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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multifunctional Polar 2D Lead Iodide Perovskites Exhibiting Persistent Spin Texture

Ferroelectric Rashba semiconductors are a rare class of multifunctional materials promising for spin–orbitronics due to the possibility of electrically switchable spin textures. Hybrid organic–inorganic metal halide perovskites offer exceptional tunability that can be harnessed to target noncentrosymmetry; however, the complex interactions between organic and inorganic components are not rationally understood. Here, we use an asymmetric spacer cation with a strong molecular dipole moment (2-fluorobenzylammonium, 2FBZ) and increase the intrinsic quantum well thickness to n > 1 to synthesize three new polar 2D lead iodide perovskites (2FBZ) 2 (A) n-1 Pb n I 3n+1 with A = methylammonium (MA) or formamidinium (FA) and n = 2, 3. Single-crystal structure analysis reveals the C 2v symmetry of these crystal structures and substantial structural distortions, which enable Rashba and Dresselhaus band splitting and persistent spin texture, confirmed by DFT calculations. Measurements of the resulting symmetry-dependent properties, such as second harmonic generation, switchable photovoltaic effect, ferroelectric polarization, and low temperature photoluminescence show switchable ferroelectric semiconducting properties. Furthermore, these results introduce a general chemical design strategy toward polar symmetry by exploiting the complex interplay between asymmetric spacer cations and A-site cations in quasi-2D (n > 1) halide perovskites to realize new classes of multifunctional materials for future spin–orbitronic applications.

Cations↗
DOE OSTI2025

Imine Reductase-Catalyzed, Radical-Mediated Asymmetric Cyano Group Migration

Functional group migration (FGM) reactions represent a fundamental class of transformations in organic chemistry, enabling the repositioning of functional moieties in nonobvious ways. However, catalytic asymmetric radical-mediated FGMs remain rare due to the inherent challenges of achieving catalyst-controlled enantioselectivity over free radical intermediates. Herein, we repurpose imine reductases (IREDs), a class of biotechnologically important enzymes known for their substrate promiscuity, to enable the first examples of catalytic asymmetric cyano group migration via a radical mechanism. An orthogonal set of radical enzymes, including PbaIREDCym and SmiIREDCym, was engineered, allowing both 1,4- and 1,5-cyano group migration reactions to occur in an enantiodivergent fashion. The use of the nonionic surfactant TPGS-1000 was found to improve both the yield and enantioselectivity of these cyano migration reactions. Furthermore, this biocatalytic process exhibited a broad substrate scope and is readily scalable, affording a rare example of chiral nonamine product assembly with imine reductases. More broadly, stereoselective radical biocatalysis with engineered IREDs and other versatile enzymes provides a potentially general solution to challenging asymmetric FGM reactions.

Biocatalysis↗
DOE OSTI2026

Mixed Nd 4+/3+ and Cluster Magnetism in Hexagonal Perovskite 12R-Ba 4 NdMn 3 O 12−γ

Hexagonal perovskite oxides with 12R stacking host well-separated face-sharing octahedral metal trimers with short metal–metal distances, leading in some cases to large degrees of magnetic frustration and cluster magnetism. Introducing magnetic ions in proximity to these trimers can influence the degree of frustration and cluster magnetism, but the extent to which the magnetism can be tuned by varying neighboring metal cations remains an open question. In this work, we test the impacts of using Nd in proximity to Mn trimers in the hexagonal perovskite 12R-Ba 4 NdMn 3 O 12−γ . Given this stoichiometry, Nd should assume the 4+ oxidation state with a spin state of S = 1, which would be the first realization of Nd 4+ in an oxide environment. Through detailed bulk magnetic, X-ray absorption spectroscopic, and powder neutron diffraction (PND) measurements, we find that Nd 4+ is realized in this material, but there is also partial reduction to Nd 3+ , which is charge-balanced by O vacancies. Magnetometry measurements indicate an antiferromagnetic ordering temperature T N ≈ 16 K, and PND measurements reveal a surprising collinear antiferromagnetic structure with magnetic space group Pc2/m (no. 10.49 in BNS notation), which has not previously been seen in this class of materials. Our results represent a comprehensive analysis of the structural, electronic, and magnetic properties of 12R-Ba 4 NdMn 3 O 12−γ , showing the first observation of partial Nd 4+ in an oxide, and demonstrating that this structural class can host a broad range of magnetic structures which are not easily predicted based on compositional trends.

