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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Optimal Frequency-domain Analysis for Spacecraft Time Series: Introducing the Missing-data Multitaper Power Spectrum Estimator

While the Lomb–Scargle periodogram is foundational to astronomy, it has a significant shortcoming: the variance in the estimated power spectrum does not decrease as more data are acquired. Statisticians have a 60 yr history of developing variance-suppressing power spectrum estimators, but most are not used in astronomy because they are formulated for time series with uniform observing cadence and without seasonal or daily gaps. Here we demonstrate how to apply the missing-data multitaper power spectrum estimator to spacecraft data with uniform time intervals between observations but missing data during thruster fires or momentum dumps. The F-test for harmonic components may be applied to multitaper power spectrum estimates to identify statistically significant oscillations that would not rise above a white noise–based false alarm probability. Multitapering improves the dynamic range of the power spectrum estimate and suppresses spectral window artifacts. We show that the multitaper–F-test combination applied to Kepler observations of KIC 6102338 detects differential rotation without requiring iterative sinusoid fitting and subtraction. Significant signals reside at harmonics of both fundamental rotation frequencies and suggest an antisolar rotation profile. Next we use the missing-data multitaper power spectrum estimator to identify the oscillation modes responsible for the complex "scallop-shell" shape of the K2 light curve of EPIC 203354381. We argue that multitaper power spectrum estimators should be used for all time series with regular observing cadence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Multi frame synchrotron radiography of pulsed power driven underwater single wire explosions

We present herein the first use of synchrotron-based phase contrast radiography to study pulsed-power driven high energy density physics experiments. Underwater electrical wire explosions have become of interest to the wider physics community due to their ability to study material properties at extreme conditions and efficiently couple stored electrical energy into intense shock waves in water. The latter can be shaped to provide convergent implosions, resulting in very high pressures (1-10 Mbar) produced on relatively small pulsed power facilities (100s of kA-MA). Multiple experiments have explored single-wire explosions in water, hoping to understand the underlying physics and better optimize this energy transfer process; however, diagnostics can be limited. Optical imaging diagnostics are usually obscured by the shock wave itself; and until now, diode-based X-ray radiography has been of relatively low resolution and rather a broad x-ray energy spectrum. Utilising phase contrast imaging capabilities of the ID19 beamline at the European Synchrotron Radiation Facility, we were able to image both the exploding wire and the shock wave. Probing radiation of 20-50 keV radiographed 200 μm tungsten and copper wires, in ~2-cm diameter water cylinders with resolutions of 8 μm and 32 μm. The wires were exploded by a ~30-kA, 500-ns compact pulser, and 128 radiographs, each with a 100-ps X-ray pulse exposure, spaced at 704 ns apart were taken in each experiment. Abel inversion was used to obtain the density profile of the wires, and the results are compared to two dimensional hydrodynamic and one dimensional magnetohydrodynamic simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel’dovich effect

Optimal analyses of many signals in the cosmic microwave background (CMB) require map-level extraction of individual components in the microwave sky, rather than measurements at the power spectrum level alone. To date, nearly all map-level component separation in CMB analyses has been performed exclusively using satellite data. In this paper, we implement a component separation method based on the internal linear combination (ILC) approach which we have designed to optimally account for the anisotropic noise (in the 2D Fourier domain) often found in ground-based CMB experiments. Using this method, we combine multi-frequency data from the Planck satellite and the Atacama Cosmology Telescope Polarimeter (ACTPol) to construct the first wide-area, arcminute-resolution component-separated maps (≈ 2100 sq. deg.) of the CMB temperature anisotropy and the thermal Sunyaev-Zel'dovich (tSZ) effect sourced by the inverse-Compton scattering of CMB photons off hot, ionized gas. Our ILC pipeline allows for explicit deprojection of various contaminating signals, including a modified blackbody approximation of the cosmic infrared background (CIB) spectral energy distribution. The cleaned CMB maps will be a useful resource for CMB lensing reconstruction, kinematic SZ cross-correlations, and primordial non-Gaussianity studies. Here, the tSZ maps will be used to study the pressure profiles of galaxies, groups, and clusters through cross-correlations with halo catalogs, with dust contamination controlled via CIB deprojection. The data products described in this paper are available on LAMBDA.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Real-Time Lifetime Prediction of Semiconductor Devices Using Hardware-in-the-Loop

