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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Rapid and precise tracking of water influx and efflux across cell membranes induced by a pulsed electric field

Quantitative measurements of water content within a single cell are notoriously difficult. In this work, we introduce a single-shot optical method for tracking the intracellular water content, by mass and volume, of a single cell at video rate. We utilize quantitative phase imaging and a priori knowledge of a spherical cellular geometry, leveraging a two-component mixture model to compute the intracellular water content. We apply this technique to study CHO-K1 cells responding to a pulsed electric field, which induces membrane permeabilization and rapid water influx or efflux depending upon the osmotic environment. The effects of mercury and gadolinium on water uptake in Jurkat cells following electropermeabilization are also examined.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

An invertible seven-dimensional Dirichlet cell characterization of lattices

Characterization of crystallographic lattices is an important tool in structure solution, crystallographic database searches and clustering of diffraction images in serial crystallography. Characterization of lattices by Niggli-reduced cells (based on the three shortest non-coplanar lattice vectors) or by Delaunay-reduced cells (based on four non-coplanar vectors summing to zero and all meeting at obtuse or right angles) is commonly performed. The Niggli cell derives from Minkowski reduction. The Delaunay cell derives from Selling reduction. All are related to the Wigner–Seitz (or Dirichlet, or Voronoi) cell of the lattice, which consists of the points at least as close to a chosen lattice point as they are to any other lattice point. The three non-coplanar lattice vectors chosen are here called the Niggli-reduced cell edges. Starting from a Niggli-reduced cell, the Dirichlet cell is characterized by the planes determined by 13 lattice half-edges: the midpoints of the three Niggli cell edges, the six Niggli cell face-diagonals and the four body-diagonals, but seven of the lengths are sufficient: three edge lengths, the three shorter of each pair of face-diagonal lengths, and the shortest body-diagonal length. These seven are sufficient to recover the Niggli-reduced cell.

Chemistry↗
NASA NTRS2015

NASA Space Radiation Program Integrative Risk Model Toolkit

NASA Space Radiation Program Element scientists have been actively involved in development of an integrative risk models toolkit that includes models for acute radiation risk and organ dose projection (ARRBOD), NASA space radiation cancer risk projection (NSCR), hemocyte dose estimation (HemoDose), GCR event-based risk model code (GERMcode), and relativistic ion tracks (RITRACKS), NASA radiation track image (NASARTI), and the On-Line Tool for the Assessment of Radiation in Space (OLTARIS). This session will introduce the components of the risk toolkit with opportunity for hands on demonstrations. The brief descriptions of each tools are: ARRBOD for Organ dose projection and acute radiation risk calculation from exposure to solar particle event; NSCR for Projection of cancer risk from exposure to space radiation; HemoDose for retrospective dose estimation by using multi-type blood cell counts; GERMcode for basic physical and biophysical properties for an ion beam, and biophysical and radiobiological properties for a beam transport to the target in the NASA Space Radiation Laboratory beam line; RITRACKS for simulation of heavy ion and delta-ray track structure, radiation chemistry, DNA structure and DNA damage at the molecular scale; NASARTI for modeling of the effects of space radiation on human cells and tissue by incorporating a physical model of tracks, cell nucleus, and DNA damage foci with image segmentation for the automated count; and OLTARIS, an integrated tool set utilizing HZETRN (High Charge and Energy Transport) intended to help scientists and engineers study the effects of space radiation on shielding materials, electronics, and biological systems.

