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At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Tailoring Fibre Structure Enabled by X-ray Analytics for Targeted Biomedical Applications

The rising interest in designing fibres via spinning techniques combining the properties of various polymeric materials into advanced functionalised materials is directed towards targeted biomedical applications such as drug delivery, wearable sensors or tissue engineering. Understanding how these functional polymers exhibit multiscale structures ranging from the molecular level to nano-, micro-and millimetre scale is a key prerequisite for their challenging applications that can be addressed by a non-destructive X-ray based analytical approach. X-ray multimodalities combining X-ray imaging, scattering and diffraction allow the study of morphology, molecular structure, and the analysis of nano-domain size and shape, crystallinity and preferential orientation in 3D arrangements. The incorporation of X-ray analytics in the design process of polymeric fibers via their nanostructure under non-ambient conditions (i.e. temperature, mechanical load, humidity…) allows for efficient optimization of the fabrication process as well as quality control along the product lifetime under operating environmental conditions. Here, we demonstrate the successful collaboration between the laboratory of Biomimetic Textiles and Membranes and the Center of X-ray Analytics at Empa for the design, characterisation and optimisation of advanced functionalised polymeric fibrous material systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Designing Harvesting and Hauling Cost Models for Energy Cane Production for Biorefineries

The harvesting and hauling operations of bioenergy feedstock is an important area in biofuel production. Production costs can be minimized by maintaining optimal machinery units for these operations. The objective of this study is to design an optimal harvesting unit for bioenergy refinery and estimate harvesting and hauling costs of energy cane. A biorefinery with the annual capacity of processing twenty-five million imp. gallons of ethanol were considered. Given the efficiency of harvesting, a two-row soldier system was considered. Considering the year-round supply of energy cane to the refinery, the optimal machinery unit was designed, and the combined operation costs were derived. The average estimated ownership, repair, labor and fuel and lubricant costs of biomass harvest unit were calculated to be $\$$0.50, $\$$0.54, $\$$1.78 and $\$$1.51/mt, respectively. The costs distribution generated showed harvesting and hauling costs could range between $\$$5.47–$\$$9.23/mt of energy cane. The methodology and the research output will provide guidelines for investors in designing harvesting and hauling units and estimating costs for different scales of operation.

09 BIOMASS FUELS↗

DOE OSTI2021

Design and implementation of a portable diagnostic system for Thomson scattering and optical emission spectroscopy measurements

A diagnostic system, which has a design goal of high-portability, has been designed at Oak Ridge National Laboratory (ORNL). This project aims at providing measurements of key plasma parameters (ne, Te, ni, Ti) for fusion-relevant devices, utilizing Thomson scattering (TS) and optical emission spectroscopy (OES). The innovative design employs mostly commercial off-the-shelf instrumentation and a traveling team of researchers to conduct measurements at various magnetic-confinement plasma devices. The TS diagnostic uses a Quantel Q-smart 1500 Nd:YAG laser with a 2ω harmonic generator to produce up to 850 mJ of 532 nm laser pulses at 10 Hz. Collection optics placed at the detection port consists of an 11 × 3 optical fiber bundle, where the TS diagnostic uses an 11 × 1 subset array of the fibers, the OES diagnostic uses another 11 fibers, and the remaining fibers are available to the host institution. The detection system is comprised of two separate IsoPlane-320 spectrometers with triple-grating turrets of various line spacing and two PI-MAX 4 intensified CCD detectors, used simultaneously to measure a broad range of ion, impurity, and electron parameters. The self-contained diagnostic package also includes a data processing and storage system. The design and initial implementation of the TS-OES diagnostic system are described. The experiments from the proof-of-principle operation of the portable package on a high density (∼2.5 × 1022 m−3) and low-temperature (∼5 eV) electrothermal arc source at ORNL are also discussed.

Kafle, N. (ORCID:000000028144787X)↗

DOE OSTI2023

Machine learning for optimizing the manufacture and operation of intermediate temperature fuel cells

The project developed machine learning and artificial intelligence (ML/AI) methodologies for guiding and accelerating the materials design and processing of new high temperature proton conducing electrode ionomer binders and reinforced membranes for high-temperature proton exchange membrane fuel cell (HT-PEMFC; aka intermediate-temperature polymer electrolyte membrane fuel cells).