This paper presents a unique approach to enable real-time lifespan prediction of semiconductor power modules using a Hardware-in-the-Loop (HIL) system. By integrating the module's overall loss characteristics-specifically switching and conduction losses-with a thermoelectric model of the thermal management system, this research demonstrates that the model can dynamically estimates the junction temperature profile of the semiconductor devices in response to a changing torque demand profile for the motor drive system. This capability enables continuous monitoring of the module's operational time and cumulative stress induced on the devices to compute accumulated remaining lifetime or time-to-failure (TTF). This study provides an architectural framework for the HIL system with high-fidelity component models of multiple physical domains, allowing simulation of dynamic behaviors of a closely-coupled motor drive system. The advanced real-time computation and measurement functionalities of the HIL system allow for both dynamic lifetime calculations based on simulated data and aggregate lifetime predictions utilizing historical data. Moreover, this paper details an algorithm that not only computes cumulative damage but also synthesizes these data into a comprehensive aggregated lifetime metric. This methodology can enhance the maintenance scheduling strategies and operational reliability of semiconductor devices in critical applications, ultimately extending their service life while optimizing performance.

hardware-in-the-loop (HIL)↗
DOE OSTI2022

Dynamic Modeling, Parameter Estimation, and Data Reconciliation of a Supercritical Pulverized Coal-Fired Boiler

A high-fidelity, spatially distributed dynamic model of a supercritical pulverized coal-fired boiler was developed for calculating transient thermal profiles of the boiler tubes, which are often not measured or unmeasurable in industrial settings due to the harsh operating conditions. In this work, rigorous models of the subcritical and supercritical steam properties, which can be highly nonlinear, were used to capture the transition between two-phase and one-phase flow, respectively, as supercritical boilers frequently transition through the critical point during load-following operation. The transient boiler model was also used for data reconciliation and parameter estimation for the purpose of model validation against industrial data. An approach was developed to reduce the size of large-scale reconciliation problem by focusing on the implementation of bias terms for the reconciled variables, which can be estimated in place of the reconciled variables themselves. In addition, a functional approximation of the reconciliation problem was defined so that it can be more simply optimized. Combining this functional approximation optimization with reformulation of the reconciliation problem considering measurement biases can significantly improve the tractability of many such large-scale problems. The validated boiler model was then used to study transient responses under load-following operation with specific attention on the calculation of unmeasurable variables.

42 ENGINEERING↗
DOE OSTI2015

GAMMA RAYS FROM TYPE Ia SUPERNOVA SN 2014J

The whole set of INTEGRAL observations of Type Ia supernova SN 2014J, covering the period 19–162 days after the explosion, has been analyzed. For spectral fitting the data are split into early and late periods covering days 19–35 and 50–162, respectively, optimized for {sup 56}Ni and {sup 56}Co lines. As expected for the early period, much of the gamma-ray signal is confined to energies below ∼200 keV, while for the late period it is strongest above 400 keV. In particular, in the late period, {sup 56}Co lines at 847 and 1248 keV are detected at 4.7σ and 4.3σ, respectively. The light curves in several representative energy bands are calculated for the entire period. The resulting spectra and light curves are compared with a subset of models. We confirm our previous finding that the gamma-ray data are broadly consistent with the expectations for canonical one-dimensional models, such as delayed detonation or deflagration models for a near-Chandrasekhar mass white dwarf. Late optical spectra (day 136 after the explosion) show rather symmetric Co and Fe line profiles, suggesting that, unless the viewing angle is special, the distribution of radioactive elements is symmetric in the ejecta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Accelerating the identification of novel secondary metabolites in bioenergy plant root exudates using MicroED

Small molecule metabolites drive inter- and intraspecies communication and dependencies in diverse biological systems, yet a large proportion of these important chemical compounds remain uncharacterized in plants and microbes. Approximately 90% of the metabolites in root exudate profiles are unknown compounds, despite the importance of root exudate composition in plant-microbe interactions. We need advanced analytical capabilities that will support rapid discovery and structural elucidation of metabolites from biological samples that may be limited in quantity and high in complexity. To fill this gap, this project aimed to develop an integrated workflow involving metabolite extraction, separation, and crystallization from plant root exudates followed by characterization using nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and microcrystal electron diffraction (MicroED). Using crude root exudates from sorghum, this project successfully developed higher throughput exudate fractionation strategies to obtain pure compounds for crystallization and identified crystals in multiple fractions that diffracted. Additional efforts to increase the throughput of high-quality crystal generation for MicroED, such as crystallization screening and crystallization chaperone exploration, will be needed to further advance root exudate metabolite identification. The overall optimized sample preparation process can then be integrated with the existing data collection and data analysis pipelines for MicroED at PNNL to facilitate more rapid natural product discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Comparative analysis of silicon and black phosphorous as an add-layer in nanomaterial based plasmonic sensor

