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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deployment and performance of a Low-Energy-Threshold Skipper-CCD inside a nuclear reactor

Charge Coupled Devices (CCD) are being used for reactor neutrino experiments and have already demonstrated their potential in constraining new physics models. The prospect of a Skipper-CCD experiment looking for standard and beyond standard model (BSM) physics in a nuclear reactor has been evaluated for different benchmark scenarios. Here, we report the first installation of a 2-g Skipper-CCD inside the containment building of a 2 GW th nuclear power plant and analyze its performance throughout its first 18 months of operation. The sensor was successfully deployed at Atucha II, in Argentina, 12 meters away from the center of the reactor core. We discuss the challenges involved in the commissioning of the detector and present data acquired during reactor ON and reactor OFF periods, with the sensor functioning with a sub-electron readout noise of 0.17 e - . Based on an exposure of 56.8 g day reactor ON and two reactor OFF data sets with a total exposure of 118.1 g day we characterize the system and evaluate the sensitivity to CEvNS. We achieved a background rate of 33 kdru and a low threshold of 45 eV ee . The ongoing efforts to improve sensitivities to CEvNS and BSM interaction are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Dynamic changes in dissolved organic matter composition in a Mountain Lake under ice cover and relationships to changes in nutrient cycling and phytoplankton community composition

We studied Bear Lake, a sub-alpine oligotrophic lake in Rocky Mountain National Park, Colorado U.S.A, during the winter ice cover period of 2018. Our goal was to understand relationships between biogeochemical processes and the chemical quality of the dissolved organic matter, a major pool of organic carbon in all lakes. The lake exhibited a highly stratified environment with limited light availability, a consistent oxycline at 7 meters, and dilute hydrochemistry. Nutrient concentrations were low and depletion of nitrogen, particularly for NH4 to a lesser extent NO3, were related to increasing phytoplankton abundance. The deep chlorophyll maxima that developed above the oxycline was dominated by a potentially mixotrophic dinoflagellate. DOM chemical quality as measured through high-resolution mass spectrometry was related to these shifts in aquatic ecosystem structure. However, CDOM spectroscopy of the whole water was a poor indicator of biogeochemical changes in the DOM pool. The spectrometry data highlighted an evolving and contrasting reservoir of phosphorus, nitrogen, and sulfur-containing organic compounds sensitive to nutrient cycling and redox conditions. We also observed reduced chemodiversity between the surface and bottom water DOM molecular formulas over time. Homogeneity increased in the surface and more unique compounds were produced in the bottom waters, where an overall increase occurred in the favorability of carbon to support microbial respiration. Our results show dynamic chemical changes in the DOM pool reflect dynamic nutrient cycling under ice cover, potentially driven by mixotrophic growth of the dinoflagellate Gymnodinium sp.

Rue, Garrett↗
DOE OSTI2025

Characterization of the fractal dimension of helium plumes in laminar to turbulent transition

Abstract Schlieren imaging in conjunction with a high-speed camera was used to observe the behavior of metered helium plumes as they transition from laminar to turbulent flow in an air environment. The plumes were visualized at twelve jet Reynolds numbers ranging from 200 to 2980. The fractal dimension of the flows was obtained by applying a box counting algorithm to the recorded schlieren images. The results were analyzed to determine the correlation between the Reynolds number of the flow and the fractal dimension of the observed turbulence. A trend of increasing fractal dimension with increasing Reynolds number was observed for several different types of schlieren cutoffs including horizontal cutoff, vertical cutoff, circular cutoff, focused shadowgraphy and de-focused shadowgraphy. The vertical cutoff and focused shadowgraphy imaging methods showed the most consistent results for the fractal dimension characterization during the laminar to turbulent transition. For transitional plumes, it was observed that fractal dimension increased with distance from the jet outlet.

