM2) in CMAQv5.5.

Skipper, T. Nash↗

Oxidation Lifetime Modeling of 625 and 120 Foils After Long-term Exposure in Flowing Air + 10% ${\hbox {H}_2\hbox {O}}$ at 700 and 800 $^\circ$C

A model describing oxidation kinetics considering simultaneous oxidation and volatilization of external oxide scales was integrated with a CALPHAD-based coupled thermodynamic and kinetic approach to predict the oxidation-induced lifetime of foils of alloys 625 and 120. Long-term exposures in flowing air +10% H 2 O at 700 and 800 °C under two flow velocities were used to validate the modeling results. The time to a critical Cr concentration of 10 wt% at the oxide/alloy interface, t 10 , was shown to correlate with the breakdown of the Cr 2 O 3 scale for the studied experimental conditions. Finally, the modeling approach was extended to consider time-dependent oxidation and volatilization rate constants to develop a more appropriate lifetime criterion for microturbine recuperator foils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis

Abstract Point defects in hexagonal boron nitride (hBN) have attracted growing attention as bright single-photon emitters. However, understanding of their atomic structure and radiative properties remains incomplete. Here we study the excited states and radiative lifetimes of over 20 native defects and carbon or oxygen impurities in hBN using ab initio density functional theory and GW plus Bethe-Salpeter equation calculations, generating a large data set of their emission energy, polarization and lifetime. We find a wide variability across quantum emitters, with exciton energies ranging from 0.3 to 4 eV and radiative lifetimes from ns to ms for different defect structures. Through a Bayesian statistical analysis, we identify various high-likelihood charge-neutral defect emitters, among which the native V N N B defect is predicted to possess emission energy and radiative lifetime in agreement with experiments. Our work advances the microscopic understanding of hBN single-photon emitters and introduces a computational framework to characterize and identify quantum emitters in 2D materials.

Chemistry↗

Predicted Fracture Tendency of Naturally Occurring Aluminum Surface Coatings under Tensile Loading

Naturally occurring coatings on aluminum metal, such as its oxide or hydroxide, serve to protect the material from corrosion. Understanding the conditions under which these coatings mechanically fail is therefore expected to be an important aspect of predictive models for aluminum component lifetimes. To this end, we develop and apply a molecular dynamics (MD) modeling framework for conducting tension tests that is capable of isolating factors governing the mechanical strength as a function of coating chemistry, defect morphology, and variables associated with the loading path. We consider two representative materials, including γ-Al 2 O 3 and γ-Al(OH) 3 (i.e., oxide and hydroxide), both of which form readily as aluminum surface coatings. Our results indicate that defects have a significant bearing on the strength of aluminum oxide, with grain boundaries serving to reduce the strain at failure from ε zz = 0.300 to 0.219, relative to perfect single crystal. Our simulations also predict that porosity lowers the elastic stiffness and yield strength of the oxide. Relative to perfect crystal, we find porosity factors of 5%, 10% and 20% decrease the yield stress by 26%, 36% and 53%, respectively. MD predicts that perfect hydroxide and oxide single crystal have respective strains at failure of 0.08 and 0.31 under tensile uniaxial strain loading, and that the corresponding yield stresses are respectively 1.6 and 11.1 GPa. These data indicate that the hydroxide is substantially more susceptible to mechanical failure than the oxide. Our results, coupled with literature findings that indicate hot and humid conditions favor formation of hydroxide and defective oxide coatings, indicate the potential for a complicated dependence of aluminum corrosion susceptibility and stress corrosion cracking on aging history.

