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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tunning the linkage of structure units to enable stable spinel-based cathode in the wide potential window

The low practical capacity (<140 mA h g –1 ) of spinel phase LiMn 2–x Ni x O 4 (0 < x < 1) excludes it from high energy density lithium ion batteries (LIBs) for powering electric vehicles. Extending the operating potential window from 3.0 to 4.8 V to 2.0–4.8 V can double the capacity, but result in fast capacity decay due to the drastic cubic-tetragonal phase transition below 3.0 V, induced by serious Jahn-Teller (J-T) distortion of structure units (Mn 3+ )O 6 octahedra. Herein, we propose a novel strategy to suppress J-T distortion by tuning the linkage of structure units MnO 6 octahedra. The original full-vertex-sharing LiO 4 tetrahedra around MnO 6 octahedra in spinel phase are partially replaced by edge-sharing LiO 6 octahedra, which relate Mn-O bonds along the dz 2 direction with those along the d xy plane, thus significantly mitigating J-T distortion and suppressing the phase transition when discharged to 2.0 V. Following this strategy, the prepared spinel-based cathode achieves a high reversible capacity of about 290 mA h g –1 and an energy density up to 957 W h kg –1 with improved cycling stability. Furthermore, this work finds a new opportunity for the traditional spinel cathode towards applications in high energy density LIBs in a low cost and sustainable manner.

25 ENERGY STORAGE↗
DOE OSTI2025

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deep kernel methods learn better: from cards to process optimization

Abstract The ability of deep learning methods to perform classification and regression tasks relies heavily on their capacity to uncover manifolds in high-dimensional data spaces and project them into low-dimensional representation spaces. In this study, we investigate the structure and character of the manifolds generated by classical variational autoencoder (VAE) approaches and deep kernel learning (DKL). In the former case, the structure of the latent space is determined by the properties of the input data alone, while in the latter, the latent manifold forms as a result of an active learning process that balances the data distribution and target functionalities. We show that DKL with active learning can produce a more compact and smooth latent space which is more conducive to optimization compared to previously reported methods, such as the VAE. We demonstrate this behavior using a simple cards dataset and extend it to the optimization of domain-generated trajectories in physical systems. Our findings suggest that latent manifolds constructed through active learning have a more beneficial structure for optimization problems, especially in feature-rich target-poor scenarios that are common in domain sciences, such as materials synthesis, energy storage, and molecular discovery. The Jupyter Notebooks that encapsulate the complete analysis accompany the article.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Chemical preintercalation of magnesium ions into ⍺-MoO 3 structure for improved electrochemical stability in Li-ion cells

Chemical preintercalation of layered materials, used as electrodes in intercalation-based energy storage devices, represents a promising strategy to enhance electrochemical stability and extend cycle life. However, standardized synthesis approaches for the chemical preintercalation of diverse ions into various layered materials are lacking, necessitating the development of specific synthesis routes for each ion and layered phase combination. In this study, we present the first successful demonstration of Mg 2+ ion chemical preintercalation into the interlayer region of α-MoO 3 , revealing its stabilizing effect during cycling in non-aqueous Li-ion cells. Using ethanol during hydrothermal treatment facilitated molybdenum reduction, which was critical for Mg 2+ ion preintercalation. Interestingly, we found that Mg preintercalation was accompanied by the incorporation of water. Mg-preintercalated α-MoO 3 exhibited enhanced charge storage capacity, electrochemical stability, and power capability compared to pristine α-MoO 3 electrodes. This improved performance is attributed to the structural stabilization provided by Mg 2+ pillars, which prevent undesirable phase transformations during repeated Li intercalation/deintercalation, and increased Li + ion diffusion due to the shielding of electrostatic interactions between electrochemically cycled ions and the α-MoO 3 lattice, enabled by structural water. In conclusion, our study offers new insights into developing chemical preintercalation synthesis approaches that can be broadly applied to a wide range of pillaring ions and layered material hosts.