In the proposed article silicon and black phosphorous as an add-layer above the plasmonic metal in nanomaterial (graphene and MoS{sub 2}) based plasmonic sensor are compared. The reflectance curves are obtained for different thickness of silicon and black phosphorous by using transfer matrix method. The performance defining parameters i.e. shift in resonance angle, beam width of reflectance curve, and minimum reflectance intensity for a minute change of 0.005 in refractive index of sensing medium at the optimized thickness 5 nm of silicon and black-phosphorous, and conventional are (13.86, 10.96, 2.415), (4.956, 3.817, 1.419), and (0.012, 0.002, 0.002) respectively. Further, the addition of nanomaterials increases these parameters and generally follows the order MoS{sub 2}-graphene > MoS{sub 2} > graphene. Furthermore, transverse-magnetic electric field shows that nanomaterial covered silicon have higher penetration depth than the nanomaterial covered black-phosphorous. The analysis shows that nanomaterial covered silicon can replace nanomaterial covered black-phosphorous in terms of higher sensitivity and penetration depth.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Flexible Grid-Based Electrolysis Hydrogen Production for Fuel Cell Vehicles Reduces Costs and Greenhouse Gas Emissions

Hydrogen fuel cell electric vehicles (FCEVs) have been proposed as an option for lowering carbon dioxide (CO 2 ) and pollutants emissions from the transportation sector, when implemented in combination with green hydrogen production methods such as water electrolysis powered by renewable electricity. FCEVs also have the added advantages of high specific energy density and rapid refueling, two important challenges that battery electric vehicles have not yet fully overcome. Moreover, flexible operation of electrolysis could support the grid and lower electricity costs. In this paper, we simulate time-varying FCEV hydrogen refueling demand for light, medium- and heavy-duty vehicles met using electrolysis systems distributed throughout the Western U.S. power system. We find that by oversizing electrolyzers the resulting load flexibility results in different hydrogen generation temporal profiles, average electricity costs, renewable curtailment levels, and CO2 emissions. Our results indicate that increasing hydrogen production flexibility lowers hydrogen and electricity generation cost and CO 2 emissions, but there is a tradeoff between lowering operational cost and increasing electrolyzer capital cost, yielding a minimum total system cost at a size corresponding to between 80% and 90% annual capacity factor assuming a future electrolyzer cost of $300/kW.

25 ENERGY STORAGE↗
DOE OSTI2019

Transfer of autocollimator calibration for use with scanning gantry profilometers for accurate determination of surface slope and curvature of state-of-the-art x-ray mirrors

X-ray optics, desired for beamlines at free-electron-laser and diffraction-limited-storage-ring x-ray light sources, must have almost perfect surfaces, capable of delivering light to experiments without significant degradation of brightness and coherence. To accurately characterize such optics at an optical metrology lab, two basic types of surface slope profilometers are used: The long trace profilers (LTPs) and nanometer optical measuring (NOM) like angular deflectometers, based on electronic autocollimator (AC) ELCOMAT-3000. The inherent systematic errors of the instrument's optical sensors set the principle limit to their measuring performance. Where autocollimator of a NOM-like profiler may be calibrated at a unique dedicated facility, this is for a particular configuration of distance, aperture size, and angular range that does not always match the exact use in a scanning measurement with the profiler. Here we discuss the developed methodology, experimental set-up, and numerical methods of transferring the calibration of one reference AC to the scanning AC of the Optical Surface Measuring System (OSMS), recently brought to operation at the ALS Xray Optics Laboratory. We show that precision calibration of the OSMS performed in three steps, allows us to provide high confidence and accuracy low-spatial-frequency metrology and not â€print into' measurements the inherent systematic error of tool in use. Here, with the examples of the OSMS measurements with a state-of-The-Art x-ray aspherical mirror, available from one of the most advanced vendors of X-ray optics, we demonstrate the high efficacy of the developed calibration procedure. The results of our work are important for obtaining high reliability data, needed for sophisticated numerical simulations of beamline performance and optimization of beamline usage of the optics. This work was supported by the U. S. Department of Energy under contract number DE-AC02-05CH11231.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Stress Relaxation Related to Spontaneous Thin Film Buckling: Correlation between Finite Element Calculations and Micro Diffraction Analysis