Kim, Myung-Hee Y.↗
NASA NTRS2000

Planar Particle Imaging Doppler Velocimetry Developed

Two current techniques exist for the measurement of planar, three-component velocity fields. Both techniques require multiple views of the illumination plane in order to extract all three velocity components. Particle image velocimetry (PIV) is a high-resolution, high accuracy, planar velocimetry technique that provides valuable instantaneous velocity information in aeropropulsion test facilities. PIV can provide three-component flow-field measurements using a two-camera, stereo viewing configuration. Doppler global velocimetry (DGV) is another planar velocimetry technique that can provide three component flow-field measurements; however, it requires three detector systems that must be located at oblique angles from the measurement plane. The three-dimensional configurations of either technique require multiple (DGV) or at least large (stereo PIV) optical access ports in the facility in which the measurements are being conducted. Optical access is extremely limited in aeropropulsion test facilities. In many cases, only one optical access port is available. A hybrid measurement technique has been developed at the NASA Glenn Research Center, planar particle image and Doppler velocimetry (PPIDV), which combines elements from both the PIV and DGV techniques into a single detection system that can measure all three components of velocity across a planar region of a flow field through a single optical access port. In the standard PIV technique, a pulsed laser is used to illuminate the flow field at two closely spaced instances in time, which are recorded on a "frame-straddling" camera, yielding a pair of single-exposure image frames. The PIV camera is oriented perpendicular to the light sheet, and the processed PIV data yield the two-component velocity field in the plane of the light sheet. In the standard DGV technique, an injection-seeded Nd:YAG pulsed laser light sheet illuminates the seeded flow field, and three receiver systems are used to measure three components of velocity. The receiver systems are oriented at oblique angles to the light sheet in order to accurately resolve the three-component velocity. Each DGV receiver system contains two cameras, which share a common view of the illuminated flow through a beam-splitting cube. One camera views the illuminated flow directly (reference camera) and the second camera images the illuminated flow through an iodine vapor cell (signal camera). The laser frequency (wavelength) is adjusted so that the Doppler-shifted light from particles in the flow falls on an iodine absorption feature, see the following graph. The iodine vapor cell acts as a frequency-to-velocity filter by modulating the intensity of the transmitted light as a function of the flow velocity (Doppler shift). The ratio of the signal and reference images yields the component of the flow velocity along the bisector of the laser sheet propagation direction and the receiver system observation direction. The hybrid system employs a single-component DGV receiver system configured to simultaneously acquire PIV image data, as shown in the following diagram. The cameras used in the DGV receiver are replaced with PIV frame-straddling cameras, and the receiver system views the illuminated light sheet plane at 90 (as in the standard PIV configuration).

Wernet, Mark P.↗
DOE OSTI2021

In Situ Visualization of Li-Whisker with Grating-Interferometry-Based Tricontrast X-ray Microtomography

The lithium-ion battery has demonstrated tremendous economic and social impacts. Upon battery operation under different conditions, lithium changes its chemical state and physical formation, leading to undesired side reactions, e.g., lithium dendrite growth that degrades the cell performance and causes safety concerns. In situ detection and visualization of lithium metal in functional batteries could offer insights with both scientific and industrial significance but remain a frontier challenge. In this work, we demonstrate in situ three-dimensional imaging of lithium whisker using a grating-interferometry-based tricontrast X-ray microtomography method. Our approach explicitly reveals the micromorphology of the electrochemically developed porous lithium whisker with micrometer-level spatial resolution while offering sensitivity to the nanoporosity that is smaller than the nominal resolution limit. Our result reveals valuable structural information on the lithium whisker that is otherwise inaccessible. This method is also readily applicable to a broad range of battery research, including all-solid-state batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Spatiotemporal metabolic responses to water deficit stress in distinct leaf cell-types of poplar

The impact of water-deficit (WD) stress on plant metabolism has been predominantly studied at the whole tissue level. However, plant tissues are made of several distinct cell types with unique and differentiated functions, which limits whole tissue ‘omics’-based studies to determine only an averaged molecular signature arising from multiple cell types. Advancements in spatial omics technologies provide an opportunity to understand the molecular mechanisms underlying plant responses to WD stress at distinct cell-type levels. Here, we studied the spatiotemporal metabolic responses of two poplar ( Populus tremula× P. alba ) leaf cell types -palisade and vascular cells- to WD stress using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI). We identified unique WD stress-mediated metabolic shifts in each leaf cell type when exposed to early and prolonged WD stresses and recovery from stress. During water-limited conditions, flavonoids and phenolic metabolites were exclusively accumulated in leaf palisade cells. However, vascular cells mainly accumulated sugars and fatty acids during stress and recovery conditions, respectively, highlighting the functional divergence of leaf cell types in response to WD stress. By comparing our MALDI-MSI metabolic data with whole leaf tissue gas chromatography-mass spectrometry (GC-MS)-based metabolic profile, we identified only a few metabolites including monosaccharides, hexose phosphates, and palmitic acid that showed a similar accumulation trend at both cell-type and whole leaf tissue levels. Overall, this work highlights the potential of the MSI approach to complement the whole tissue-based metabolomics techniques and provides a novel spatiotemporal understanding of plant metabolic responses to WD stress. This will help engineer specific metabolic pathways at a cellular level in strategic perennial trees like poplars to help withstand future aberrations in environmental conditions and to increase bioenergy sustainability.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