25 ENERGY STORAGE↗
DOE OSTI2020

Structural trends in atomic nuclei from laser spectroscopy of tin

Tin is the chemical element with the largest number of stable isotopes. Its complete proton shell, comparable with the closed electron shells in the chemically inert noble gases, is not a mere precursor to extended stability; since the protons carry the nuclear charge, their spatial arrangement also drives the nuclear electromagnetism. We report high-precision measurements of the electromagnetic moments and isomeric differences in charge radii between the lowest 1/2 + , 3/2 + , and 11/2 - states in 117–131 Sn, obtained by collinear laser spectroscopy. Supported by state-of-the-art atomic-structure calculations, the data accurately show a considerable attenuation of the quadrupole moments in the closed-shell tin isotopes relative to those of cadmium, with two protons less. Linear and quadratic mass-dependent trends are observed. While microscopic density functional theory explains the global behaviour of the measured quantities, interpretation of the local patterns demands higher-fidelity modelling.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Solvari SR, Simplifying Residential Solar to 1 SKU, with Extended Testing

Accelerated weathering and material compatibility testing for polymeric and asphaltic materials. NLR will be testing the durability of the polymeric materials proposed for use in the supporting structures designed by TESCI solar. This will include the bare materials and coupons attached to asphalt shingles. The exposure will be in damp heat and separately heat, humidity and UV light, all followed by mechanical evaluation. Modification 1 is an extension of the first round of testing with both a continuation of some of the same testing and addition of new testing methods and materials. The testing of materials in the condition of A3 looking at mechanical durability will be continued looking at the materials used in the mounting brackets. We will be adding in testing of the silicone adhesive to the module and of the module itself. For the mounting brackets, testing will also be conducted at multiple temperatures and humidity levels to allow for extrapolation to the field.

14 SOLAR ENERGY↗
DOE OSTI2021

Methods of making porous molecular structures

Disclosed herein is a method of making a porous molecular structure from a solution comprising an insoluble metal containing material and a ligand-providing material. In some embodiments, the porous molecular structure can be a Metal-Organic Framework (MOF). Ionic metal salts are the most common type of metal source for MOF production, but dissolution of metal salts complicates solvent recycling and creates corrosion and oxidation issues through evolved nitrate and chloride anions. Elucidating information that leads toward more efficient production of these versatile nanomaterials, while extending the knowledge base of how MOFs form during reaction, is critical to advancing MOF materials into large-scale use. Disclosed herein are improved methods for controlled synthesis of porous molecular structures such as MOFs comprising a solution-based synthesis with insoluble metallic precursor.

Joshi, Jayraj Nayan↗
DOE OSTI2022

Hierarchical, Self-Assembled Metasurfaces via Exposure-Controlled Reflow of Block Copolymer-Derived Nanopatterns

Here, nanopatterning for the fabrication of optical metasurfaces entails a need for high-resolution approaches like electron beam lithography that cannot be readily scaled beyond prototyping demonstrations. Block copolymer thin film self-assembly offers an attractive alternative for producing periodic nanopatterns across large areas, yet the pattern feature sizes are fixed by the polymer molecular weight and composition. Here, a general strategy is reported that overcomes the limitation of fixed feature size by treating the copolymer thin film as a hierarchical resist, in which the nanoscale pattern motif is defined by self-assembly. Feature sizes can then be tuned by thermal reflow controlled locally by irradiative crosslinking or chemical alteration using lithographic ultraviolet light or electron beam exposure. Using blends of polystyrene-block-poly(methylmethacrylate) (PS-b-PMMA) with PS and PMMA homopolymer, we demonstrate both self-assembled PS grating and hexagonal hole patterns; exposure-controlled reflow is then used to reduce hole diameter by as much as 50% or increase PS grating linewidth by more than 180%. Transferring these nanopatterns, or their inverse obtained by a lift-off approach, into silicon yields structural colors that may be prescriptively controlled based on nanoscale feature size. Furthermore, patterned exposure enables area-selective feature size control, yielding uniform structural color patterns across centimeter square areas. Electron beam lithography is also used to show that the lithographic resolution of this selective-area control can be extended to the nanoscale dimensions of the self-assembled features. The exposure-controlled reflow approach demonstrated here takes a pivotal step towards fabricating complex, hierarchical optical metasurfaces using scalable self-assembly methods.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Mechanistic Transformation of CuI Nanoparticles Into Oxidation‐Resistant 2D Copper Nanoplates