36 MATERIALS SCIENCE↗

CH 4 combustion over a commercial Pd/CeO 2 -ZrO 2 three-way catalyst: Impact of thermal aging and sulfur exposure

Thermal aging and sulfur poisoning are major problems influencing the efficiency and lifetime of natural gas three-way catalysts (TWCs) during real-world operation. In the present study, thermal aging and sulfur-induced deactivations on CH 4 combustion were investigated over commercial monolithic honeycombs, i.e., Pd/CexZr 1-x O 2 (CZ)-based TWCs that are thermally aged in the bench (HTA), followed by being operated behind the stoichiometric natural gas engine in high sulfur fuel (HTA + S). In this work, both HTA and HTA + S samples show degraded performance in CH 4 combustion relative to the fresh one, which are caused by the reconstruction of Pd species induced by thermal aging and the decreased reducibility of the support. The 18 O 2 labelling experiments show that in all cases CH 4 combustion proceeds via a MvK mechanism in which lattice O (OL) plays a key role. The sulfation aging (HTA + S sample) promotes the activation of CH 4 and O 2 by forming Pd δ+ -(SO$_4^{2-}$) δ- and Ce 3+ -VO couples at the interface as compared to HTA sample. However, such a promotion effect could be compromised by the blocking effect of sulfate on the exchange of O L from the bulk to the surface and across the surface. The fundamental understanding of thermal and S deactivation mechanisms from this study could help to predict a real-world lifetime use curve of natural gas TWCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Residually Stressed Bimaterial Beam Specimen for Measuring Environmentally Assisted Crack Growth

Background: Subcritical crack growth can occur in a brittle material when the stress intensity factor is smaller than the fracture toughness if an oxidizing agent (such as water) is present at the crack tip. Objective: Here we present a novel bi-material beam specimen which can measure environmentally assisted crack growth rates. The specimen is “self-loaded” by residual stress and requires no external loading. Methods: Two materials with different coefficient of thermal expansion are diffusion bonded at high temperature. After cooling to room temperature a subcritical crack is driven by thermal residual stresses. A finite element model is used to design the specimen geometry in terms of material properties in order to achieve the desired crack tip driving force. Results: The specimen is designed so that the crack driving force decreases as the crack extends, thus enabling the measurement of the crack velocity versus driving force relationship with a single test. The method is demonstrated by measuring slow crack growth data in soda lime silicate glass and validated by comparison to previously published data. Conclusions: The self-loaded nature of the specimen makes it ideal for measuring the very low crack velocities needed to predict brittle failure at long lifetimes.

36 MATERIALS SCIENCE↗

Photoionization of seeded combustion products as a method of enhancing the efficiency of magnetohydrodynamic power generators

Here, in this study, we performed an experimental and computational investigation into the feasibility of utilizing photoionization to enhance the electrical conductivity of seeded oxy-fuel combustion products and improve the performance of magnetohydrodynamic (MHD) power generators. We applied a variety of optical and microwave diagnostics to study the ionization and recombination processes of potassium excited by an excimer laser in a high-velocity oxy-fuel free jet. Computational fluid dynamic (CFD) simulations were performed to model the thermophysical properties and species densities of the free jet. The CFD results were validated with position-dependent potassium concentration measurements. Electron recombination exponential lifetimes were measured through time-resolved microwave transmission. The experimental electron lifetimes were compared with lifetimes calculated from CFD-predicted species densities and literature recombination rates. It was determined that K + or O 2 are the most likely recombination partners for photoionized electrons. Time-resolved fluorescence measurements provided evidence of an ionization pathway involving a two-photon ionization of KOH . Finally, a zero-dimensional chemical kinetic model was developed to assess the fundamental viability of inducing a non-equilibrium electron population to provide a net energy return in combustion-driven MHD power generators. We determined that a high energy return is feasible for targeting electrode boundary layers with ultraviolet photoionization. We also found that photoionization could potentially lower the required temperature of the bulk gas flow.

