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At least 145 records · Page 8

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DOE OSTI2023

Proton-Conducting Solid Oxide Electrolysis Cells for Large-scale Hydrogen Production at Intermediate Temperatures

Proton-conducting electrolyte based SOECs offer potential for operation at low to intermediate temperatures. Although yttrium-doped barium zirconate (BZY) and ceria-doped barium zirconate (BCY) have conductivity of 0.01 and 0.017 S.cm -1 respectively at 650C in comparison to the conductivity of 0.015 S.cm -1 for 8-YSZ at 850°C, there remains technology gaps and research needs related to understanding of chemical and structural stability in oxidizing and/or reducing atmospheres at intermediate temperatures, material processing and densification techniques, high polarization losses, and electrode poisoning due to intrinsic and extrinsic gas phase contaminants. Synthesis methods have produced proton-conducting materials and cells that met degradation rate targets, showcasing stable hydrogen production. Improved performance was evident in the HSOEC cell, achieving higher hydrogen production at a lower operating temperature compared to standard cells. Collaborations with multiple research facilities ensured scaling up of synthesis processes and milestone achievements for large-scale manufacturing. Assessment of contaminants revealed their adverse effects on electrode performance and structural stability. Contaminants like Cr and Si compounds, in high humidity, degraded electrodes by forming stable silicate and chromates, inhibiting active surface reactions. Getter materials showed promise in capturing contaminants, suggesting potential for mitigation.

08 HYDROGEN↗

DOE OSTI2022

Understanding of bacterial lignin extracellular degradation mechanisms by Pseudomonas putida KT2440 via secretomic analysis

Abstract Background Bacterial lignin degradation is believed to be primarily achieved by a secreted enzyme system. Effects of such extracellular enzyme systems on lignin structural changes and degradation pathways are still not clearly understood, which remains as a bottleneck in the bacterial lignin bioconversion process. Results This study investigated lignin degradation using an isolated secretome secreted by Pseudomonas putida KT2440 that grew on glucose as the only carbon source. Enzyme assays revealed that the secretome harbored oxidase and peroxidase/Mn 2+ -peroxidase capacity and reached the highest activity at 120 h of the fermentation time. The degradation rate of alkali lignin was found to be only 8.1% by oxidases, but increased to 14.5% with the activation of peroxidase/Mn 2+ -peroxidase. Gas chromatography–mass spectrometry (GC–MS) and two-dimensional 1 H– 13 C heteronuclear single-quantum coherence (HSQC) NMR analysis revealed that the oxidases exhibited strong C–C bond ( β-β , β -5, and β -1) cleavage. The activation of peroxidases enhanced lignin degradation by stimulating C–O bond ( β -O-4) cleavage, resulting in increased yields of aromatic monomers and dimers. Further mass spectrometry-based quantitative proteomics measurements comprehensively identified different groups of enzymes particularly oxidoreductases in P. putida secretome, including reductases, peroxidases, monooxygenases, dioxygenases, oxidases, and dehydrogenases, potentially contributed to the lignin degradation process. Conclusions Overall, we discovered that bacterial extracellular degradation of alkali lignin to vanillin, vanillic acid, and other lignin-derived aromatics involved a series of oxidative cleavage, catalyzed by active DyP-type peroxidase, multicopper oxidase, and other accessory enzymes. These results will guide further metabolic engineering design to improve the efficiency of lignin bioconversion. Graphical Abstract

09 BIOMASS FUELS↗

DOE OSTI2021

Carbonyl Identification and Quantification Uncertainties for Oxidative Polymer Degradation