Compressive residual stresses generated during thin film deposition may lead to undesirable film damage, such as delamination, buckling, and flaking, ultimately leading to the failure of the device employing the film. Understanding the residual stress generation and role in these damage mechanisms is necessary to preserve thin film integrity and optimize its functional properties. Thin shell theory has been used for decades to predict buckling but the results have not yet been correlated with experimental data since the techniques used to measure stress in metallic films were not able to do so at the required micron scale until recently. Micro scanning X-ray diffraction now enables the direct mapping of the local stress of metallic films. In this paper, finite element method based on thin shell theory and synchrotron X-ray micro diffraction have been used to determine stress maps of thin film buckling patterns. Calculations of the stress distribution in the metallic films have been performed taking into account the buckling geometry determined from optical measurements. Stress distributions over gold blisters and tungsten wrinkles obtained with the two techniques are in fair agreement and allow for the accurate determination of the stress relaxation profile from the bottom to the top of the buckling, validating the thin shell theory model.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Multi-Analysis Approach for Estimating Regional Health Impacts from the 2017 Northern California Wildfires

In the evening of October 8 and early hours of October 9, 2017, high winds in Northern California downed trees and power lines, igniting some of the most devastating wildfires the state had seen, and within hours unhealthy air quality impacted millions of people. We simulated these air quality conditions using fire detection information from the MODIS, VIIRS, and GOES-16 ABI satellite instruments, and applying a set of three WRF–CMAQ simulations, one data fusion, and three machine learning methods. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ air quality modeling system. Interestingly, this approach did not necessarily improve results compared to the baseline case, which used a default time profile. However, this approach was key to simulating the initial 12-hr explosive fire activity and smoke impacts. The WRF-CMAQ simulations compared well with observational data for the October 8-15 time period and tended to overestimate concentrations October 16-20. To improve these results, we applied three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across the WRF-CMAQ, data fusion, and machine learning datasets, the best Pearson correlation was 0.5. The data fusion and machine learning results were biased low and WRF-CMAQ results were biased high. Finally, we applied the optimized PM2.5 exposure estimate in a short-term exposure-response function. Total estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to wildland fire smoke.

O'Neill, Susan↗
DOE OSTI2019

Co-optima fuels combustion: A comprehensive experimental investigation of prenol isomers

Carbon monoxide time-histories, ignition delay times, and laminar burning velocity measurements are reported for the oxidation of 3-methyl-2-buten-1-ol (prenol) and 3-methyl-3-buten-1-ol (isoprenol). These prenols are fuel candidates outlined by the U.S. Department of Energy’s Co-Optimization of Fuels and Engines (Co-Optima) program. The laminar burning velocity measurements were conducted for two fuels with synthetic air within a constant-volume spherical combustion chamber at initial conditions of 428 K and 1 atm for a range of equivalence ratios from 0.75 to 1.50. The laminar burning velocities of the two fuels were found to be similar, and the maximum value occurred at an equivalence ratio near 1.0. Carbon monoxide time-histories and ignition delay times were recorded behind reflected shockwaves in a double-diaphragm, heated shock tube over the temperature range 1269–1472 K near 9.4 atm with a mixture of 0.05% fuel/0.35% O 2 /99.6% Ar. Comparisons with predictions of a detailed chemical kinetic mechanism from the literature were provided. Current model predictions overpredicted both the ignition delay time and the max CO yield; however, the model captured the profile of CO formation well. Detailed uncertainty and sensitivity analyses were carried out to identify important reactions that need attention for accurate prediction of these fuel’s chemistry. Further investigation into the rate of C 3 H 3 + O 2 = CH 2 CO + HCO reaction was suggested based on current experiments. In conclusion, the experimental data and analysis presented here is critical in the development, validation and improvement of kinetic models of these promising Co-Optima fuels.