20 FOSSIL-FUELED POWER PLANTS↗

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

3D Frequency Domain Reflectometry Digital Twin of an Electrical Cable: A First Glance

Electrical cables within nuclear power plants (NPPs) are critical components required for power, control, and instrumentation systems which may be exposed to stressors, such as elevated temperatures and gamma radiation. Such stressors can lead to a reduction in the remaining useful life of electrical cables, jeopardizing the safety of NPP systems. To evaluate the effect of stressors on the degradation of electrical cables, electrical reflectometry methods are commonly employed. Frequency domain reflectometry (FDR) is a non-destructive electrical reflectometry method that uses transmission line theory to detect degradation or impedance changes within electrical cables. However, in most cases FDR is only applied to de-energized cables, limiting the application in NPPs as the cable system must be taken offline. In this work, we explore the development of an FDR digital twin to predict the degradation of an electrical cable exposed to elevated temperature, which is expected to reduce the need for offline FDR. A 3-conductor low-voltage electrical cable was selected for evaluation of the digital twin. The fully three-dimensional digital twin was developed in COMSOL using the RF module. A cable length of 30-m and frequency bandwidth of 400 MHz was selected to mimic real-world application of FDR. Over a 1-m region, the permittivity of the insulation was varied by up to 20% to model thermal degradation. The results demonstrate accurate detection of the insulation damage region, supporting further investigation of the FDR digital twin using real-world data and machine learning for predictive damage estimation or remaining lifetime.

Spencer, Mychal P.↗

Effect of random antiferromagnetic exchange on the spin waves in a three-dimensional Heisenberg ferromagnet

Neutron scattering is used to study spin waves in the three-dimensional Heisenberg ferromagnet YTiO 3 , with spin-spin exchange disorder introduced via La substitution at the Y site. No significant changes are observed in the spin-wave dispersion up to a La concentration of 20%. However, a strong broadening of the spectrum is found, indicative of shortened spin-wave lifetimes. Density-functional theory calculations predict minimal changes in exchange constants as a result of average structural changes due to La substitution, in agreement with the data. The absence of significant changes in the spin-wave dispersion, the considerable lifetime effect, and the reduced ordered magnetic moment previously observed in the La-substituted system are qualitatively captured by an isotropic, nearest-neighbor, three-dimensional Furthermore, Heisenberg ferromagnet model with random antiferromagnetic exchange. We therefore establish Y 1-$x$ La $x$ TiO 3 as a model system for the study of antiferromagnetic spin-exchange disorder in a three-dimensional Heisenberg ferromagnet.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Neutron Mean Life and Big Bang Nucleosynthesis

We explore the effect of neutron lifetime and its uncertainty on standard big bang nucleosynthesis (BBN). BBN describes the cosmic production of the light nuclides, 1H, D, 3H+3He, 4He, and 7Li+7Be, in the first minutes of cosmic time. The neutron mean life τn has two roles in modern BBN calculations: (1) it normalizes the matrix element for weak n↔p interconversions, and (2) it sets the rate of free neutron decay after the weak interactions freeze-out. We review the history of the interplay between τn measurements and BBN, and present a study of the sensitivity of the light element abundances to the modern neutron lifetime measurements. We find that τn uncertainties dominate the predicted 4He error budget, but these theory errors remain smaller than the uncertainties in 4He observations, even with the dispersion in recent neutron lifetime measurements. For the other light element predictions, τn contributes negligibly to their error budget. Turning the problem around, we combine present BBN and cosmic microwave background (CMB) determinations of the cosmic baryon density to predict a “cosmologically preferred” mean life of τn(BBN+CMB)=870±16s, which is consistent with experimental mean life determinations. We show that if future astronomical and cosmological helium observations can reach an uncertainty of σobs(Yp)=0.001 in the 4He mass fraction Yp, this could begin to discriminate between the mean life determinations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit

Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.