The most revealing indicator for oxidative processes or state of degraded plastics is usually carbonyl formation, a key step in materials degradation as part of the carbon cycle for man-made materials. Hence, the identification and quantification of carbonyl species with infrared spectroscopy have been the method of choice for generations, thanks to their strong absorbance and being an essential intermediate in carbon oxidation pathways. Despite their importance, precise identification and quantification can be challenging and rigorous fully traceable data are surprisingly rare in the existing literature. An overview of the complexity of carbonyl quantification is presented by the screening of reference compounds in solution with transmission and polymer films with ATR IR spectroscopy, and systematic data analyses. Significant variances in existing data and their past use have been recognized. Guidance is offered how better measurements and data reporting could be accomplished. Experimental variances depend on the combination of uncertainty in exact carbonyl species, extinction coefficient, contributions from neighboring convoluting peaks, matrix interaction phenomena and instrumental variations in primary IR spectral acquisition (refractive index and penetration depth for ATR measurements). In addition, diverging sources for relevant extinction coefficients may exist, based on original spectral acquisition. For common polymer degradation challenges, a relative comparison of carbonyl yields for a material is easily accessible, but quantification for other purposes, such as degradation rates and spatially dependent interpretation, requires thorough experimental validation. All variables featured in this overview demonstrate the significant error margins in carbonyl quantification, with exact carbonyl species and extinction coefficients already being major contributors on their own.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Ferroelastic Hysteresis in Thin Films of Methylammonium Lead Iodide

Mechanical strain can modify the structural and electronic properties of methylammonium lead iodide MAPbI 3 . The consequences of ferroelastic hysteresis, which involves the retention of structural memory upon cycles of deformation, are reported for polycrystalline thin films of MAPbI 3 . Repeatedly bent films were examined using grazing incidence wide-angle X-ray scattering (GIWAXS) to quantitatively characterize the strains and proportions of twin domains. Approximate locations for the coercive stress and saturation on the ferroelastic stress–strain curve are identified, and changes to the stress–strain curve with cyclic strain are characterized. Notably, an external stress source, such as thermal stress from the substrate or a roll-to-roll printing setup, must apply at least |50| MPa to modify the proportions of different twins. The presence of specific twin domains is found to correlate to previously reported strain and defect heterogeneity in MAPbI 3 films. Domains from differently strained twin sets interact with each other. Long-term stability testing reveals that the domain walls are highly immobile over extended periods. Nucleation of new domain walls occurs for specific mechanical strains and correlates closely with degradation. Furthermore, these results help to explain the behavior of ion migration, degradation rate, and photoluminescence in thin films under compressive and tensile strain.

Defects↗

DOE OSTI2023

Degradation of Monocrystalline Silicon Photovoltaic Modules From a 10-Year-Old Rooftop System in Florida

A system of 180 monocrystalline aluminum back-surface field modules were installed in Cocoa, Florida, for 10 years. In total, 156 modules are characterized and compared to 3 controls. Power degradation rates vary between – 0.14% to – 3.22% per year, with median and average rates of –0.92% and –1.05% per year, respectively. The losses are primarily resistive with minor optical and recombination loss contributions. Electroluminescence imaging shows a characteristic pattern, which is shown to be resistive in nature when compared to photoluminescence. Resistive losses are due to corrosion of the rear contact Ag/solder interface and, to a much lesser degree, gridline Ag oxidation. Moisture ingress through the backsheet is likely responsible for mediating corrosion. Optical losses are due mostly to a combination of antireflection coating degradation, minor encapsulant browning, and delamination. Minor front contact corrosion may contribute to recombination. Furthermore, this study expands upon previous work on this vintage of the module by examining a large sample set, comprehensive characterization including techniques not previously used on these modules, and a comparison between two other systems of different climates.

14 SOLAR ENERGY↗

DOE OSTI2023

Towards linking lab and field lifetimes of perovskite solar cells

Metal halide perovskite solar cells (PSCs) represent a promising low-cost, thin-film photovoltaic (PV) technology, with unprecedented power conversion efficiencies (PCEs) obtained for both single-junction and tandem applications. To push PSCs toward commercialization, it is critical, albeit challenging, to understand device reliability under real-world outdoor conditions where multiple stress factors (e.g., light, heat, humidity) coexist, generating complicated degradation behaviors. It is necessary to identify accelerated indoor testing protocols - which can correlate specific stressors with observed degradation modes in fielded devices - to quickly guide PSC development. Here, we use a state-of-the-art p-i-n PSC stack (with PCE up to ~25.5%) to show that indoor accelerated stability tests can predict our 6-month outdoor aging tests. Device degradation rates under illumination and at elevated temperatures are most instructive for understanding outdoor device reliability. Further, we also find that the indium tin oxide (ITO)/self-assembled monolayer (SAM)-based hole transport layer (HTL)/perovskite interface most strongly affects our device operation stability. Improving the ion-blocking properties of the SAM HTL increases averaged device operational stability at 50 degree C-85 °C by a factor of ~2.8, reaching over 1000 h at 85 °C and to near 8200 h at 50 °C with a projected 20% degradation, which is among the best to date for high-efficiency p-i-n PSCs.

