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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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NASA NTRS1985

A Leaky Waveguide Model for MHD Wave Driven Winds from Coronal Holes

Magnetohydrodynamic (MHD) waves, driven by the large scale convective motions of the photosphere are suggested as a possible source of additional acceleration for the stellar wind. Most of the turbulent power in a coronal hole is carried by MHD waves with periods of a few hundred seconds or longer. This is evident from direct observations of turbulence in the solar photosphere, as well as in situ observations of turbulence in the solar wind. But waves with periods this long have wavelengths which are typically as large as the transverse scale of the coronal hole flux tube itself. For these waves boundary effects are important and the coronal hole must be treated as a waveguide. The propagation of MHD waves using this waveguide approach is discussed. The simple model presented demonstrates that coronal holes can act as waveguides for MHD waves. For typical solar parameters the waves are compressible and can generate a wave tensile force which tends to cancel at least part of the wave pressure force. This effect tends to decrease the efficiency of MHD wave acceleration.

Davila, J. M.↗

NASA NTRS2015

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

climate↗

DOE OSTI2026

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Solution-Processable Polymer Donor-Small Molecule Acceptor Bulk Heterojunction Organocatalysts for Enhancing CO 2 -to-CO Photoconversion

Metal-free organic semiconductors have emerged as a kind of promising star material in photocatalysis. However, their photocatalytic efficacy is impeded by the great recombination rate of the photogenerated charge carriers. Herein, we demonstrate the devising of solution-processable organic semiconductor bulk heterojunction (BHJ) systems with varying ratios by using BP3DT and PC 61 BM as the donor (D) and acceptor (A) candidates, respectively, for enhanced selective CO production from CO 2 photoreduction. The prepared BP3DT/PC 61 BM BHJs are solution-processed on both glass substrates (GS) and molecular sieves (MS) via a drop-casting technique to form an active thin film and porous photocatalysts to catalyze CO production. All BP3DT/PC 61 BM BHJs efficiently produce CO as the primary product in the existence of trace-level TEA/H 2 O (0.5 mL). Our results show that the photocatalytic efficiency depended on the D/A w% ratios and its nanoscale phase separation morphology within the BHJ, contributing to the promotion of exciton dissociation. Additionally, the BHJ undergoes an ostensible morphological transition from large-scale phase-separation to a fine mixed homogeneous nanoscale by varying the BP3DT/PC 61 BM blend ratio from 30/70 w% to 70/30 w%, which increases the interfacial area and shortens the distance of the exciton to the D/A surface, and promotes charge carrier separation, corroborated by photo-optical and photoelectrochemical experimental results. Accordingly, the resulting BP3DT/PC 61 BM BHJ@MS with a D/A ratio of 70/30 w% achieves a CO yield of 819 μmol·g cat -1 h -1 , surpassing those of pure PC 61 BM (126 μmol·g cat -1 h -1 ) and BP3DT (72 μmol·g cat -1 h -1 ) by 6.5- to 11.3-fold and also exceeding that of metal-free linear conjugated polymer-based organocatalysts reported to date. Specifically, this is the first work to develop an organic-semiconductor-based BHJ photocatalyst, which may offer a nascent way to design more efficient organocatalysts for CO 2 reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1978

Dual polarized long wavelength radar for discrimination of agricultural land use

The scattered return of imaging radars is primarily sensitive to target structure or roughness and to composition of complex permittivity. The relative degree of penetration, or the depth of material to which the return is sensitive, also varies directly with the wavelength. Where vegetation can be eliminated as a factor, the surface return may be analyzed for variations in roughness or composition (primarily moisture content). L-band (25-cm) imagery has provided evidence that long-wavelength systems with improved penetration capability have the potential for minimizing the vegetation contribution and enhancing the surface return variations. However, the increased wavelength increases the sensitivity to large-scale structure. In the present paper, it is shown that addition of a cross polarized channel enables the interpreter to distinguish vegetation and orientation perturbations in the surface return.

Waite, W. P.↗

NASA NTRS1989

Galaxy evolution and large-scale structure in the far-infrared. I - IRAS pointed observations

Redshifts for 66 galaxies were obtained from a sample of 93 60-micron sources detected serendipitously in 22 IRAS deep pointed observations, covering a total area of 18.4 sq deg. The flux density limit of this survey is 150 mJy, 4 times fainter than the IRAS Point Source Catalog (PSC). The luminosity function is similar in shape with those previously published for samples selected from the PSC, with a median redshift of 0.048 for the fainter sample, but shifted to higher space densities. There is evidence that some of the excess number counts in the deeper sample can be explained in terms of a large-scale density enhancement beyond the Pavo-Indus supercluster. In addition, the faintest counts in the new sample confirm the result of Hacking et al. (1989) that faint IRAS 60-micron source counts lie significantly in excess of an extrapolation of the PSC counts assuming no luminosity or density evolution.

