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At least 163 records · Page 9

Local Structure Analysis and Modelling of Lignin‐Based Carbon Composites through the Hierarchical Decomposition of the Radial Distribution Function

Abstract Carbonized lignin has been proposed as a sustainable and domestic source of activated, amorphous, graphitic, and nanostructured carbon for many industrial applications as the structure can be tuned through processing conditions. However, the inherent variability of lignin and its complex physicochemical structure resulting from feedstock and pulping selection make the Process‐Structure‐Property‐Performance (PSPP) relationships hard to define. In this work, radial distribution functions (RDFs) from synchrotron X‐ray and neutron scattering of lignin‐based carbon composites (LBCCs) are investigated using the Hierarchical Decomposition of the Radial Distribution Function (HDRDF) modelling method to characterize the local atomic environment and develop quantitative PSPP relationships. PSPP relationships for LBCCs defined by this work include crystallite size dependence on lignin feedstock as well as increasing crystalline volume fraction, nanoscale composite density, and crystallite size with increasing reduction temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Upgrading biocrude oil into sustainable aviation fuel using zeolite-supported iron-molybdenum carbide nanocatalysts

Food waste is an underdeveloped source for production of sustainable aviation fuel (SAF). Now, there is no certified conversion process of food waste for SAF by American Society for Testing and Materials (ASTM). We report the use of zeolite-supported molybdenum carbide nanocatalysts in upgrading biocrudes, produced from food wastes through HTL, into SAF precursors. Our data show a complete removal of oxygen from the biocrude through hydrodeoxygenation and a higher heating value of 46.5 MJ/kg, which is comparable to that of Jet A (46.1 MJ/kg). The prescreening tests (tier alpha and beta) show the average carbon number of the distillation cut (150° to 230°C) of upgraded fuel is 10.6, close to the value of 11.4 for average conventional jet fuel, and the specifications of properties including surface tension, viscosity, heating value, flash point, and freezing point were found to meet the standards of SAF. The metal carbide nanocatalysts were reusable in upgrading tests, and the activity of deoxygenation was retained.

10 SYNTHETIC FUELS↗

Root water uptake of biofuel crops revealed by coupled electrical resistivity and soil water content measurements

Abstract Biofuel crops, including annuals such as maize ( Zea mays L.), soybean [ Glycine max (L.) Merr.], and canola ( Brassica napus L.), as well as high‐biomass perennial grasses such as miscanthus ( Miscanthus × giganteus J.M. Greef & Deuter ex Hodkinson & Renvoiz), are candidates for sustainable alternative energy sources. However, large‐scale conversion of croplands to perennial biofuel crops could have substantial impacts on regional water, nutrient, and C cycles due to the longer growing seasons and differences in rooting systems compared with most annual crops. However, due to the limited tools available to nondestructively study the spatiotemporal patterns of root water uptake in situ at field scales, these differences in crop water use are not well known. Geophysical imaging tools such as electrical resistivity (ER) reveal changes in water content in the soil profile. In this study, we demonstrate the use of a novel coupled hydrogeophysical approach with both time domain reflectometry soil water content and ER measurements to compare root water uptake and soil properties of an annual crop rotation with the perennial grass miscanthus, across three growing seasons (2009–2011) in southwest Michigan, USA. We estimated maximum root depths to be between 1.2 and 2.2 m, with the vertical distribution of roots being notably deeper in 2009 relative to 2010 and 2011, likely due to the drought conditions during that first year. Modeled cumulative ET of both crops was underestimated (2–34%) relative to estimates obtained from soil water drawdown in prior studies but was found to be greater in the perennial grass than the annual crops, despite shallower modeled rooting depths in 2010 and 2011.