14 SOLAR ENERGY↗

DOE OSTI2020

System-level performance and degradation of 21 GWDC of utility-scale PV plants in the United States

We assess the performance of a fleet of 411 utility-scale (i.e., >5 MWAC and ground-mounted) photovoltaic (PV) projects totaling 21.1 GWDC (16.3 GWAC) of capacity, which achieved commercial operations in the United States from 2007 to 2016. This fleet of projects contributed more than 50% of all solar electricity generated in the United States in 2017. Using detailed information on individual project characteristics, in conjunction with modeled irradiance data, we assess the extent to which actual first-year performance has lived up to both modeled and stated expectations. We then analyze system-level performance degradation in subsequent years by employing a “fixed effects” regression model to statistically isolate the impact of age on system performance. We find that this fleet of utility-scale PV projects has generally lived up to ex ante expectations for first-year performance but that subsequent system-level degradation—found to be −1.3%/year (±0.2%)—has, on average, been worse than both ex ante expectations (commonly −0.5%/year) and results from past studies (ranging from −0.8%/year to −1.0%/year). We emphasize that −1.3%/year is a system-level estimate that captures more than just module degradation (e.g., including soiling, balance of plant degradation, and downtime for maintenance and/or other events). A side analysis of a variety of project characteristics suggests that system-level degradation rates tend to be of lower magnitude among newer projects and larger projects and at sites with lower long-term average temperatures.

14 SOLAR ENERGY↗

DOE OSTI2024

Aging Mechanisms of Broad Area ~800 nm Laser Diodes

Here, this work presents a comprehensive study of early aging behavior (<500 hr) in ~800 nm, phosphide-based laser diodes grown by solid-source MBE with different oxygen concentration levels incorporated into the diode epitaxial layers during growth. The data indicate that lasing characteristics prior to aging are degraded by oxygen introduction, but the gradual power degradation rate after the onset of aging is not a strong function of oxygen at these concentration levels. Devices with oxygen concentrations of ~2.5 × 10 15 cm -3 showed significantly longer delay before the onset of aging (incubation time) than devices with less than 1 × 10 15 cm -3 oxygen. Generation-Recombination current and Laser Beam Induced Current measurements indicate that defect densities and aggregation are suppressed at the facets by oxygen, which can explain longer incubation times. Diagnostic data and parametric fits to diode simulation models show that increased cavity optical loss and defect density are primarily responsible for gradual power degradation during aging, rather than changes in nonradiative recombination. Mechanisms are proposed that explain this behavior, based on density functional theory (DFT) simulations and known recombination-enhanced defect generation phenomena.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Compilation of a Solar Mirror Materials Database and an Analysis of Natural and Accelerated Mirror Exposure and Degradation

The National Renewable Energy Laboratory (NREL) has been conducting exposure experiments on solar reflectors for over four decades. Thousands of mirror samples from over one hundred suppliers have been exposed to and monitored in a range of relevant environments. These test conditions include outdoor test settings and several controlled laboratory environments. These samples have been rigorously individually characterized using a series of reflectance measurements, visual inspections, and in some cases, in-depth composition analysis to identify degradation modes, reflectance losses, and other mirror properties integral to understanding the solar reflector's life cycle. Here, this paper compiles the decades of measurement data into a concise statistical analysis. It includes exposure and degradation data for numerous reflector types, including secondary-surface reflector permutations of polymer and glass superstrates with silver and aluminum reflectors as well as front-surface reflectors. The results herein are intended to analyze environmental stressors and degradation trends among various historical and state-of-the-art solar reflectors. It may be used to support solar reflector design, effective testing methodology, and inform manufacturing decisions moving forward. Presented are the results of the compiled database and an initial analysis for degradation rate modeling using full-spectrum and wavelength-dependent approaches. The database is a growing resource hosted on a live, publicly accessible website. In conjunction with the analysis presented here, it provides a valuable resource to the solar reflector manufacturing and testing industry.