Terrestrial Exospheric Dayside H-density Profile at 3 - 15 RE from UVIS/HDAC and TWINS Lyman-alpha Data Combined

Terrestrial ecliptic dayside observations of the exospheric Lyman-α column intensity between 3–15 Earth radii (RE) by UVIS/HDAC (UVIS – ultraviolet imaging spectrograph; HDAC – hydrogen-deuterium absorption cell) Lyman-α photometer at CASSINI have been analyzed to derive the neutral exospheric H-density profile at the Earth’s ecliptic dayside in this radial range. The data were measured during CASSINI’s swing-by maneuver at the Earth on 18 August 1999 and are published by Werner et al. (2004). In this study the dayside HDAC Lyman-α observations published by Werner et al. (2004) are compared to calculated Lyman-α intensities based on the 3D H-density model derived from TWINS (Two Wide-angle Imaging Neutral-atom Spectrometers) Lyman-α observations between 2008–2010 (Zoennchen et al., 2015). It was found that both Lyman-α profiles show a very similar radial dependence in particular between 3–8RE. Between 3.0–5.5RE impact distance Lyman-α observations of both TWINS and UVIS/HDAC exist at the ecliptic dayside. In this overlapping region the cross-calibration of the HDAC profile against the calculated TWINS profile was done, assuming that the exosphere there was similar for both due to comparable space weather conditions. As a result of the cross-calibration the conversion factor between counts per second and rayleigh, fc = 3.285 counts s−1R−1, is determined for these HDAC observations. Using this factor, the radial H-density profile for the Earth’s ecliptic dayside was derived from the UVIS/HDAC observations, which constrained the neutral H density there at 10RE to a value of 35 cm-3. Furthermore, a faster radial H-density decrease was found at distances above 8RE (≈r−2.37) compared to the lower distances of 3–7RE (≈r−2.37). This increased loss of neutral H above 8RE might indicate a higher rate of H ionization in the vicinity of the magnetopause at 9–11RE (near subsolar point) and beyond, because of increasing charge exchange interactions of exospheric H atoms with solar wind ions outside the magnetosphere.

Jochen H Zoennchen↗
DOE OSTI2024

Flexible Soft X-Ray Image Sensors based on Metal Halide Perovskites With High Quantum Efficiency

Soft X-ray imaging is a powerful tool to explore the structure of cells, probe material with nanometer resolution, and investigate the energetic phenomena in the universe. Conventional soft X-ray image sensors are by and large Si-based charge coupled devices that suffer from low frame rates, complex fabrication processes, mechanical inflexibility, and required cooling below -60 °C. Here, a soft X-ray photodiode is reported based on low-cost metal halide perovskite with comparable performance to commercial Si-based device. Nanothrough network electrode minimized the optical loss due to the shadowing of insensitive layers, while a multidimensional perovskite heterojunction is generated to reduce the photo-generated carrier loss. Further, this strategy promoted a record quantum efficiency of 8 × 10 3 % without cooling, several orders of magnitude greater than the previously achieved. Flexible and curved soft X-ray imaging arrays are fabricated based on this high-performance device structure, demonstrating stable soft X-ray response and sharp imaging capabilities. This work highlights the low-cost and efficient perovskite photodiode as a strong candidate for the next-generation soft X-ray image sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

PLEKHA7 signaling is necessary for the growth of mutant KRAS driven colorectal cancer