08 HYDROGEN↗

DOE OSTI2024

Frequency-domain computing using nonlinear acoustic-wave device on lithium niobate

Abstract Multiply-accumulation are crucial computing operations in signal processing, numerical simulations, and machine learning. In recent years, optical analog approaches have demonstrated higher computing performance and better power efficiency than their digital counterparts. However, analog computing chips usually need large areas and complex structures for parallel computing, as a single device element only executes one computing operation at a single time. Here, we demonstrate frequency-domain computing using the nonlinear acoustic-wave devices on lithium niobate, featuring a normalized external second-harmonic generation conversion efficiency of ~ 5.7 × 10-4 W-1. The second-order sum-frequency nonlinear process of lithium niobate enables multiplication of inputs encoded in the frequency domain. Compared to the analog schemes, our device features a notably simpler design, and nanofabrication requires only one lift-off. Using a single acoustic-wave device within an area of 0.03 mm2, we can simultaneously conduct over 130,000 multiply-accumulation operations. Our acoustic-wave device shows applications in real and complex vector convolutions and image processing. This demonstration sets the stage for experimental realizations into frequency-domain integrated nonlinear acoustic computing systems, potentially shaping future developments in acoustic neural networks and quantum computing.

chai, mingzhao (ORCID:0009000466226341)↗

DOE OSTI2026

Heliostat Sizing Methodology for Solar Heat for Industrial Processes

This study presents a method to obtain a heliostat size that minimizes the levelized cost of a heliostat-based concentrating solar thermal system for industrial process heat (IPH) applications at operating temperatures from 565 to 1550 degrees Celsius. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWhth. Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the levelized cost of heat (LCOH), producing a characteristic U-shaped trend with a robust near-optimal window of 8 - 12 m2; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats under deployment at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗

DOE OSTI2020

Advanced sorbents for modular oxygen production for REMS gasifiers

Under a DOE funded effort, Thermosolv LLC has been developing a sorbent-based oxygen production technology for gasification and oxy-combustion applications. The sorbents utilize oxygen-storage properties of certain perovskites to (1) selectively adsorb oxygen at moderate temperature from compressed air and (2) release the adsorbed oxygen into a vacuum or a sweep gas such as CO2 and/or steam. Through cyclic operations of multiple sorbent beds such a process can be made continuous. Pressure drop across the sorbent bed and other similar design considerations dictate that the sorbent be in the form of a high surface-area-to-volume pellet and yet still possess sufficient crush strength and integrity. Process efficiency is determined by the sorption and desorption kinetics and sorbent capacity. Typical process involves cycle times in the order of 100 seconds, a time too short to fully utilize the full volume of the sorbent and the sorption capacity of the sorbent pellets. As a part of this project, Thermosolv LLC undertook the development of oxygen sorbents as a high-surface area supported sorbent on a light-weight inert support to (1) reduce the cost, (2) increase the productivity, and (3) reduce the overall weight of the reactor. Using a previously developed perovskite (LSCF 1991) with its well-characterized performance, composite sorbent pellets each consisting of an inert core coated by a thin layer of the functional perovskite material were produced. Several low-density, inexpensive inert solids supports in the 1/8”-1/4” size were selected to keep the pressure drop across the sorbent bed in the acceptable range. A number of commercial technologies including spray coating, dip coating, incipient impregnation of porous substrate followed by thermal annealing at various temperatures and duration were employed and tested to produce robust composite supported sorbent pellets. A sense of optimum coating thickness was developed by testing sorbent pellets of various increasing diameter pellets. LSCF-1991extrudates ranging in size from 1/32” to 3/16” were tested in a TGA and in a fixed-bed pressure swing test set-up for sorption/desorption cycles of interest. The data show that for the operational conditions of interest the coating thickness for a supported sorbent pellet needs to be approximately 1/32” (about 0.8 mm). Subsequent work thereby concentrated on developing composite pellets of various substrates, shapes and sizes with coating layer of about this size range. Candidate support materials were chosen based on cost, inertness, mechanical strength, thermal expansion and chemical stability with sorbent material, and in a size range to give an acceptable pressure drop in fixed-bad reactor configurations. Coating application methods used for application of the sorbent onto the support included precipitation, spray coating and dip coating from sorbent slurries and sol gels. For all coated supports where we could successfully apply a uniform coating of desired thickness with an acceptable handling performance in terms of exfoliation, TGA-based cyclic sorption/desorption testing was performed to determine cycling capacity of oxygen. Among nearly twenty different support materials tested, best adhesion performance was obtained from stainless saddle supports. In the bench-scale fixed-bad tests stainless steel saddle support composite pellets with a coating thickness in the 0.6 mm or so range, the composite sorbent pellet performance approached up to 95% of that of the 2 mm parent material pellets. In a parallel approach to reducing the cost of the sorbent, alternate sorbent formulations replacing/reducing the amount of cobalt in the LSCF family were also investigated. Successful formulations that could match the performance of LSCF 1991 were identified based on TGA cyclic tests as LSCF 1919 and LSF 1910. In the range of operational envelop of cycle times and other relevant process operating conditions, the reduced Co formulations showed comparable performance in the bench-scale fixed-bad cyclic operations. As a part of this project, we also attempted substitution of La and Sr with Ca and Ba, and Co with Mn, Ni and Cu with little success, but the overall project goal of reducing sorbent cost in terms of raw material and manufacturing expenses was successful.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Process Improvements For Pu-238 Production at Idaho National Laboratory