97 MATHEMATICS AND COMPUTING↗

Impact of classical statistics on thermal conductivity predictions of BAs and diamond using machine learning molecular dynamics

Machine learning interatomic potentials (MLIPs) have greatly enhanced molecular dynamics (MD) simulations, achieving near-first-principles accuracy in thermal conductivity studies. In this work, we reveal that this accuracy, observed in BAs and diamond at sub-Debye temperatures, stems from an accidental error cancelation: classical statistics overestimates specific heat while underestimating phonon lifetimes, balancing out in thermal conductivity predictions. However, this balance is disrupted when isotopes are introduced, leading MLIP-based MD to significantly underpredict thermal conductivity compared to experiments and quantum statistics-based Boltzmann transport equation. This discrepancy arises not from classical statistics affecting phonon–isotope scattering rates but from its impact on the interplay between phonon–isotope and phonon–phonon scattering in the normal scattering-dominated BAs and diamond. In conclusion, this work underscores the limitations of MLIP-based MD for thermal conductivity studies at sub-Debye temperatures.

36 MATERIALS SCIENCE↗

Stabilizing and Improving Qubit Coherence by Engineering the Noise Spectrum of Two-Level Systems

Superconducting circuits are a leading platform for quantum computing. However, their coherence times are still limited and exhibit temporal fluctuations. Those phenomena are often attributed to the coupling between qubits and material defects that can be well described as an ensemble of two-level systems (TLSs). Among them, charge fluctuators inside amorphous oxide layers contribute to both low-frequency 1 / f charge noise and high-frequency dielectric loss, causing fast qubit dephasing and relaxation. Moreover, spectral diffusion from mutual TLS interactions varies the noise amplitude over time, fluctuating the qubit lifetime. Here, we propose to mitigate those harmful effects by engineering the relevant TLS noise spectral densities. Specifically, our protocols smooth the high-frequency noise spectrum and suppress the low-frequency noise amplitude via depolarizing and dephasing the TLSs, respectively. As a result, we predict a drastic stabilization in qubit lifetime and an increase in qubit pure dephasing time. Our detailed analysis of feasible experimental implementations shows that the improvement is not compromised by spurious coupling from the applied noise to the qubit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effect of Measurement Temperature on Electrical Cable Frequency Domain Reflectometry Response

In nuclear power plants, electrical cables are exposed to stressors, such as elevated temperature and radiation. Evaluation of the effect of stressors on the lifetime of electrical cables can be conducted using offline electrical reflectometry techniques, such as frequency domain reflectometry (FDR). However, recent work has raised the concern that FDR measurements at temperatures higher than ambient may diminish or reduce the response due to stressors, potentially leading to incorrect predictions of electrical cable damage and lifetime. In this work, we explore the FDR response of an electrical cable exposed to an oven-based thermal stressor up to 140°C, including both ramping up and ramping down temperature. It was observed that, for both the oven entrance and exit, an increase in the FDR measurement temperature led to a decrease in the FDR reflection coefficient. In particular, it was found that the reflection coefficient at the oven entrance decreased from the ambient measurement by approximately 7%, 22%, and 36% at a temperature of 60°C, 100°C, and 140°C, respectively.

Spencer, Mychal P.↗

Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes

Differential epidermal growth factor receptor (EGFR) phosphorylation is thought to couple receptor activation to distinct signaling pathways. However, the molecular mechanisms responsible for biased signaling are unresolved due to a lack of insight into the phosphorylation patterns of full-length EGFR. We extended a single-molecule pull-down technique previously used to study protein–protein interactions to allow for robust measurement of receptor phosphorylation. We found that EGFR is predominantly phosphorylated at multiple sites, yet phosphorylation at specific tyrosines is variable and only a subset of receptors share phosphorylation at the same site, even with saturating ligand concentrations. We found distinct populations of receptors as soon as 1 min after ligand stimulation, indicating early diversification of function. To understand this heterogeneity, we developed a mathematical model. The model predicted that variations in phosphorylation are dependent on the abundances of signaling partners, while phosphorylation levels are dependent on dimer lifetimes. The predictions were confirmed in studies of cell lines with different expression levels of signaling partners, and in experiments comparing low- and high-affinity ligands and oncogenic EGFR mutants. These results reveal how ligand-regulated receptor dimerization dynamics and adaptor protein concentrations play critical roles in EGFR signaling.

59 BASIC BIOLOGICAL SCIENCES↗

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