Kuhl, Alexandria S.↗

Traversable wormhole solution with a background Kalb–Ramond field

Highlights: • Wormhole solutions of gravity in a Lorentz breaking symmetry scenario are found. • Light deflection by the wormhole in a Lorentz breaking symmetry scenario is calculated. • It is shown the influence of the vacuum expectation value of a Kalb–Ramond field in deflection of light. We obtain a static spherically symmetric wormhole solution due to the vacuum expectation value (vev) of a Kalb–Ramond field. The Kalb–Ramond (vev) is a background tensor field which produces a local Lorentz symmetry breaking (LSB) of spacetime. Considering a non-minimal coupling between the Kalb–Ramond (vev) and the Ricci tensor, we found an exact traversable wormhole solution sustained by matter sources with a negative isotropic pressure. The matter source satisfies the energy conditions at the throat for particular choices of the LSB parameter. Moreover, we employ the Gauss–Bonnet method to analyze the deflection angle of light in the weak limit approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Battery passports for promoting electric vehicle resale and repurposing

Starting in 2026, most batteries sold in the European Union will require a battery passport. This initiative is part of a broader legislative framework, led by the European Commission, to improve sustainable battery materials sourcing practices and enable a circular economy. All batteries having a capacity of greater than 2 kilowatt-hours will be covered under the legislation, effectively encompassing all electric vehicle (EV) batteries and stationary grid storage batteries. At its core, a battery passport defines a minimum, standard set of information that must be reported for every battery made and sold (see Figure 1). Legislative actions have so far focused on labeling standards enabling raw material traceability and recycling, which has received ongoing support from the European Council and Parliament. Furthermore, work remains to finalize the electrochemical performance and durability minimum reporting requirements by 2024, which has been challenging since performance and durability are subject to many different interpretations.

25 ENERGY STORAGE↗

Sparsely Dispersed CeO x ‑Stabilized Pt Nanoparticles Overcome Pt Loading–Durability Trade-Off for Highly Durable Heavy-Duty Fuel Cells

Proton-exchange-membrane fuel cells (PEMFCs) are clean and sustainable mobile power sources for transportation. Recently, their deployment in heavy-duty vehicles (HDVs) has attracted growing interest owing to their high energy scalability and lower infrastructure requirements. However, to meet the stringent requirements for efficiency and long-term durability for HDV applications, PEMFCs typically employ a relatively high platinum group metal (PGM) loading (>0.2 mg PGM /cm 2 ). This elevated PGM loading significantly increases the stack and system costs, surpassing the U.S. Department of Energy (DOE) target of $\$ 60$/kW for commercial viability. Reducing PGM loading while maintaining performance and durability remains a central challenge for HDV fuel cells. Here we exploit metal oxide–Pt interactions and utilize the strong CeO x –Pt interaction to design a CeO x @Pt catalyst structure with exceptional durability. At a low total PGM loading (0.1 mg PGM /cm 2 ), the CeO x @Pt/C catalyst demonstrates high fuel cell performance (8.8 kW/g PGM ) and stability (power retention >90%) after the challenging HDV durability testing (90,000 accelerated-stress-test cycles). With the CeO x @Pt/C catalyst, we showcase over 70% reduction in Pt cost from the M2FCT target (to $\$ 9$/kW), highlighting its promising potential for enabling stable and cost-effective fuel cell systems for heavy-duty applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observed declines in leaf nitrogen explained by photosynthetic acclimation to CO 2

Widespread evidence of decreasing leaf nutrients has raised concerns about ecosystem productivity under global change. Interpreting trends in leaf nutrients has important implications for the fate of ecosystem services, particularly the role of forests in mitigating climate change and sustaining quality food sources. Here, we challenge the common interpretation that decreasing leaf nitrogen concentration (LNC) is evidence of increasing nutrient limitations on ecosystem primary productivity. Instead, we show that declines in LNC (4% decrease per 50 ppm CO 2 increase), observed across 409 European forest plots over 22 y, can be explained by reduced photosynthetic nitrogen demand. This regional trend is consistent with leaf acclimation to increasing atmospheric CO 2 according to optimality theory. This finding suggests that enhanced photosynthetic nitrogen use efficiency due to CO 2 fertilization may lead to less nitrogen uptake and/or reallocation of nitrogen for plant growth and other functions. Our results have large implications for understanding and simulating interactions between ecosystem nitrogen and carbon cycles and suggest nitrogen requirements for terrestrial carbon uptake under elevated CO 2 may be lower than previously thought.