14 SOLAR ENERGY↗
DOE OSTI2025

Surface Hydration of Porous Nickel Hydroxides Facilitates the Reversible Adsorption of CO 2 from Ambient Air

Direct air capture (DAC) under humid ambient conditions typically requires the use of organic components, with sorbents that are purely inorganic in composition for the most part operating hundreds of degrees above room temperature. In this work, we report porous metal hydroxides as a novel class of water-tolerant, oxidatively and hydrothermally stable low-temperature sorbents that exhibit competitive DAC working capacities of 1.25 mmol/g over 5 consecutive temperature swing adsorption–desorption cycles in the presence of steam and oxygen. Aqueous miscible organic solvent treatments are used to create highly porous structures with surface areas exceeding 700 m 2 /g that capture CO 2 in the form of bicarbonates under dry conditions, and carbonates under wet conditions. Water exerts a facilitative rather than an inhibiting effect on CO 2 binding, and the presence of hydrating multilayers serves to stabilize carbonate species akin to moisture swing adsorbents except for the fact that solvation results in a remarkable (upto 10-fold) increase, not decrease, in DAC capacity. High-valent doping with cerium is used to improve DAC capacities by amplifying surface basicity, evidencing porous nickel hydroxides specifically (and porous metal hydroxides more generally) as a novel class of robust, earth-abundant DAC sorbents.

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

Emergent Trends Complicate the Interpretation of the United States Drought Monitor (USDM)

Abstract Effective drought management must be informed by an understanding of whether and how current drought monitoring and assessment practices represent underlying nonstationary climate conditions, either naturally occurring or forced by climate change. Here we investigate the emerging climatology and associated trends in drought classes defined by the United States Drought Monitor (USDM), a weekly product that, since 2000, has been used to inform drought management in the United States. The USDM classifies drought intensity based in part on threshold percentiles in key hydroclimate quantities. Here we assess how those USDM‐defined drought threshold percentiles have changed over the last 23 years, examining precipitation, runoff, soil moisture (SM), terrestrial water storage (TWS), vapor pressure deficit (VPD), and near‐surface air temperature. We also assess underlying trends in the frequency of drought classifications across the U.S. Our analysis suggests that the frequency of drought class occurrence is exceeding the threshold percentiles defined by the USDM in a number of regions in the United States, particularly in the American West, where the last 23 years have emerged as a prolonged dry period. These trends are also reflected in percentile‐based thresholds in precipitation, runoff, SM, TWS, VPD, and temperature. Our results emphasize that while the USDM appears to be accurately reflecting observed nonstationarity in the physical climate, such trends raise critical questions about whether and how drought diagnosis, classification, and monitoring should address long‐term intervals of wet and dry periods or trends.

Geology↗
DOE OSTI2025

The System for Classification of Low-Pressure Systems (SyCLoPS): An All-In-One Objective Framework for Large-Scale Data Sets

We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Simulating Marine Ecosystem Dynamics and Biogeochemical Cycling With Multiple Plankton Functional Types

Current representations of marine ecosystems in Earth System Models are greatly simplified, neglecting key interactions between dynamic food webs, biogeochemistry, and climate change. We use the Marine Biogeochemistry Library code base within the Community Earth System Model 2.2.2 to create an expanded ecosystem model with eight phytoplankton groups and four zooplankton size classes (MARBL-8P4Z). Incorporating more specific plankton types and size classes has the potential to capture a wider range of possible behaviors of the ecosystem, its complex interactions with biogeochemistry, and its feedback to climate change. It also permits stronger observational constraints, including in situ group-specific biomass and various observational estimates of plankton community composition. MARBL-8P4Z broadly captures observed global-scale patterns in biomass and community composition for both phytoplankton and zooplankton, with a good performance in simulating broad biogeochemistry fields. The model shows comparable spatial patterns and magnitudes to the observed picophytoplankton biomass (Prochlorococcus, Synechococcus, picoeukaryotes), and captures the seasonal cycle of mesozooplankton biomass. Picophytoplankton groups and microzooplankton dominate biomass and production in oligotrophic, subtropical regions, while nano-phytoplankton, diatoms and the larger zooplankton groups prevail at higher latitudes and within upwelling zones. The model simulates reasonable energy transfer efficiency through the food web, with tight linkages between the phytoplankton community composition, zooplankton grazing, and carbon export, with the potential to link to fisheries models. Thus, MARBL-8P4Z has the potential to account for key climate-driven ecological shifts in the plankton that will modify ocean biogeochemistry in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Monitoring Fracture Hydromechanical Evolution in the Lab and Field Using Unsupervised Metric Learning