Idaho National Laboratory (INL) has supported the production of Pu-238 for future NASA deep space missions since 2017. Over this time, INL has worked to improve the qualification process of Pu-238 production targets as well as improve processes related to the shipping, storage, irradiation, and storage of Pu-238 production targets. Qualification of Pu-238 production targets began with flux measurements and scoping analysis to provide fundamental data to confirm the impacts on the operation of the Advanced Test Reactor (ATR), Fig1. Later, initial production targets were irradiated in ATR’s I-7 position, and then the South Flux Trap (SFT). A modified target design was then implemented which would use the full length of the ATR core and increase Pu-238 production. While working to improve and streamline the qualification of the Pu-238 production targets, INL worked to improve multiple operational aspects of the Pu-238 production process. These changes include updating procedures to streamline operations, supporting modification of shipping containers to contain five rather than one production target, reviewing target receipt procedures and changing work flow to provide flexibility in target receipt, and designing and fabricating support equipment for the storage and internal transfer of production targets.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2026

Compositional Reasoning for Hierarchical State Machines

Harel statecharts and its derivatives are popular graphical languages for specifying discrete control systems via hierarchical state machines. Separately, there has been a long line of work on specifying concurrent systems with process calculi which come equipped with an algebraic theory, the ability reason compositionally about various temporal properties, and strong type systems. While these two approaches to modeling systems are tantalizingly similar, the integrated reasoning principles that exist for process calculi have not been demonstrated in hierarchical state machines. A key issue is that operational theories for process calculi do not behave like control systems, and thus, there is virtually no tool support for modeling control systems with such languages. For a control system designer, bringing the integrated, more scalable reasoning from the process calculi to state-machine languages would enable the specification of more complex systems and a more modular systems development process. Our insight is that we can recover many important results from the process calculi in hierarchical state machines with local scope. We employ a structural operational semantics, which is ubiquitous in process and 𝜆-calculi but uncommon in hierarchical statemachine formalizations, to enable inductive reasoning about behavior. Taking inspiration from the structure of process calculi metatheories, we define a calculus of refinement and equivalence that we prove sound with respect to local notion of (bi)simulation. Furthermore, we prove that the calculus preserves the behavioral properties of reactivity, observational determinism, traces, and linear temporal properties. Our results are mechanized in the Rocq proof assistant.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Efficient Mesofluidic Separation of Large Particles in nuclear slurries - 20408