Lonsdale, Carol J.↗

NASA NTRS1993

Comparison of HRDI wind measurements with radar and rocket observations

Wind fields in the mesosphere and lower thermosphere are obtained with the High Resolution Doppler Imager (HRDI) on the Upper Atmosphere Research Satellite (UARS) by observing the Doppler shifts of emission lines in the O2 Atmospheric band. The validity of the measured winds depends on an accurate knowledge of the positions on the detector of the observed lines in the absence of a wind-induced Doppler shift. These positions have been determined to an accuracy of approximately 5 m/s from the comparison of winds measured by HRDI with those obtained by MF radars. Excellent agreement is found between HRDI measured winds and winds observed with radars and rockets. In addition, the sensitivity of HRDI to migrating tides and other large scale waves is demonstrated.

Burrage, M. D.↗

NASA NTRS1993

Numerical simulation of non-Newtonian free shear flows

Free shear flows, like those of mixing layers, are encountered in aerodynamics, in the atmosphere, and in the ocean as well as in many industrial applications such as flow reactors or combustion chambers. It is, therefore, crucial to understand the mechanisms governing the process of transition to turbulence in order to predict and control the evolution of the flow. Delaying transition to turbulence as far downstream as possible allows a gain in energy expenditure while accelerating the transition can be of interest in processes where high mixing is desired. Various methods, including the use of polymer additives, can be effective in controlling fluid flows. The drag reduction obtained by the addition of small amounts of high polymers has been an active area of research for the last three decades. It is now widely believed that polymer additives can affect the stability of a large variety of flows and that dilute solutions of these polymers have been shown to produce drag reductions of over 80 percent in internal flows and over 60 percent in external flows under a wide range of conditions. The major thrust of this work is to study the effects of polymer additives on the stability of the incompressible mixing layer through large scale numerical simulations. In particular, we focus on the two dimensional flow and examine how the presence of viscoelasticity may affect the typical structures of the flow, namely roll-up and pairing of vortices.

Homsy, G. M.↗

NASA NTRS1994

Imager for Mars Pathfinder (IMF)

The IMP camera is a near-surface sensing experiment with many capabilities beyond those normally associated with an imager. It is fully pointable in both elevation and azimuth with a protected, stowed position looking straight down. Stereo separation is provided with two optical paths; each has a 12-position filter wheel. The primary function of the camera, strongly tied to mission success, is to take a color panorama of the surrounding terrain. IMP requires approximately 120 images to give a complete downward hemisphere from the deployed position. IMP provides the geologist, and everyone else, a view of the local morphology with millimeter-tometer-scale resolution over a broad area. In addition to the general morphology of the scale, IMP has a large compliment of specially chosen filters to aid in both the identification of the mineral types and their degree of weathering.

Smith, Peter H.↗

NASA NTRS1994

Direct numerical simulation of incompressible axisymmetric flows

In the present work, we propose to conduct direct numerical simulations (DNS) of incompressible turbulent axisymmetric jets and wakes. The objectives of the study are to understand the fundamental behavior of axisymmetric jets and wakes, which are perhaps the most technologically relevant free shear flows (e.g. combuster injectors, propulsion jet). Among the data to be generated are various statistical quantities of importance in turbulence modeling, like the mean velocity, turbulent stresses, and all the terms in the Reynolds-stress balance equations. In addition, we will be interested in the evolution of large-scale structures that are common in free shear flow. The axisymmetric jet or wake is also a good problem in which to try the newly developed b-spline numerical method. Using b-splines as interpolating functions in the non-periodic direction offers many advantages. B-splines have local support, which leads to sparse matrices that can be efficiently stored and solved. Also, they offer spectral-like accuracy that are C(exp O-1) continuous, where O is the order of the spline used; this means that derivatives of the velocity such as the vorticity are smoothly and accurately represented. For purposes of validation against existing results, the present code will also be able to simulate internal flows (ones that require a no-slip boundary condition). Implementation of no-slip boundary condition is trivial in the context of the b-splines.