Fractures evolve in time through thermal‐hydraulic‐mechanical‐chemical (THMC) processes that alter their long‐range hydraulic transport properties and modify subsurface behavior and activities. The location of subsurface fractures makes it necessary to use remote sensing techniques such as passive or active seismic monitoring for fracture characterization. In this paper, we develop a machine learning approach to monitor the evolution of fracture properties using passive seismic sources in a laboratory setting and using active seismic monitoring from the Sanford Underground Research Facility in Lead, South Dakota, at a depth of 1.25 km in amphibolite rock during stimulation of natural fractures as well as during induced fracturing. The unsupervised metric learning technique applies tandem neural networks (twin (Siamese) or triplet) with contrastive loss and adaptive margins to track slowly varying systems for which class or similarity labels are not available. The approach adopts locality‐sensitive hashing to divide time‐ordered contiguous data into an arbitrary number of pseudo‐classes. Contrastive‐loss training with many hash bins generates an evolving latent‐space trajectory. This approach enables unsupervised metric learning for seismic data stacks under the condition of contiguous state sampling and slowly varying fracture properties. The displacement discontinuity theory provides a mechanistic foundation for the fracture‐dependent trajectories that are related to relaxation of fractures with time‐dependent specific stiffness responding to changes in stress or fluid saturation.

02 PETROLEUM↗
DOE OSTI2024

Legionella metaeffector MavL reverses ubiquitin ADP-ribosylation via a conserved arginine-specific macrodomain

ADP-ribosylation is a reversible post-translational modification involved in various cellular activities. Removal of ADP-ribosylation requires (ADP-ribosyl)hydrolases, with macrodomain enzymes being a major family in this category. The pathogen Legionella pneumophila mediates atypical ubiquitination of host targets using the SidE effector family in a process that involves ubiquitin ADP-ribosylation on arginine 42 as an obligatory step. Here, we show that the Legionella macrodomain effector MavL regulates this pathway by reversing the arginine ADP-ribosylation, likely to minimize potential detrimental effects caused by the modified ubiquitin. We determine the crystal structure of ADP-ribose-bound MavL, providing structural insights into recognition of the ADP-ribosyl group and catalytic mechanism of its removal. Further analyses reveal DUF4804 as a class of MavL-like macrodomain enzymes whose representative members show unique selectivity for mono-ADP-ribosylated arginine residue in synthetic substrates. We find such enzymes are also present in eukaryotes, as exemplified by two previously uncharacterized (ADP-ribosyl)hydrolases in Drosophila melanogaster . Crystal structures of several proteins in this class provide insights into arginine specificity and a shared mode of ADP-ribose interaction distinct from previously characterized macrodomains. Collectively, our study reveals a new regulatory layer of SidE-catalyzed ubiquitination and expands the current understanding of macrodomain enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Spectrally sharp magnetic excitations above the critical temperature in a frustrated Weyl semimetal

The rare-earth α-pyrochlore iridates are a prospective class of conducting frustrated magnets where electronic correlations, large spin-orbit coupling, and geometrical frustration interplay, leading to a rich set of magnetic and electronic phases. Despite their intriguing properties, the magnetic order and excitations in this fundamental class of topological quantum materials remain poorly understood due to challenges in growing large single crystals and insufficient microscopic information on their temperature-dependent phases. Here, by combining state-of-the-art thin-film synthesis, resonant elastic and inelastic X-ray scattering, spin wave analysis, and dynamical spin susceptibility calculations, we unequivocally reveal the presence of spectrally sharp, gapped magnetic excitations in Y 2 Ir 2 O 7 that surprisingly persist well above the Néel transition temperature, signaling the presence of a quasi-universal regime connected to fluctuations on frustrated lattices. This finding implies the existence of a highly unusual cooperative paramagnetic (CP) phase above the ordering temperature and offers an explanation for the puzzling high-temperature magnetic behavior observed across the family of metallic pyrochlore crystals. Understanding such magnetic excitations at technologically relevant temperatures opens up possibilities for novel topological spintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Novel adaptive immune systems in pristine Antarctic soils

Antarctic environments are dominated by microorganisms, which are vulnerable to viral infection. Although several studies have investigated the phylogenetic repertoire of bacteria and viruses in these poly-extreme environments with freezing temperatures, high ultra violet irradiation levels, low moisture availability and hyper-oligotrophy, the evolutionary mechanisms governing microbial immunity remain poorly understood. Using genome-resolved metagenomics, we test the hypothesis that Antarctic poly-extreme high-latitude microbiomes harbour diverse adaptive immune systems. Our analysis reveals the prevalence of prophages in bacterial genomes (Bacteroidota and Verrucomicrobiota), suggesting the significance of lysogenic infection strategies in Antarctic soils. Furthermore, we demonstrate the presence of diverse CRISPR-Cas arrays, including Class 1 arrays (Types I-B, I-C, and I-E), alongside systems exhibiting novel gene architecture among their effector cas genes. Notably, a Class 2 system featuring type V variants lacks CRISPR arrays, encodes Cas1 and Cas2 adaptation module genes. Phylogenetic analysis of Cas12 effector proteins hints at divergent evolutionary histories compared to classified type V effectors and indicates that TnpB is likely the ancestor of Cas12 nucleases. Our findings suggest substantial novelty in Antarctic cas sequences, likely driven by strong selective pressures. These results underscore the role of viral infection as a key evolutionary driver shaping polar microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A human-in-the-loop explanation framework for morphologically transparent AI predictions from whole-slide images