Plekha7 (Pleckstrin homology [PH] domain containing, family A member 7) regulates the assembly of proteins of the cytoplasmic apical zonula adherens junction (AJ), thus ensuring cell-cell adhesion and tight-junction barrier integrity. Little is known of Plekha7 function in cancer. In colorectal cancer (CRC) Plekha7 expression is elevated compared to adjacent normal tissue levels, increasing with clinical stage. Plekha7 was present at plasma membrane AJ with wild-type KRas (wt-KRas) but was dispersed in cells expressing mutant KRas (mut-KRas). Fluorescence lifetime imaging microscopy (FLIM) indicated a direct Plekha7 interaction with wt-KRas but scantily with mut-KRas. Inhibiting Plekha7 specifically decreased mut-KRas cell signaling, proliferation, attachment, migration, and retarded mut-KRAS CRC tumor growth. Binding of diC8-phosphoinositides (PI) to the PH domain of Plekha7 was relatively low affinity. This may be because a D175 amino acid residue plays a “sentry” role preventing PI(3,4)P{sub 2} and PI(3,4,5)P{sub 3} binding. Molecular or pharmacological inhibition of the Plekha7 PH domain prevented the growth of mut-KRas but not wt-KRas cells. Taken together the studies suggest that Plekha7, in addition to maintaining AJ structure plays a role in mut-KRas signaling and phenotype through interaction of its PH domain with membrane mut-KRas, but not wt-KRas, to increase the efficiency of mut-KRas downstream signaling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Forecasting the Decay of Hybrid Perovskite Performance Using Optical Transmittance or Reflected Dark-Field Imaging

The practicality and economic viability of hybrid perovskite solar cells hinge on their operational lifetime, and methods for forecasting the performance of perovskites under different operational stresses are urgently needed. Here, we explore the evolution of material-level optoelectronic properties as MAPbI 3 degrades and discover universal behaviors where the carrier diffusion length (L D ) decays before quasi-Fermi-level splitting (ΔE F ), regardless of the specific stress protocol (oxygen, humidity, thermal stress, or a combination). We employ a machine learning greedy feature selection model that uses initially measured properties to predict the time it takes L D to decrease to 85% of its initial value with a prediction accuracy of 12.8%. This model reveals a strong correlation between the initial rate of transmittance change and the time until loss of transport. We translate this material-level finding to photovoltaic device-level forecasting by demonstrating that the rate of change of transmittance is equivalent to the rate of change of the spatial standard deviation of dark-field image intensity (i.e., scattered light intensity) collected in reflection mode (and thus applicable to devices with opaque contacts). Furthermore, this work demonstrates that transmittance and scattering methods are highly effective for accelerated material (and device) stability evaluation and forecasting.

14 SOLAR ENERGY↗
NASA NTRS2019

Use of Polarimetric Radar Measurements to Constrain Simulated Convective Cell Evolution: A Pilot Study with Lagrangian Tracking

To probe the potential value of a radar-driven field campaign to constrain simulation of isolated convection subject to a strong aerosol perturbation, convective cells observed by the operational KHGX weather radar in the vicinity of Houston, Texas, are examined individually and statistically. Cells observed in a single case study of onshore flow conditions during July 2013 are first examined and compared with cells in a regional model simulation. Observed and simulated cells are objectively identified and tracked from observed or calculated positive specific differential phase (K(sub DP)) above the melting level, which is related to the presence of supercooled liquid water. Several observed and simulated cells are subjectively selected for further examination. Below the melting level, we compare sequential cross sections of retrieved and simulated raindrop size distribution parameters. Above the melting level, we examine time series of KDP and radar differential reflectivity (Z(sub DR)) statistics from observations and calculated from simulated supercooled rain properties, alongside simulated vertical wind and supercooled rain mixing ratio statistics. Results indicate that the operational weather radar measurements offer multiple constraints on the properties of simulated convective cells, with substantial value added from derived K(sub DP) and retrieved rain properties. The value of collocated three-dimensional lightning mapping array measurements, which are relatively rare in the continental US, supports the choice of Houston as a suitable location for future field studies to improve the simulation and understanding of convective updraft physics. However, rapid evolution of cells between routine volume scans motivates consideration of adaptive scan strategies or radar imaging technologies to amend operational weather radar capabilities. A 3-year climatology of isolated cell tracks, prepared using a more efficient algorithm, yields additional relevant information. Isolated cells are found within the KHGX domain on roughly 40 % of days year-round, with greatest concentration in the northwest quadrant, but roughly 5-fold more cells occur during June through September. During this enhanced occurrence period, the cells initiate following a strong diurnal cycle that peaks in the early afternoon, typically follow a south-to-north flow, and dissipate within 1 h, consistent with the case study examples. Statistics indicate that ∼ 150 isolated cells initiate and dissipate within 70 km of the KHGX radar during the enhanced occurrence period annually, and roughly 10 times as many within 200 km, suitable for multi-instrument Lagrangian observation strategies. In addition to ancillary meteorological and aerosol measurements, robust vertical wind speed retrievals would add substantial value to a radar-driven field campaign.