Efficient and effective particle separation is essential to cleanup of many nuclear wastes. For example, particle separation may be used to accelerate settle-decant bottlenecks that limit the throughput necessary to achieve the U.S. Department of Energy waste cleanup mission in a timely manner. Particle separation may be used to protect downstream processing equipment from pulses of solids that may be encountered near (within a few feet of) liquid-solid interfaces during waste transfer operations, thereby preventing work stoppages. Effective particle separation may permit efficient sludge washing. These are only a few of the ways in which particle separation is important. Yet, efficient and effective particle separation in nuclear processing environments remains challenging. For example, settle-decant operations permit larger and heavier particles to settle, leaving smaller, lighter particles suspended. However, settle-decant operations are slow, convection currents may resuspend solids, hindered settling of multicomponent slurries remains incompletely understood, and predictive models for settling in graduated cylinders fail to match limited observations of settling in large waste tanks. Additionally, pumping operations can cause turbulent resuspension of particles when the pump intake is close to the settled solids layer. Filtration techniques that use membranes or partially permeable barriers retain larger particles, permitting smaller particles to permeate. However, filters, including dead-end filtration, are prone to clogging and caking, operate at elevated pressures due to minimal void volume, and increase in pressure during operations, which require more control systems. Therefore, the need for high throughput particle separation techniques that operate with modest pressure drops persists. A novel mesofluidic separator presents the opportunity to effectively and efficiently accelerate the waste cleanup mission. The separator separates large particles from process streams across a broad range of particle sizes and has no moving parts or media to replace, regenerate, or clean. This separator design has an unusually large void volume, permitting operation at much higher flow rates (and lower pressures) than traditional filtration (e.g., dead-end filtration). Industrial-scale flow rates have been demonstrated. In performance testing, mesofluidic separators operate at might flow rates (>90 gpm (0.0006 m{sup 3}/s) in piping 3 inches (0.08 m) in diameter; Re>10{sup 5}), with modest pressure drop (∼25 psi (170 KPa) in testing). In complex, aggregating waste simulants, the separator loses <25% of flow projected over months without back pulsing or chemical cleaning. Mesofluidic separation presents infrastructure advantages, reduces risk, and provides mission impact. Infrastructure advantages include implementation within existing transfer systems, plug and play without facility modifications to safety systems, and operation at low pressures. The separator is flexible in location, may be positioned within or outside of waste tanks, and may replace or augment dead-end and cross-flow filters. Mesofluidic separation reduces risk by minimizing waste (no media to replace or regenerate and no cleaning chemicals to handle and dispose) and by minimizing filter change-out consistent with as low as reasonably achievable (ALARA) exposure to workers. The potential mission impact of these separators is substantial. The separator has potential to support, simplify, and accelerate in-farm transfers and waste feed delivery. Furthermore, the separator can free up settling and holding tanks in the Direct Feed Low-Activity Waste (DFLAW) mission by reducing or eliminating post-transfer settling and wait times with the potential to free up 1 Mgal (4000 m{sup 3}) of double-shell tank space. This paper quantitatively compares mesofluidic separation to dead-end filtration, discusses scale-up results, and considers the separator's potential to efficiently and effectively reduce the long-term environmental ability of particulate-rich nuclear wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Process Improvement For Pu-238 Production at Idaho National Laboratory

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2021

BETO 2021 Peer Review - FCIC Task 6: High Temperature Conversion

The impacts of feedstock variability on pyrolysis processes are significant but poorly defined. Current engineering designs are based on empirical guidelines, useful only over a narrow range of feedstock properties. The objectives of this project are to (1) Develop science-based knowledge of how feedstock attributes and operational parameters impact pyrolysis process reliability and product quality; and (2) Build an experimental and computational toolset that predicts these outcomes, enabling processes to optimize reliability and product quality. Biomass is a complex feedstock. Controlling for and testing the effects of individual attributes is very challenging. This project couples multiscale experimentation and modeling to accurately capture the fundamental physics and chemistry of biomass flow and conversion behavior in feeding and pyrolysis reactor operations. Our focus is on pine residue attributes – anatomical fraction (bark, needles, wood), particle morphology (size/shape distribution, density, porosity), and chemical composition (extractives, biopolymers, alkali metals) – that impact product quality for downstream catalytic upgrading. Because detailed pyrolysis product characterization is limited, cutting-edge analytical techniques are being developed to reveal impactful product attributes. The tools and knowledge developed here will enable integrated pyrolysis-based processes that are more robust, flexible, and market-responsive with respect to feedstock variability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Online data analysis and reduction: An important co-design motif for extreme-scale computers

A growing disparity between supercomputer computation speeds and I/O rates means that it is rapidly becoming infeasible to analyze supercomputer application output only after that output has been written to a file system. Instead, data-generating applications must run concurrently with data reduction and/or analysis operations, with which they exchange information via high-speed methods such as interprocess communications. The resulting parallel computing motif, online data analysis and reduction (ODAR), has important implications for both application and HPC systems design. Here we introduce the ODAR motif and its co-design concerns, describe a co-design process for identifying and addressing those concerns, present tools that assist in the co-design process, and present case studies to illustrate the use of the process and tools in practical settings.