Loulou, Patrick↗

NASA NTRS1947

Supplementary Free-Spinning-Tunnel Tests of a 1/16-Scale Model of the McDonnell XB-85 Airplane Equipped with a Conventional-Tail Arrangement

Spin tests have been conducted in the Langley free-spinning tunnel on a 1/16-scale model of the McDonnell XP-85 airplane with the normal X-tail replaced with a short-coupled conventional tail arrangement. The effect of the conventional tail arrangement and the effects of various modifications upon the spin and recovery characteristics of the model were determined. The results of the tests indicated that installation of the conventional tail arrangement wil not provide satisfactory recoveries from spins of the airplane. Satisfactory recoveries will be obtainable, however, either by installing in addition a very large ventral fin (17.94 sq ft, full-scale) below the tail or by decreasing the width of the fuselage and making it flat sided rearward of the wing trailing edge.

Klinar, Walter J.↗

NASA NTRS2009

Nanofiber Filters Eliminate Contaminants

With support from Phase I and II SBIR funding from Johnson Space Center, Argonide Corporation of Sanford, Florida tested and developed its proprietary nanofiber water filter media. Capable of removing more than 99.99 percent of dangerous particles like bacteria, viruses, and parasites, the media was incorporated into the company's commercial NanoCeram water filter, an inductee into the Space Foundation's Space Technology Hall of Fame. In addition to its drinking water filters, Argonide now produces large-scale nanofiber filters used as part of the reverse osmosis process for industrial water purification.

Source record↗

NASA NTRS2018

Mars Ecopoiesis Testbed

Mars surface conditions where liquid water is absent were simulated for the purposes of laboratory research. A pressure-temperature (P-T) profile was maintained in which no combination of pressure or temperature corresponds to the liquid region of the water phase diagram. The triple point of pure water occurs at T = 0.1oC and P(H2O) = 6.01 mbar; therefore all temperatures and pressures must be kept below these values, respectively. A 35-day test was performed in a commercial planetary simulation system (Techshot, Inc., Greenville, IN) in which the minimum night-time temperature was -80oC, the maximum daytime temperature was +26oC, the simulated day-night light cycle in earth hours was 12-on and 12-off, and the total pressure of the pure CO2 atmosphere was maintained below 11 mbar. Any water present was allowed to equilibrate with the changing temperature and pressure. The gas phase was sampled into a CR1-A condensation-mirror low-pressure hygrometer, which uses liquid nitrogen (down to 77oK) to determine the dew point (Buck Technologies, Boulder, CO). Dew point was measured once every hour and recorded on a data logger, along with the varying temperature in the chamber, from which the partial pressure of water was calculated. The resulting calculated daily cycles were tracked on the water P-T diagram, and no points were found to fall within the liquid-phase region of the diagram. It is concluded that there was no liquid water present throughout the test except during the initial pump-down period when aqueous specimens were introduced on the first day (less than 1 hour). Mars regolith simulant was present during this test, and further investigation is needed to determine whether liquid water could have been present or absent in the regolith in the form of brine. Biological samples consisting of Cyanobacteria: Anabena sp., Chroococcidiopsis CCMEE171, Plectonema boryanum; Eubacteria: Bacillus subtilis, Pseudomonas aeruginosa, and Eukaryota: Chlorella ellipsoidia were maintained in the simulator under the above-described conditions. The exposed specimens were tested for intracellular esterase activity, chlorophyll content (where appropriate) and reproductive survival. All tests yielded low-level positive results in all cases. In parallel to these terrestrial studies a planned design study was undertaken for the proposed test bed. Design requirements include compact assembly for transport and installation on the planetary surface (multiple units per mission would be expected), protective internal package for the release of organisms, a means of atmosphere exchange, access to sunlight, a means of penetrating the planetary surface, and most importantly a means of acquiring regolith while meeting the requirements of planetary protection. In consultation with advisers a design was created, and a large-scale mock-up of this design was fabricated by additive manufacturing at Techshot, Inc. with moving parts that simulated the components of the design. The mock-up assembly has been demonstrated to interested parties. A means of detecting live metabolism will also be included in the test bed. Several options were reviewed, and it is concluded that, by the time the ecopoiesis test bed is ready for testing the optimum instrument will be the equivalent of a hand-held mass spectrometer for metabolic gas analysis. This will maximize versatility and reveal much more information than could a detector of a single product (such as molecular oxygen), and the