Deep learning models enable the prediction of clinical endpoints from whole-slide images (WSIs), but many such models function as “black boxes”, lacking transparency about whether and which histomorphological patterns drive their predictions, hindering interpretability and clinical adoption. Here we propose a human-in-the-loop explanation framework, MorphoXAI, which provides both local and global interpretability for deep learning models by incorporating human-expert interpretations. At the global level, it reveals the histomorphological patterns on which the model consistently relies to distinguish between classes of WSIs, as well as the patterns associated with confusion between classes. At the local level, it indicates which of these patterns are used in the prediction of an individual WSI and which regions within the slide correspond to such patterns. We validated our method across multiple deep learning–based WSI analysis tasks spanning different tissue types. The results show that our framework generates explanations that accurately reflect the histomorphology underlying the model’s predictions at both global and local levels. For interpretability and clinical utility in diagnostic contexts, human evaluation results showed that our explanations were easy to interpret, rich in diagnostic features, and directly helpful for diagnostic decision-making, thereby enhancing pathologist-AI collaboration. Our work highlights that unifying global and local explanations and grounding them in expert-interpreted morphology enhances the interpretability and verifiability of deep learning models, thereby facilitating the transparent deployment of such models in clinical practice.

Lou, Peiliang↗
DOE OSTI2025

High-throughput and data-driven search for stable optoelectronic AMSe 3 materials

The rapid advancement in emerging optoelectronic technologies demands highly efficient, affordable, and ecofriendly materials. In this context, ternary chalcogenides, especially ternary selenides, show early promise as a material class due to their stability and remarkable electronic, optical, and transport properties. In this work, we integrate first-principles-based high-throughput computations with machine learning (ML) techniques to predict the thermodynamic stability and optoelectronic properties of 920 valency-satisfied selenide compounds. Through investigating polymorphism, our study reveals the edge-sharing orthorhombic Pnma phase (NH 4 CdCl 3 -type) as the most stable structure for most ternary selenides. High-fidelity supervised ML models are trained and tested to accelerate stability and band gap predictions. These data-driven models pin down the most influential features that dominantly control key material characteristics. The multistep high-throughput computations identify the ternary selenides with optimal direct band gaps, light carrier masses, and strong optical absorption edges. The extensive materials screening considering phase stability, toxicity, and defect tolerance, finally identifies the seven most suitable candidates for photovoltaic applications. Two of these final compounds, SrZrSe 3 and SrHfSe 3 , have already been synthesized in a single-phase form, with the latter showing an optically suitable band gap, aligning well with our findings. The non-adiabatic molecular dynamics reveal sufficiently long photoexcited charge carrier lifetimes (on the order of nanoseconds) in some of these selected selenide materials, indicating their exciting characteristics. Overall, our study suggests a robust in silico framework that can be extended to screen large datasets of various material classes for identifying promising photoactive candidates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrosome assembly: Structural insights from high voltage-activated calcium channel (CaV)–chaperone interactions

Ion channels are multicomponent complexes (termed here as“electrosomes”) that conduct the bioelectrical signals required for life. It has been appreciated for decades that assembly is critical for proper channel function, but knowledge of the factors that undergird this important process has been lacking. Although there are now exemplar structures of representatives of most major ion channel classes, there has been no direct structural information to inform how these complicated, multipart complexes are put together or whether they interact with chaperone proteins that aid in their assembly. Recent structural characterization of a complex of the endoplasmic membrane protein complex (EMC) chaperone and a voltage-gated calcium channel (CaV) assembly intermediate comprising the pore-forming CaVα1 and cytoplasmic CaVβ subunits offers the first structural view into the assembly of a member of the largest ion channel class, the voltagegated ion channel (VGIC) superfamily. The structure shows how the EMC remodels the CaVα1/CaVβ complex through a set of rigid body movements for handoff to the extracellular CaVα2δ subunit to complete channel assembly in a process that involves intersubunit coordination of a divalent cation and ordering of CaVα1 elements. These findings set a new framework for deciphering the structural underpinnings of ion channel biogenesis that has implications for understanding channel function, how drugs and disease mutations act, and for investigating how other membrane proteins may engage the ubiquitous EMC chaperone.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Predicting Damages to Remainder Parcels in Right-of-Way Acquisitions for Expanding Transportation Infrastructure: Using a Truncated Finite-Mixture Model