42 ENGINEERING↗
DOE OSTI2025

Active Divertor Heat Flux Control using Impurity Powder Dropper

Divertor plasma-facing components (PFCs) in a tokamak are typically designed to withstand average steady-state heat loads of about 5–10 MW/m 2 , a limit that applies to both solid and liquid lithium (LL) PFCs. Exceeding these design values can result in surface damage to tungsten PFCs or excessive lithium (Li) evaporation in liquid lithium divertor (LLD) PFCs. Since exceeding the divertor heat load limits has serious consequences, it is therefore prudent to develop a tool to reduce the divertor heat load and bring the heat load to within the design limit without affecting the plasma performance. Active low Z impurity injection such as Li has been suggested as a potential solution to mitigate excess heat flux as suggested previously, given that non-coronal radiation can be quite large ~ 20–30 MJ per mole of injected Li. Li is considered desirable for reducing the edge neutral recycling helping to improve plasma energy confinement. In this paper, we model the Impurity Power Dropper (IPD) to investigate its potential of divertor heat flux control. The IPD is typically located at the top of the tokamak device and uses a vertical drift tube of a few meters. In the 2 m drift tube case, the IPD powder is accelerated to ~ 6 m/sec before reaching the plasma with the upper divertor configuration, matching the condition for the in-board side pellet injection case. By modeling the IPD geometry we determined the IPD powder deposition profile, and thus the non-coronal radiation and ionization profiles in time as well. From the enhanced radiation power loss, it is therefore possible to reduce the divertor heat load using the divertor simulation code. In conclusion, the IPD divertor heat flux control can be tested in the facilities with IPD including ST-40, DIII-D, EAST, WEST and NSTX-U.

Active lithium injection↗
DOE OSTI2020

Evaluation of measuring thermal conductivity of isotropic and anisotropic thermally insulating materials by transient plane source (Hot Disk) technique

The transient plane source (TPS) technique, also referred as the Hot Disk method, has been widely used due to its ability to measure the thermal properties of an extensive range of materials (solids, liquids, and powder). Recently, it has been recognized that typical Hot Disk sensors can influence TPS results of thermally insulating materials and lead to an overestimation of thermal conductivity. Although improvements have been proposed, they have not yet been implemented in the commercial TPS, leaving researchers with non-standardized modifications or options provided by a commercial Hot Disk apparatus. An empirical study of thermally insulating materials such as extruded polystyrene (XPS) and aerogel blanket is conducted in order to address the factors that affect the reliability of thermal conductivity k obtained using the commercial TPS apparatus. Sensor size, input power, duration of the measurements, applied pressure, and, in the case of anisotropic materials, heat capacity are investigated, and the results are compared with those using a Heat Flow Meter apparatus. The effect of sensor size on the k value is ascribed to heat loss through connecting leads and is more pronounced in smaller sensors and in materials with lower k values . In the case of XPS and aerogel, the effect becomes minimal for sensors with a radius r ≥ 6.4 mm. The low input power yields a high scattering of the results and should be avoided. Applied contact pressure and the tested region of the specimen play an important role in experiments with low-density fibrous materials due to the large percentage of heat being transferred by radiation and the heterogeneous nature of the samples, respectively. Additionally, the sensitivity of anisotropic measurements to the value of the material’s volumetric heat capacity ( ρC p ) is shown, emphasizing the need for the precise determination.

thermal conductivity↗
DOE OSTI2021

FAST discovery of an extremely radio-faint millisecond pulsar from the Fermi -LAT unassociated source 3FGL J0318.1+0252

High sensitivity radio searches of unassociated γ-ray sources have proven to be an effective way of finding new pulsars. Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST) during its commissioning phase, we have carried out a number of targeted deep searches of Fermi Large Area Telescope (LAT) γ-ray sources. On February 27, 2018 we discovered an isolated millisecond pulsar (MSP), PSR J0318+0253, coincident with the unassociated γ-ray source 3FGL J0318.1+0252. PSR J0318+0253 has a spin period of 5.19 ms, a dispersion measure (DM) of 26 pc cm –3 corresponding to a DM distance of about 1.3 kpc, and a period-averaged flux density of (~11±2) µJy at L-band (1.05–1.45 GHz). Among all high energy MSPs, PSR J0318+0253 is the faintest ever detected in radio bands, by a factor of at least ~4 in terms of L-band fluxes. With the aid of the radio ephemeris, an analysis of 9.6 years of Fermi-LAT data revealed that PSR J0318+0253 also displays strong γ-ray pulsations. Follow-up observations carried out by both Arecibo and FAST suggest a likely spectral turn-over around 350 MHz. This is the first result from the collaboration between FAST and the Fermi-LAT teams as well as the first confirmed new MSP discovery by FAST, raising hopes for the detection of many more MSPs. Finally, such discoveries will make a significant contribution to our understanding of the neutron star zoo while potentially contributing to the future detection of gravitational waves, via pulsar timing array (PTA) experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Support of Adhesion Mechanisms in Al 2 O 3 Aerosol Deposition Through Laser-Induced Particle Impact Testing