Unconventional phase transformations reveal new crystallization mechanisms, yet direct observation of such pathways during nanoscale solution-phase synthesis remains challenging. This study uncovers an atypical growth process in which thermodynamically stable CuI nanoparticles (NPs) transform into high-energy 2D Cu plates. Using a combination of in situ transmission electron microscopy, ex situ structural analysis, and density functional theory calculations shows that the formation of structural defects induced by hexadecylamine and chloride ions facilitates the transformation by promoting surface iodine vacancies. The resulting Cu{111} nanoplates, with ultrathin thicknesses (≈4 nm) and exceptionally high aspect ratios (≈450), display enhanced oxidation resistance and long-term stability under ambient conditions. This resistance is attributed to the close-packed {111} facets, which suppress chemical oxidation even after extended exposure to air over 100 days. These findings provide new insights into non-classical crystallization pathways in metal nanomaterials and suggest a versatile approach for preparing oxidation-resistant, structurally defined Cu nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Nodavirus RNA replication crown architecture reveals proto-crown precursor and viral protein A conformational switching

Positive-strand RNA viruses replicate their genomes in virus-induced membrane vesicles, and the resulting RNA replication complexes are a major target for virus control. Nodavirus studies first revealed viral RNA replication proteins forming a 12-fold symmetric “crown” at the vesicle opening to the cytosol, an arrangement recently confirmed to extend to distantly related alphaviruses. Using cryoelectron microscopy (cryo-EM), we show that mature nodavirus crowns comprise two stacked 12-mer rings of multidomain viral RNA replication protein A. Each ring contains an ~19 nm circle of C-proximal polymerase domains, differentiated by strikingly diverged positions of N-proximal RNA capping/membrane binding domains. The lower ring is a “proto-crown” precursor that assembles prior to RNA template recruitment, RNA synthesis, and replication vesicle formation. In this proto-crown, the N-proximal segments interact to form a toroidal central floor, whose 3.1 Å resolution structure reveals many mechanistic details of the RNA capping/membrane binding domains. In the upper ring, cryo-EM fitting indicates that the N-proximal domains extend radially outside the polymerases, forming separated, membrane-binding “legs.” The polymerase and N-proximal domains are connected by a long linker accommodating the conformational switch between the two rings and possibly also polymerase movements associated with RNA synthesis and nonsymmetric electron density in the lower center of mature crowns. The results reveal remarkable viral protein multifunctionality, conformational flexibility, and evolutionary plasticity and insights into (+)RNA virus replication and control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Mechanical and durability properties of ultra-high-performance concrete of spent nuclear fuel dry storage systems: a review