Ecopoiesis↗

NASA NTRS2002

Tropical Convection's Roles in Tropical Tropopause Cirrus

Remote sensing observations reveal the frequent occurrence of tropopause cirrus, thin cirrus layers located near the tropical cold-point tropopause. Here, we present a theory in which tropical convection plays several important roles in tropopause cirrus formation. First, tropical convection is the primary means by which the moisture required for tropopause cirrus formation is transported into the upper troposphere. However, previous studies suggest that this convection rarely penetrates to the altitudes at which tropopause cirrus layers are observed, suggesting that additional vertical moisture transport is required to explain tropopause cirrus formation. We propose a mechanism for explaining this transport in which tropical convection plays the key role. According to this hypothesis, the transport is accomplished by meridional circulations that develop within the tropopause transition layer (TTL) in response to momentum transport by Rossby waves generated by tropical convection. Results of a series of global scale model runs designed to test this hypothesis will be presented. In addition, reanalyses vertical velocity data will be examined for evidence of the expected correlation between large-scale rising motion within the TTL and tropical convection. Once moisture is present near the cold-point tropopause, large-scale cooling is required to initiate tropopause cirrus formation. One source of this cooling is stratospheric tropical waves induced by tropical convection, as we will show using a time series of radiosonde temperature data superimposed with data on cloud occurrence from the DOE ARM Nauru99 field experiment. Observations of the global characteristics of these waves from a longer time series of reanalysis data will also be presented.

Boehm, Matthew T.↗

DOE OSTI2025

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)↗

NASA NTRS2020

Model Design and Pre-Test CFD Analysis for a Supersonic Retropropulsion Wind Tunnel Test

Future Mars human lander missions will require using powered descent beginning at supersonic conditions, something which has never been done before at Mars. Significant aerosciences challenges exist due to interactions between the retrorocket exhaust plumes and the freestream flow that alter the aerodynamic behavior of the powered descent vehicle. Historically, wind tunnel tests have been used to study supersonic retropropulsion with inert gas exhaust simulants. Also, SpaceX has successfully decelerated the Falcon 9 first stage numerous times by using powered flight at supersonic conditions. On the computational side, Reynolds-Averaged Navier-Stokes flowfield simulations are regularly completed at full-scale conditions. However, the available ground and flight data do not provide a basis for calibrating the computational uncertainties for aerodynamic interference forces and moments on proposed Mars descent vehicles, either because of insufficient data or dissimilar vehicles geometries and/or conditions. Thus, additional ground testing is needed to continue addressing the aerosciences risks for large-scale human Mars landers. To that end, a retropropulsion wind tunnel test will be conducted in the NASA Langley Unitary Plan Wind Tunnel in 2020. The test is designed to improve upon similar past tests, both in terms of model design and measured data. The test campaign will use subscale model geometries derived from the two current NASA powered descent reference vehicles: a blunt low lift-to-drag vehicle and a more slender geometry. This paper covers the reference vehicles, test objectives, model design, scaling parameters, test matrix, and computational analysis to date.

Karl T Edquist↗

NASA NTRS2022

The Earth Model Column Collaboratory (EMC2) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Earth Model Column Collaboratory↗

DOE OSTI2025

Identification and Classification of Fungal GPCR Gene Families

G protein-coupled receptors (GPCRs) are transmembrane proteins crucial for signal transduction in eukaryotes, responding to diverse extracellular signals. Researchers have found and systematically summarized 14 distinct types of GPCRs in fungi but their distribution among numerous fungal species remained largely unexamined. Additionally, three families of mammalian homologs (Rhodopsin, Glutamate, and Frizzled) have been found in previous studies, but they are not included in the systematic classification of fungal GPCRs. Our study establishes a unified classification of 17 GPCR classes in fungi, combining 14 fungal and 3 mammalian previously recognized groups, and classifies 28,294 GPCRs across 1357 fungal species, significantly expanding the scale of GPCRs in fungi and demonstrating their broader distribution. We found that mammalian homologs are notably more prevalent in Early Diverging Fungi (EDF), whereas the previous 14 classes are predominantly found in Ascomycota and Basidiomycota. The most abundant class detected in fungi was Pth11-like GPCRs, exclusively found in Pezizomycotina and involved in fungal pathogenicity. Our analysis suggested that Pezizomycotina ancestor possessed an extensive array of Pth11-like GPCRs, but over time, some species underwent considerable reductions in these GPCRs in conjunction with genome contractions. Utilizing a custom-built convolutional neural network (CNN) for the identification of fungal GPCRs, we identified several putative novel fungal GPCRs. Predicted interactions between these prospective new GPCRs and G-alpha proteins, as simulated by AlphaFold Multimer, provided additional support for their functional relevance. In conclusion, our work defines the first large-scale, unified classification of fungal GPCRs, reveals lineage-specific expansions and contractions, and uncovers previously unrecognized GPCR candidates with potential functional roles in fungal signaling.

G protein-coupled receptors↗