CO2 fertilization↗

Experiments on excitation of Alfvén eigenmodes by alpha-particles with bump-on-tail distribution in JET DTE2 plasmas

Dedicated experiments were performed in JET DTE2 plasmas for obtaining an α-particle bump-on-tail (BOT) distribution aiming at exciting Alfvén eigenmodes (AEs). Neutral beam injection-only heating with modulated power was used so that fusion-born α-particles were the only ions present in the MeV energy range in these DT plasmas. The beam power modulation on a time scale shorter than the α-particle slowing down time was chosen for modulating the α-particle source and thus sustaining a BOT in the α-particle distribution. High-frequency modes in the toroidicity-induced Alfven eigenmode (TAE) frequency range and multiple short-lived modes in a wider frequency range have been detected in these DT discharges with interferometry, soft x-ray cameras, and reflectometry. The modes observed were localised close to the magnetic axis and were not seen in the Mirnov coils. Analysis with the TRANSP and Fokker-Planck FIDIT codes confirms that α-particle distributions with BOT in energy were achieved during some time intervals in these discharges though no clear correlation was found between the times of the high-frequency mode excitation and the BOT time intervals. The combined magneto-hydrodynamic (MHD) and kinetic modelling studies show that the high-frequency mode in the TAE frequency range is best fitted with a TAE of toroidal mode number n= 9. This mode is driven mostly by the on-axis beam ions while the smaller drive due to the pressure gradient of α-particles allows overcoming the marginal stability and exciting the mode. The observed multiple short-lived modes in a wider frequency range are identified as the on-axis kinetic AEs predicted in Rosenbluth and Rutherford.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Alfvén eigenmode-driven zonal modes saturate and heat thermal ions by cross-scale interactions

In scenarios where a sustained energetic particle source strongly drives toroidal Alfvén eigenmodes (TAE), and phase-space transport is insufficient to saturate TAE, this novel theory of TAE-zonal mode (ZM)-turbulence—self-regulated by cross-scale interactions (including collisionless ZF damping) – merits consideration. Zonal modes are driven by Reynolds and Maxwell stresses, without the onset of modulational instability. TAE evolution in the presence of ZMs conserves energy and closes the system feedback loop. The saturated zonal shears can be sufficient to suppress ambient drift-ion temperature gradient (ITG) turbulence, achieving an enhanced core confinement regime. The saturated state is regulated by linear and turbulent zonal flow drag. This regulation leads to bursty TAE spectral oscillations, which overshoot while approaching saturation. Heating by both collisional and collisionless ZM damping deposits alpha particle energy into the thermal plasma, achieving effective alpha channeling. This theory offers a mechanism for EP-induced transport barrier formation, and predicts a novel thermal ion heating mechanism.

ITB↗

Identifying Spectral Descriptors for Protonation in BaZr 0.8 Y 0.2 O 3-x with Electron Energy Loss Spectroscopy

Hydrogen economy is of paramount importance in the global transition to a sustainable, clean energy source that contributes to decarbonization efforts. In particular, the proton conducting proton ceramic fuel cells (PCFCs) play a crucial role in promoting hydrogen energy technology [1-5]. In a PCFC, the electrolyte is typically a solid oxide material that enables proton transport and can operate at temperatures lower than those of traditional oxygen ion conducting fuel cells [6]. The reduced operating temperature of PCFCs contributes to their durability, scalability, and efficiency [7,8]. BaZr 0.8 Y 0.2 O 3-x (BZY) is a promising proton conducting solid oxide electrolyte [9,10]. The emphasis on proton conductivity entails the importance of understanding proton content in the system. However, previous studies have largely relied on bulk techniques such as electrochemical impedance spectroscopy [7,11], Karl-Fischer titration [12,13], and thermogravimetric analysis [14] to obtain proton concentration. This is due to the small atomic size and light mass of hydrogen species making direct detection challenging. Bulk methods may be useful in estimating the proton content; however, it overlooks possible proton concentration gradient or segregation that may occur across or within a nanoparticle, especially when proton incorporation occurs nonuniformly through steam exposure on powder samples. In this paper, BZY is protonated at an estimated 0.15 mol of protons via steam exposure. Electron energy loss spectroscopy (EELS) with nanoscale spatial resolution is explored to identify proxy signals for proton detection using a JEOL ARM300 microscope operated at 300 kV with a Gatan GIF Continuum detector.