Aerosol deposition (AD) is a kinetic spray process capable of depositing ceramic coatings at room temperature, but AD process development is generally a laborious exploration of a large process parameter space. Here, this paper presents a case study investigating whether laser-induced particle impact testing (LIPIT) could be applied to expedite development of an alumina (Al 2 O 3 ) coating on nickel (Ni): Specifically, whether LIPIT measurements could predict critical velocities of adhesion on Ni and Al 2 O 3 , and the effect of ball milling the Al 2 O 3 powder. Because LIPIT has a diffraction-limited lower bound on imageable particle size, the usefulness of Al 2 O 3 powder agglomerates as a proxy for single particles was additionally studied. Overall, LIPIT measurements and AD sprays agreed that ball milling dramatically improves adhesion. Additionally, LIPIT measurements of critical velocity of adhesion of Al 2 O 3 powder agglomerates on Ni and Al 2 O 3 substrates (150 meters per second [m/s] and 250 m/s, respectively) quantitatively agreed with predictions from a previously published model based on picoindentation and molecular dynamics simulations. Together, these findings support the established hypothesis that Al 2 O 3 adheres via a dislocation-mediated mechanism in AD, that Al 2 O 3 powder agglomerates adhere as individual constituent particles rather than collectively, and that, for this case study, LIPIT measurements were predictive of AD process parameters.

Al2O3↗
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2021

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗
DOE OSTI2021

Impact of electric vehicle charging on the power demand of retail buildings

As electric vehicle penetration increases, charging is expected to have a significant impact on the grid. Electric vehicle charging stations will greatly affect a building site's power demand, especially with the onset of fast charging with power levels as high as 350 kW per charger. Here, we assess how electric vehicle charging stations would impact a retail big box grocery store, exploring numerous station sizes, charging power levels, and utilization factors in various climate zones and seasons. We measure the effect of charging by assessing changes in monthly peak power demand, electricity usage, and annual electricity bill, computed using three distinct rate structures. We find that an electric vehicle station has the potential to dwarf a big box building's power demand if behind the same meter, increasing monthly peak power demand at the site by over 250%. Cold-climate areas paired with rate structures incorporating high demand charges are most susceptible for significant changes to the annual electricity bill, with increases as high as 88%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Model predictive control for demand flexibility: Real-world operation of a commercial building with photovoltaic and battery systems

Hundreds of studies have investigated Model Predictive Control (MPC) for the optimal operation of building energy systems in the past two decades. However, MPC field tests are still uncommon, especially for small- and medium-sized commercial buildings and for buildings integrated with onsite renewables. This paper describes the implementation and the long-term performance evaluation of an MPC controller in a small commercial building equipped with behind-the-meter photovoltaics and electrochemical batteries. MPC controls space conditioning, commercial refrigeration, and the battery system. We tested two types of demand flexibility applications in the field: electricity bill minimization under time-of-use tariffs and responses to grid flexibility events. Results show that the proposed controller achieves 12% of annual electricity cost savings and 34% peak demand reduction against the baseline, while respecting thermal comfort and food safety. The field tests also demonstrate the ability of the MPC controller to provide a multitude of grid services including real-time pricing, demand limiting, load shedding, load shifting, and load tracking, using the same optimization framework.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation

Large-format additive manufacturing (LFAM) is a branch of additive manufacturing (AM) research with the ability to create large structures typically measuring several meters in scale. LFAM is advantageous for tooling applications, not only because it offers the ability to create complex geometries not easily made using subtractive manufacturing processes, but the cost savings of pelletized feedstock used by these systems result in larger parts printed at faster speeds than traditional AM systems. Fiber reinforced polymer (FRP) is a commonly used feedstock material in LFAM structures because it reduces the distortion experienced during printing. However, FRP introduces highly anisotropic thermomechanical properties and contributes to a nonhomogeneous microstructure that can result in critical distortion of dimensions during tooling. Measuring the global thermomechanical response of LFAM structures requires a more representative method that accounts for not only anisotropic properties but also the nonhomogeneous nature of the final part. This is where traditional techniques to measure thermomechanical response, such as thermomechanical analysis (TMA), fall short as they assume homogeneity. This study evaluated the coefficient of thermal expansion (CTE) of LFAM structures as measured by TMA as compared to a novel digital image correlation oven (DIC Oven) system. The LFAM structures were made from 20 % by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS). TMA measurements showed significant variations in CTE across a single LFAM bead, confirming the need for a global technique that captures overall thermomechanical response. The CTE values measured using the DIC Oven compared well to average TMA values obtained from localized measurements across the sample. The DIC Oven was also used to quantify the effects of different layer orientations on thermomechanical properties, which cannot be easily captured using TMA. A predictive model was also developed by using localized TMA values across an LFAM bead to predict the overall thermomechanical response of an LFAM structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Community-scale interaction of energy efficiency and demand flexibility in residential buildings

Demand-side management (DSM) strategies, including energy efficiency (EE) and demand flexibility (DF), contribute to cost-effective operation of the electricity grid. From a system-level perspective, such programs reduce costs, enhance reliability, and reduce network issues. Similarly, DSM programs help participating customers reduce utility bills while maintaining occupant comfort. Understanding the relationship between EE and DF is key to realizing the full potential of DSM programs. In this study, we modeled an all-electric residential community based on a 498-home community that is planned for construction in Fort Collins, Colorado in the United States. We used this community model to study the relationship between different EE measures, including building envelope upgrades and smart appliances, and DF enabled by a home energy management system (HEMS) responding to a time-varying tariff. Various EE levels in the homes – code-minimum, zero energy ready, and even higher levels of envelope efficiency – were simulated. DF is enabled by the HEMS, which coordinates behind-the-meter resources, including flexible building loads, PV, and home battery systems, to minimize utility bills while maintaining occupant comfort. When comparing to the code-minimum homes, EE upgrades alone reduce HVAC energy use during peak hours by up to 50% and the HVAC utility bill by up to $312/year. With the addition of HEMS, the average daily peak demand can be reduced by up to 0.58 MW or 1.2 kW/home in the higher envelope efficiency homes. The combination of EE upgrades, HEMS, and home battery systems is expected to save homeowners up to $590/year while increasing community load flexibility. However, HEMS and home battery systems are less effective in increasing the DF in the more efficient homes due to the lower load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Implementing multi-settlement decentralized electricity market design for transactive communities with imperfect communication

Recent advances in information and communication technologies and smart metering, provides strategic opportunities for ``prosumers" to reform their conventional energy practices towards more consumer-centric economies. From an operational perspective, managing power distribution networks is becoming more difficult with such active grid-edge systems providing limited to no visibility or control. Transactive Energy (TE) has been emerging as a key enabler towards effectively and efficiently integrating prosumers into competitive electricity markets. This work presents a transactive implementation of community-centric markets. A co-simulation framework is developed for evaluating the proposed market structure with high-fidelity models. Case studies on the IEEE-123 node test system demonstrate that community-centric transactive markets can enable communities of prosumers to operate collaboratively as grid-edge systems. The potential benefits of implementing community-centric TE systems are also illustrated.

Mukherjee, Monish↗
DOE OSTI2021

Techno-economic analysis of roll-to-roll production of perovskite modules using radiation thermal processes

Perovskite solar technology can produce economically viable photovoltaic devices due to low cost of materials and scalable manufacturing. Solution phase deposition of all active layers lends itself to roll-to-roll fabrication methods which are well-established and have production rates of several hundred square meters per minute. In this techno-economic analysis, the opportunity to scale at this production throughput is considered with manufacturing rates exceeding one gigawatt per year in a single plant. Intense pulsed light is used for the post deposition process to minimize costs associated with the footprint, equipment, and operation. The analysis is limited to the operation of a roll-to-roll manufacturing facility producing a perovskite solar film that can be incorporated into photovoltaic modules. Costs associated with materials, labor, and equipment are considered along with utilities determined from the fundamental engineering calculations. Furthermore, the results show that at very large-scale operations of several gigawatts, the costs to produce the solar films range between $0.04-$0.10 per watt.

14 SOLAR ENERGY↗