09 BIOMASS FUELS↗
DOE OSTI2024

Static and Dynamic Thermomechanical Properties of Phase-Separated Epoxy Networks with Tuned Microstructures

Here, polymerization-induced phase separation is a useful method for the construction of heterogeneous epoxy networks with properties exceeding their homogeneous counterparts. In this work, we examine the static and dynamic thermomechanical properties of phase-separated epoxy networks salient to their application as encapsulants. Three heterogeneous epoxy-amine networks with nano-, meso-, and macro-phase-separated morphologies comprised of hard and soft domains are compared to a rigid, unstructured network. The glass transition profiles of the heterogeneous networks are complex, spanning many decades in the frequency domain. The nanophase-separated morphology leads to higher coefficient of thermal expansion, yet surprisingly is characterized by reduced residual stress. Under both quasi-static and dynamic compression (strain rates of order 10 –3 and 10 3 s –1 , respectively), the nanophase-separated network also exhibits higher modulus and strength. In split-Hopkinson bar experiments, the energy dissipation characteristics of the epoxy networks were nearly identical. Curiously, however, the Hugoniot response of the macro-phase-separated network determined by ballistic shockwave analysis indicates a remarkable ability of this material to mitigate shockwave propagation in comparison to many homogeneous and heterogeneous polymer materials. Collectively, this work reveals several previously unreported phenomena with respect to structure–property relationships in phase-separated epoxy networks, illustrating the potential value of systematically tuned microstructures for optimization of application-specific physical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Generation of gamma radiation by a subterawatt ultrashort laser pulse: optimisation of preplasma and pulse duration

We report an experimental and numerical study of the acceleration of electrons in a plasma interacting with a subterawatt laser pulse (intensity of ∼3 × 10{sup 18} W cm{sup −2} at a pulse duration of 50 fs). A preplasma layer on the surface of a molybdenum target is formed by an additional laser pulse with a duration of 8 ns and an intensity of ∼2 × 10{sup 12} W cm{sup −2}. It is shown that an increase in the laser pulse duration to 1700 fs at a constant energy (and a proportional decrease in intensity) leads to an increase in the yield of bremsstrahlung γ-radiation by more than an order of magnitude when the nanosecond pulse is ahead of the femtosecond one by 15 − 25 ns. Interferometry data and results of diagnostics of optical and γ-radiation of a plasma demonstrate that the collisional ionisation of atoms by electrons oscillating in the field of such a laser pulse plays an essential role in the formation of electron density profile. The sensitivity of the described effect to the level of amplified spontaneous emission is determined, despite the nanosecond pulse impact. Numerical simulations show that at a large pulse duration, the acceleration of electrons is stipulated by the beaking of plasma waves excited during stimulated Raman scattering of laser radiation. (paper)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Destruction of axion miniclusters in the Galaxy

Previously, it has been established that axion dark matter (DM) is clustered to form clumps (axion miniclusters) with masses M ≈ 10{sup –12}M{sub ⊙}. The passages of such clumps through the Earth are very rare events occurring once in 10{sup 5} years. It has also been shown that the Earth’s passage through DM streams, which are the remnants of clumps destroyed by tidal gravitational forces from Galactic stars, is a much more probable event occurring once in several years. In this paper, we have performed detailed calculations of the destruction of miniclusters by taking into account their distribution in orbits in the Galactic halo. We have investigated two DM halo models, the Navarro–Frenk–White and isothermal density profiles. Apart from the Galactic disk stars, we have also taken into account the halo and bulge stars. We show that about 2–5% of the axion miniclusters are destroyed when passing near stars and transform into axion streams, while the clump destruction efficiency depends on the DM halo model. The expected detection rate of streams with an overdensity exceeding an order of magnitude is 1–2 in 20 years. The possibility of detecting streams by their tidal gravitational effect on gravitational-wave interferometers is also considered.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Artificial Intelligence and Computer Vision for Cost-Effective Benthic Habitat Characterizations

Machine learning applied to computer vision and pattern recognition is a type of artificial intelligence that has advanced rapidly in the last 10 to 15 years, spurred forward by breakthroughs in deep convolutional neural networks. These state-of-the-art methods are poised to become widely used in environmental monitoring applications as a result of the increasing abundance of data available from different imaging platforms (e.g., fixed-point cameras, drone surveys, high-resolution satellite data) that can be analyzed to observe, model, and understand environmental conditions. Computer vision and pattern recognition (CVPR) tools advance our ability to use imagery and camera-based tools in cost-effective ways for environmental monitoring. Although these techniques offer great potential, some challenges remain, such as the need for large sets of labeled images for model training and validation and optimized hardware and software to ensure that the models can be trained effectively and in a reasonable amount of time. Here, we have overcome many of these rate-limiting challenges by using a diverse image library built across multiple projects coupled with staff expertise and onsite computing resources. We are working toward a fully automated SPI processing system and also are moving to develop CVPR analytical tools for other imaging platforms and data sets.

02 PETROLEUM↗