Dry storage systems are used for interim storage of spent nuclear fuel (SNF). However, with the growing need to extend the operational periods of these systems, there are concerns about the degradation of their concrete overpacks, which could compromise the system's structural integrity and safety during hazardous events. Traditional concrete mixtures used in SNF dry storage systems have remained largely unchanged since their inception and often use conventional ingredients. These materials are susceptible to degradation mechanisms such as chemical attacks, alkali-silica reactions (ASR), and freeze–thaw cycles, which can lead to a loss of strength and durability over time. To address these challenges, this paper reviews the application of ultra-high-performance concrete (UHPC) as a promising alternative for spent nuclear fuel dry storage system overpacks. UHPC offers superior mechanical properties, exceptional durability, and reduced susceptibility to degradation mechanisms compared to conventional concrete. This paper focuses on the role of supplementary cementitious materials (SCMs) such as silica fume, fly ash, and metakaolin in enhancing UHPC performance for SNF storage applications. These SCMs have been shown to significantly improve the material’s microstructure, strength, and resistance to environmental stressors typically encountered in SNF storage environments. Moreover, incorporating SCMs supports sustainable construction by reducing cement consumption and associated carbon emissions. The review brings together existing research and experimental data, providing insights for engineers and researchers on developing UHPC mixtures that meet the rigorous demands of spent nuclear fuel dry storage systems, extending their service life and minimizing inspection intervals.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving. For machines though, this gap is guarded by at least two challenges: 1) machine learning techniques remain brittle and unable to generalize to a wide range of scenarios, and 2) effective training data that enhances generalization and generates the desired driving behavior. Further, each challenge can be computationally intensive on its own thereby exasperating the gap. Moreover, is has not yet been shown that a single form of learning or training is capable of addressing a large range of scenarios. As a result, solving the first challenge does not inherently solve the second and vice versa. The work described here discusses an approach to address the first challenge that would also provide a foundation for solving the second. Our approach utilizes a combination of conditional imitation learning with a static dataset, reinforcement learning with a simulation environment, and high-performance computing to train a neural network. As a result, this reduces the “time to solution” from to the existing techniques for autonomous driving and provides an extensible framework to address the second key challenge.

autonomous vehicles↗
DOE OSTI2022

Microbial Type IA Topoisomerase C-Terminal Domain Sequence Motifs, Distribution and Combination

Type IA topoisomerases have highly conserved catalytic N-terminal domains for the cleaving and rejoining of a single DNA/RNA strand that have been extensively characterized. In contrast, the C-terminal region has been less covered. Two major types of small tandem C-terminal domains, Topo_C_ZnRpt (containing C4 zinc finger) and Topo_C_Rpt (without cysteines) were initially identified in Escherichia coli and Mycobacterium tuberculosis topoisomerase I, respectively. Their structures and interaction with DNA oligonucleotides have been revealed in structural studies. Here, we first present the diverse distribution and combinations of these two structural elements in various bacterial topoisomerase I (TopA). Previously, zinc fingers have not been seen in type IA topoisomerases from well-studied fungal species within the phylum Ascomycota. In our extended studies of C-terminal DNA-binding domains, the presence of zf-GRF and zf-CCHC types of zinc fingers in topoisomerase III (Top3) from fungi species in many phyla other than Ascomycota has drawn our attention. We secondly analyze the distribution and combination of these fungal zf-GRF- and zf-CCHC-containing domains. Their potential structures and DNA-binding mechanism are evaluated. The highly diverse arrangements and combinations of these DNA/RNA-binding domains in microbial type IA topoisomerase C-terminal regions have important implications for their interactions with nucleic acids and protein partners as part of their physiological functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Microstructural changes and mass transport in cement-based materials: A modeling approach

Highlights: • Concept to relate microstructural changes, mass transport, and chemical reactions in cement-based materials is presented. • Multi-physics modeling approach utilizing an extended version of the PNP equation and the geochemical code IPHREEQC. • Case studies indicate significant changes in mass transport properties due to alterations in the microstructure. • Microstructural changes depend on exposure and interactions between chemical reactions, pore structure, and mass transport. A generic modeling framework is presented to relate microstructural changes, i.e. changes in the pore volume distribution and phase assemblage, and mass transport in cement-based materials. The modeling framework accounts for mass transport and chemical equilibrium between ions in the pore solution and solid hydrates by means of an extended version of the Poisson-Nernst-Planck equation, in which the chemical equilibrium is solved by the external geochemical code IPHREEQC. Results of numerical studies concerning carbonation and leaching of a cement-based material indicate significant changes in mass transport properties due to chemical reactions leading to alterations in the microstructure. The resulting highly non-linear (both spatial and temporal) microstructural changes are thereby depending on the exposure and indicate that interactions between chemical reactions, pore structure changes, and mass transport have to be accounted for as a whole.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Gaussian approximation potential for amorphous Si : H