Data Analysis↗

DOE OSTI2021

Large-scale dissolution of sintered Mo disks

Non-uranium production of 99 Mo via neutron capture or by photonuclear reaction using an electron accelerator is receiving considerable attention. For commercial production of 99 Mo, post-irradiation processes must incorporate a robust design for easy scale-up. Once developed, large-scale chemical processes must be optimized for hot-cell operations and potential automation. In this work, we present experimental results on the large-scale dissolution of sintered Mo disks using three 50% hydrogen peroxides from different suppliers. Dissolution rates obtained for 600-g Mo batches and potential reasons for different dissolution behaviors is discussed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

CMOS-Based Single-Cycle in-Memory XOR/XNOR

Big data applications are on the rise, and so is the number of data centers. The ever-increasing massive data pool needs to be periodically backed up in a secure environment. Moreover, a massive amount of securely backed-up data is required for training binary convolutional neural networks for image classification. XOR and XNOR operations are essential for large-scale data copy verification, encryption, and classification algorithms. The disproportionate speed of existing compute and memory units makes the von Neumann architecture inefficient to perform these Boolean operations. Compute-in-memory (CiM) has proved to be an optimum approach for such bulk computations. The existing CiM-based XOR/XNOR techniques either require multiple cycles for computing or add to the complexity of the fabrication process. Here, we propose a CMOS-based hardware topology for single-cycle in-memory XOR/XNOR operations. Our design provides at least 2× improvement in the latency compared with other existing CMOS-compatible solutions. We verify the proposed system through circuit/system-level simulations and evaluate its robustness using a 5000-point Monte Carlo variation analysis. This all-CMOS design paves the way for practical implementation of CiM XOR/XNOR at scaled technology nodes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Electro-Oxidative Dehydrogenation of Ethane to Ethylene Using Lanthanum-Strontium-Iron Oxide Perovskite Electrocatalysts

Developing alternative, industrially viable ethylene production routes has received important research attention. One chemical pathway of interest is the oxidative dehydrogenation (ODH) of ethane, although issues such as product selectivity, combustion hazards, and oxidizer supply have hindered the practical scale-up of this technology. The presented work describes the use of a solid oxide fuel cell (SOFC) platform employing lanthanum-strontium-iron oxide perovskite (La 1-x Sr x FeO 3-δ , or LSFx) electrocatalysts to perform electrochemical-ODH (e-ODH), a process design that has the potential to address the challenges of ODH implementation. The effects of La and Sr stoichiometry, operating temperature, and current density are reported. The highest performance was observed using a La:Sr ratio of 0.50 (LSF0.50) at 750 °C and a current density of 0.50 A·cm –2 , achieving an ethane conversion of 18.7 ± 0.3%, ethylene selectivity of 91.4 ± 1.9%, and ethylene yield of 17.1 ± 0.1%. These results demonstrate several potential advantages for utilizing a SOFC platform to perform e-ODH of ethane to ethylene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

ARJUNA: An Electrochemical Interface Mapping Probe for Solid-State Batteries

Solid-state batteries (SSBs) are promising candidates for next-generation energy storage, although their performance can be compromised by interfacial heterogeneity within the electrolyte. Furthermore, ensuring the quality of large form-factors electrolyte film is crucial for establishing a robust manufacturing platform for solid-state batteries. Herein, we report on the use of ARJUNA, an electrochemical interface mapping system, to characterize heterogeneities at solid electrolyte interfaces and to serve as a quality control system for SSB manufacturing. In addition to spatial mapping, the proposed system can also probe the interface behavior as a function of pressure and temperature. We present the operating principle, design, instrumentation, and evaluation of the system alongside a typical hybrid solid electrolyte produced using two common manufacturing processes. This report showcases the capability of ARJUNA to probe the heterogeneity and quality of processed solid electrolyte films.

25 ENERGY STORAGE↗