14 SOLAR ENERGY↗

DOE OSTI2025

Environmental degradation testing of Alloy 709

Alloy 709 is an advanced austenitic stainless steel developed to meet the demanding conditions of sodium fast reactors (SFRs) but may also be of use for lead fast reactors, high temperature gas reactors, and molten salt reactors. Understanding environmental degradation modes and quantifying degradation rates are crucial to ensure the long-term, reliable operation of these reactors. This paper discusses recent neutron irradiation results, future neutron irradiation test plans, and sodium corrosion testing to communicate current best understanding of the performance of Alloy 709 in SFR environments.

A709↗

DOE OSTI2020

Shape-Selective Mesoscale Nanoarchitectures: Preparation and Photocatalytic Performance

We create ordered arrays of shape-selective gold-titania composite nanomaterials at the mesoscale (100 µm to 5 mm) by a combination of both bottom-up and top-down approaches for exquisite control of the size, shape, and arrangement of nanomaterials. Lithographic techniques along with wet chemical synthetic methods were combined to create these composite nanomaterials. The photocatalytic activity of these TiO 2, TiO 2 -Au and SiO 2 -TiO 2 -Au nano-composite mesoscale materials was monitored by the photodegradation of a model analyte, methyl orange, under UV and visible (Vis) illumination. Bare TiO 2 - and SiO 2 -TiO 2 -coated pillar arrays showed significant activity toward methyl orange in UV light with degradation rates on the order of 10 −4 –10 −3 min −1 . The photocatalytic activity of these arrays was also found to depend on the nanoparticle shape, in which particles with more edges and corners were found to be more reactive than spherical particles (i.e., the photocatalytic activity decreased as follows: diamonds > squares > triangles > spheres). SiO 2 -TiO 2 -Au nano-composite pillar arrays were tested in both UV and Vis light and showed increased activity in Vis light but decreased activity in UV light as compared to the bare semiconductor arrays. Additionally, the Au nanorod-functionalized nanoarrays exhibit a strong shape-dependence in their photocatalytic activity toward methyl orange degradation in Vis light.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.

backsheet↗

DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Fault Characterization and Diagnostics Supporting Condition-Based Operation and Maintenance of Gas Turbine Engines

Condition-Based Operation and Maintenance (CBOM) is the state-of-the-art in maintenance approaches for gas turbine engines. CBOM applies engine sensor information to the optimization of future operation and maintenance procedures; this technique reduces costs for engine operators by minimizing unplanned outages and catastrophic engine degradation. However, due to the complexities of gas turbine operation and the lack of available engine sensors, further development is required to fully realize the benefits of CBOM. In the turbine section, rotating components interact with high temperature flows, which creates intense thermal and mechanical stresses. As a result, there are numerous mechanisms of component degradation in the turbine section. Furthermore, turbine components – like stator vanes and rotor blades – are among the most expensive in the engine because they are complex to design and manufacture. For these reasons, this dissertation addresses two main questions: (i) which parameters or faults within the turbine section are most important to monitor, and (ii) how can these parameters or faults be monitored in an engine-relevant environment? Although many turbine parameters and faults have been investigated in the open literature, there are some faults that are still not well understood. Rotor-casing eccentricity, which causes a non-constant blade tip clearance around the annulus, has not been investigated in terms of its effects on turbine efficiency. Therefore, the first study in this dissertation quantifies overall and local turbine efficiency for varying levels of rotor-casing eccentricity. Results showed negligible variations to overall turbine efficiency, meaning rotor-casing eccentricity only becomes relevant to CBOM when its severity causes rotordynamic issues. Purge flow is critical to turbine hardware longevity because it prevents ingestion of hot main gas path (MGP) flow into the under-platform regions. Despite its importance, there are currently no methods for monitoring purge flow performance in an engine environment. Therefore, the second study in this dissertation develops a predictive model for sealing effectiveness using inputs from two fast-response pressure sensors. Results exhibited low prediction errors across a full range of purge flow rates, which supports the viability of the modelling approach for CBOM. The final two studies in this dissertation address blade coolant flow monitoring. This cooling flow is responsible for protecting the turbine blades from the MGP flow, which exits the combustor at temperatures greater than the blade melting point. These studies showed that temperature measurements on the blade surface can be used to accurately predict blade coolant flow rate, and that defining the candidate features relative to the coolant trajectory is important for maintaining accuracy as coolant flow rate degradation occurs. This work enables blade coolant flow monitoring, which is currently not possible through existing condition monitoring techniques.