Right-of-way acquisition is a critical component of transportation infrastructure development. Transportation infrastructure projects cannot proceed without proper right-of-way acquisition or may face significant delays. State Departments of Transportation frequently acquire parcels of land for roadway expansion projects. A majority of these acquisitions can be partial takings, referring to a portion of a parcel that is acquired. The remainder of the property usually suffers economic changes due to the partial acquisition, which can be calculated as damage percentages. The damage percentage represents the extent to which the remaining land or property value has been diminished due to the acquisition. It reflects the remaining property value percentage that may have been lost or compromised due to the acquisition. Here, this study aims to provide a robust model to estimate damage percentages to the remainder parcels that may help state Departments of Transportation appraisers make early predictions about the damages in cases involving partial takings. The research uses 509 appraisal reports from the Tennessee Department of Transportation to identify the key parcel attributes that influence the percentage of damages. Three regression models are developed: a linear regression model, a finite-mixture model (FMM), and a truncated FMM with two latent classes. The modeling results show that the truncated FMM with two classes outperforms the other models. To validate the models, actual sales data is collected and analyzed for 59 properties, and the results suggest that the model predictions are fairly accurate. A predictive tool is developed based on the models to help appraisers anticipate right-of-way damages under different scenarios and can provide early predictions about the damages.

42 ENGINEERING↗
DOE OSTI2024

Upper and lower bounds on phase-space rearrangements

Broad classes of plasma phenomena can be understood in terms of phase-space rearrangements. For example, the net effect of a wave–particle interaction may consist of moving populations of particles from one region of phase space to another. Different phenomena drive rearrangements that obey different rules. When those rules can be specified, it is possible to calculate bounds that limit the possible effects the rearrangement could have (such as limits on how much energy can be extracted from the particles). This leads to two problems. The first is to understand the mapping between the allowed class of rearrangements and the possible outcomes that these rearrangements can have on the overall distribution. The second is to understand which rules are appropriate for which physical systems. There has been recent progress on both fronts, but a variety of interesting questions remain unanswered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Scintillation of colloidal nanocrystals

Scintillators are materials that convert ionizing radiation in the form of particles or photons into low-energy photons in the ultraviolet to near-infrared spectral range. Here, this work reviews efforts to use colloidal nanocrystals as scintillator materials. To date, research on colloidal nanocrystals as scintillators has focused on doped phosphor systems, quantum dots and related structures, and perovskite-based nanocrystals. Among various material classes and forms, colloidal semiconductor nanocrystals stand out thanks to their appealing fluorescence properties, yet understanding of their radioluminescence and cathodoluminescence is incomplete. This review discusses fundamental limits and material design challenges toward achieving high brightness, fast speed, and durable scintillator performance with nanocrystal scintillators. First, this review describes the basic principles and efficiency limitations of scintillation, particularly the large influence of multiple exciton generation in many nanocrystal species, as well as performance metrics. Second, methods for measurement are described. Third, we review the results of the main classes of nanocrystal scintillators, including quantum dots and related particles, perovskites, and doped-phosphor particles. Fourth, scintillation imaging is discussed in terms of the relevant performance metrics and results obtained using nanocrystal materials. Finally, we note the strengths and weaknesses of nanocrystal scintillators and discuss potential areas of further development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Thermodynamic properties of “near-perfect” gas

When applied thermodynamics requires simple representations of thermodynamic quantities, one often finds quantities such as pressure and the thermal energy density expressed as a monomial linear product of density and temperature power laws. This is a simple generalization of the product of density and temperature used for the perfect gas that admits a broader range of thermodynamic behavior into analytic fluid calculations or provides an analytic form that is readily fit to tabulated equation-of-state data for an arbitrary material. This paper reviews the thermodynamic properties of this generalized perfect-gas model, treating it as a class of “near-perfect-gas” models that are defined and unified here, for the first time, through a shared Helmholtz free energy. This generalization from perfect to near-perfect-gas models preserves some perfect-gas properties (e.g., constant adiabatic exponents) but not others (e.g., constant specific heats) and is constrained by thermodynamic consistency. It is important to be aware of the properties of this class of near-perfect-gas models when using them as surrogates for real nonperfect materials that may have properties that cannot be captured by near-perfect-gas models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