Hydrogenation of amorphous silicon (a–Si : H) is critical for reducing defect densities, passivating midgap states and surfaces, and improving photoconductivity in silicon-based electro-optical devices. Modeling the atomic-scale structure of this material is critical to understanding these processes, which in turn is needed to describe c–Si/a–Si : H heterojunctions that are at the heart of modern solar cells with world-record efficiency. Density functional theory (DFT) studies achieve the required high accuracy but are limited to moderate system sizes of 100 atoms or so by their high computational cost. Simulations of amorphous materials have been hindered by this high cost because large structural models are required to capture the medium-range order that is characteristic of such materials. Empirical potential models are much faster, but their accuracy is not sufficient to correctly describe the frustrated local structure. Data-driven, machine-learned interatomic potentials have broken this impasse and have been highly successful in describing a variety of amorphous materials in their elemental phase. Here, we extend the Gaussian approximation potential (GAP) for silicon by incorporating the interaction with hydrogen, thereby significantly improving the degree of realism with which amorphous silicon can be modeled. We show that our Si : H GAP enables the simulation of hydrogenated silicon with an accuracy very close to DFT but with computational expense and run times reduced by several orders of magnitude for large structures. Here, we demonstrate the capabilities of the Si : H GAP by creating models of hydrogenated liquid and amorphous silicon and showing that their energies, forces, and stresses are in excellent agreement with DFT results, and their structure as captured by bond and angle distributions are in agreement with both DFT and experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analytical Solutions for Seismic Fluid-Structure Interaction of Head-Supported Cylindrical Tanks

Fluid-structure interaction (FSI) of earthquake shaking is a design consideration in the civil, nuclear, chemical, and mechanical industries. Preliminary sizing of structures and components in these industries will often use analytical solutions because there is insufficient information to warrant the analysis of numerical models. Here, this study extends prior analytical work on seismic FSI of base-supported tanks in the 1980s to accommodate head-supported tanks with geometries similar to those proposed for new-build, liquid (fluid)-filled, advanced reactors. Analytical solutions are derived for flexible, head-supported, cylindrical tanks subjected to small-amplitude, unidirectional, horizontal seismic motion, and address frequencies of lateral motions of the tank, hydrodynamic pressures, frequencies of waves, wave heights, and reactions at the head support. Solutions are presented for a range of tank dimensions and could be used for a) preliminary design of head-supported cylindrical tanks and their supporting structures with idealized seismic input, and b) verification of numerical models to be used for final seismic analysis, design, and probabilistic risk assessment.

42 ENGINEERING↗
DOE OSTI2026

First CLAS12 Double-Pion (Npp) Electroproduction Analysis

The N* program aims to explore strong interaction dynamics of the three-valence quark distance-dependent structure. The electroproduction and photoproduction studies provide insight into the nucleon resonance structure. One of the primary objectives of N* is to extract the electroexcitation amplitudes, which are crucial in determining the inner structure of various nucleon excitation states and their underlying degrees of freedom. Studying them on the nucleon length scale reveals also parts of the complex nature of the universe and its origin at their most fundamental level. The extraction of these amplitudes is mostly based on the single-pion, and particularly at higher invariant masses W, on the double-pion electroproduction channels, because nucleon resonance dominantly couple to them. CLAS has produced mostly all of the world data on charged double-pion electroproduction in the nucleon resonance region for photon virtualities Q2 up to 5 GeV2. The kinematic range can be extended with CLAS12, which can explore these amplitudes in the still almost unexplored range of Q2 > 5.0 GeV2. This will offer opportunities to understand the resonance structure at distances where the three-bound quark degree of freedom dominates and pave the way towards perturbative Quantum Chromodynamics (pQCD). This dissertation presents new double-pion electroproduction cross sections in the W range [1.4, 2.10] GeV and the Q2 range [2.0, 8.0] GeV2, using the Run Group A Fall-2018 dataset. This data was taken with the CLAS12 detector in Hall B at Thomas Jefferson National Laboratory (JLab) at an electron beam energy of 10.6 GeV. These cross sections are the basis for the extraction of resonance electroexcitation amplitudes using the phenomenological JLab- Moscow State University (JM) model.

Neupane, Krishna↗