condition-based, gas turbines, diagnostics,↗

DOE OSTI2025

PV Fleet Performance Data Initiative Final Technical Report (FTR)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. This project will leverage data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Please see our list of public reports at https://www.nrel.gov/pv/fleet-performance-data-initiative.html. Objective 1: Support the global PV industry with scalable, robust data analysis tools that reduce the uncertainty of PV system performance and loss calculation. Objective 2: Reduce perceived risk arising from degradation rate, soiling loss, and system availability by publishing detailed statistics on U.S. fleet performance. Objective 3: Highlight factors leading to system underperformance including module type, climate, mounting configuration, etc. Objective 4: Enable continued high system performance in modern PV systems, as turnover and advances in technology bring new suppliers and high-efficiency modules into the market.

14 SOLAR ENERGY↗

DOE OSTI2024

A high-performance intermediate temperature reversible solid oxide cell with a new barrier layer free oxygen electrode

The best solution to address the critical durability issue of solid oxide electrolytic cells (SOECs) for high-efficiency and high-rate H 2 production is to lower the operating temperature without sacrificing the performance. Developing high performance oxygen electrodes (OEs) is a key to capitalizing this solution. Here, in this paper, we report on a highly active OE for intermediate temperature ZrO 2 -based SOECs without a CeO 2 barrier layer. The new barrier-layer-free (BLF) OE is a composite of two materials, (Bi 0.75 Y 0.25 ) 0.93 Ce 0.07 O 1.5±δ (BYC) that exhibits high oxide-ion conductivity and La 0.8 Sr 0.2 MnO 3 (LSM) that possesses a high electronic conductivity to enable fast oxygen reduction/evolution reactions (ORR/OER). Featuring a microscale porous BYC scaffold decorated with high surface area LSM nanoparticles (NPs), the new BLF-OE exhibited a low area specific resistance (ASR) of 0.10 Ω cm 2 at 650 °C in air. With 50%H 2 -50%H 2 O as a feed to hydrogen electrode (HE) and air to OE, the single cell performance achieved 588 mA cm -2 at 0.80 V in the fuel cell mode and 688 mA cm -2 at 1.30 V in the electrolytic mode at 650 °C. Our in-house testing showed that this level of performance was ~3.5x higher than the cell with the benchmark La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ -Ce 0.9 Gd 0.1 O 2-δ OE. The long-term durability testing under alternating fuel cell and electrolytic modes showed a low degradation rate of 0.10 mA cm -2 h -1 over 550 hours. These encouraging results showed the great promise of the newly developed BYC-LSM to be an excellent OE candidate for intermediate temperature SOECs.

25 ENERGY STORAGE↗

DOE OSTI2024

Towards 50 Year Lifetime PV Modules: Double Glass vs. Glass/Backsheet

This award aims to increase the lifetime of c-Si modules by lowering the power degradation rate to the goal of 0.2 %/year, while also increasing the harvested irradiance per module using bifacial cells to achieve the 2030 SunShot goal of $0.03/kWh. Increasing the durability and lifetime of modules requires improved module packaging material choices and module architectures to exploit new cell improvements. Bifacial PERC cells (with backside aluminum fingers) are becoming a primary PV technology due to their decreased rear surface recombination and increased light absorption compared to traditional monofacial Al-BSF cells. Bifacial modules with double glass architectures have been deployed to capture the rear-side irradiance thereby increasing the light captured. The choice of a double glass (DG) or glass/backsheet (GB) module leads to two very different chemical (e.g., O 2 , H 2 O) and mechanical environments (e.g., mechanical stress levels) inside the PV module that impact the cell’s operational conditions. The recipient will fabricate 4-cell DG and GB minimodules with various module architectures or constructions (mono- & bifacial cells, transparent & white encapsulants), and conduct stepwise accelerated exposures and characterization.

14 SOLAR ENERGY↗

DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