Fridlind, Ann M.↗
DOE OSTI2022

NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images

Understanding the spatial interactions between the elements of the tumor microenvironment -i.e. tumor cells. fibroblasts, immune cells- and how these interactions relate to the diagnosis or prognosis of a tumor is one of the goals of computational pathology. We present NaroNet, a deep learning framework that models the multi-scale tumor microenvironment from multiplex-stained cancer tissue images and provides patient-level interpretable predictions using a seamless end-to-end learning pipeline. Trained only with multiplex-stained tissue images and their corresponding patient-level clinical labels, NaroNet unsupervisedly learns which cell phenotypes, cell neighborhoods, and neighborhood interactions have the highest influence to predict the correct label. To this end, NaroNet incorporates several novel and state-of-the-art deep learning techniques, such as patch-level contrastive learning, multi-level graph embeddings, a novel max-sum pooling operation, or a metric that quantifies the relevance that each microenvironment element has in the individual predictions. We validate NaroNet using synthetic data simulating multiplex-immunostained images where a patient label is artificially associated to the -adjustable- probabilistic incidence of different microenvironment elements. We then apply our model to two sets of images of human cancer tissues: 336 seven-color multiplex-immunostained images from 12 high-grade endometrial cancer patients; and 382 35-plex mass cytometry images from 215 breast cancer patients. In both synthetic and real datasets, NaroNet provides outstanding predictions of relevant clinical information while associating those predictions to the presence of specific microenvironment elements.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1999

A Photometric Technique for Determining Fluid Concentration using Consumer-Grade Hardware

In support of a separate study to produce an exponential concentration gradient in a magnetic fluid, a noninvasive technique for determining, species concentration from off-the-shelf hardware has been developed. The approach uses a backlighted fluid test cell photographed with a commercial digital camcorder. Because the light extinction coefficient is wavelength dependent, tests were conducted to determine the best filter color to use, although some guidance was also provided using an absorption spectrophotometer. With the appropriate filter in place, the provide attenuation of the light passing, through the test cell was captured by the camcorder. The digital image was analyzed for intensity using, software from Scion Image Corp. downloaded from the Internet. The analysis provides a two-dimensional array of concentration with an average error of 0.0095 ml/ml. This technique is superior to invasive techniques, which require extraction of a sample that disturbs the concentration distribution in the test cell. Refinements of this technique using a true monochromatic laser light Source are also discussed.

Leslie, F.↗
DOE OSTI2021

Deep learning classification of lipid droplets in quantitative phase images

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Neutron-Friendly Li-Ion Battery Coin Cell for In Situ 3D Visualization of Li Plating

Advanced battery characterization using in situ/operando neutron imaging is critical for uncovering degradation modes such as lithium (Li) plating in Li-ion batteries (LIBs). However, conventional LIBs hinder operando neutron radiography (NR) and in situ neutron micro-computed tomography (N-μCT) for visualizing Li plating near the graphite-separator interface due to strong attenuation from hydrogen-rich components like PP–PE–PP separators, electrolyte, and Fe-based spacers. In this work, we designed and tested a neutron-friendly battery (NFB) optimized for in situ Li detection during extreme fast charging (XFC). Guided by neutron attenuation cross-sections and material transmission, the NFB enables clear visualization at the graphite–separator interface, which is typically opaque in standard LIBs. Electrochemical tests show the NFB exhibits voltage/current responses like standard cells for up to 50 XFC cycles. However, its lower reversibility and capacity are likely due to Cu-coated Al spacer degradation from delamination or corrosion. We propose titanium spacers as a more stable alternative, albeit requiring custom machining. Using this optimized cell, we achieved simultaneous neutron tomography of multiple cells, capturing in situ 3D images of dead Li accumulation, particularly near graphite edges. These heterogeneous deposits and disconnected Li clusters suggest localized current density hotspots during XFC.

25 ENERGY STORAGE↗