08 HYDROGEN↗

Bioproduction of cerium-bearing magnetite and application to improve carbon-black supported platinum catalysts

Biogeochemical processing of metals including the fabrication of novel nanomaterials from metal contaminated waste streams by microbial cells is an area of intense interest in the environmental sciences. Here we focus on the fate of Ce during the microbial reduction of a suite of Ce-bearing ferrihydrites with between 0.2 and 4.2 mol% Ce. Cerium K-edge X-ray absorption near edge structure (XANES) analyses showed that trivalent and tetravalent cerium co-existed, with a higher proportion of tetravalent cerium observed with increasing Ce-bearing of the ferrihydrite. The subsurface metal-reducing bacterium Geobacter sulfurreducens was used to bioreduce Ce-bearing ferrihydrite, and with 0.2 mol% and 0.5 mol% Ce, an Fe(II)-bearing mineral, magnetite (Fe(II)(III) 2 O 4 ), formed alongside a small amount of goethite (FeOOH). At higher Ce-doping (1.4 mol% and 4.2 mol%) Fe(III) bioreduction was inhibited and goethite dominated the final products. During microbial Fe(III) reduction Ce was not released to solution, suggesting Ce remained associated with the Fe minerals during redox cycling, even at high Ce loadings. In addition, Fe L 2,3 X-ray magnetic circular dichroism (XMCD) analyses suggested that Ce partially incorporated into the Fe(III) crystallographic sites in the magnetite. The use of Ce-bearing biomagnetite prepared in this study was tested for hydrogen fuel cell catalyst applications. Platinum/carbon black electrodes were fabricated, containing 10% biomagnetite with 0.2 mol% Ce in the catalyst. The addition of bioreduced Ce-magnetite improved the electrode durability when compared to a normal Pt/CB catalyst. Different concentrations of Ce can inhibit the bioreduction of Fe(III) minerals, resulting in the formation of different bioreduction products. Bioprocessing of Fe-minerals to form Ce-containing magnetite (potentially from waste sources) offers a sustainable route to the production of fuel cell catalysts with improved performance.

59 BASIC BIOLOGICAL SCIENCES↗

Cryogenic Carbon Capture™ (CCC) Status Report

The Cryogenic Carbon Capture™ (CCC) process separates CO2 from light gases in essentially any continuous process. CCC cools the gases to the frost or desublimation point of CO2 (-100 to -135 °C), separates and pressurizes the solids, and warms all streams to produce a CO2-depleted stream at ambient pressure and a pure (99+%) pressurized liquid CO2 stream typically to about 150 bar, both at ambient temperature. The process also recovers all gas moisture and most gas impurities less volatile than CO2 (NOx, SOx, Hg, PM, UHC, CCC, etc.) in separable streams. CCC nearly eliminates refrigeration energy for sensible temperature changes through heat integration. CCC does require energy to change the CO2 phase from a mixed vapor to a pressurized fluid, which represents the minimum energy required of any process for this separation. CCC uses additional energy for turbomachinery inefficiencies, heat losses, moisture removal and overall process pressure drop. Aside from these real-world energy demands, CCC operates near the minimum energy required to perform this gas separation by minimizing stream recycling. CCC compresses CO2 as a liquid, which is one of several reasons it costs about about half as much and consumes about half as much energy as an amine process when using flue gases with about 15% CO2. The process also has several major additional advantages, including (a) it is a bolt-on retrofit technology that does not need steam or any modification of existing equipment, (b) it recovers water and nearly all pollutants in addition to CO2 from the flue gas, (c) it enables highly efficient and cost effective energy storage at grid scale and on time scales of minutes, (d) it enables NG storage if the energy storage option is used, and (d) it has a small footprint and is minimally disruptive to existing plants, requiring only electrical power and a gas source to operate. Sustainable Energy Solutions (SES) has scaled this technology through several levels, the largest of which captures nominally 1 tonne of CO2/day and is called the skid system. Skid system field tests include utility-scale power plants, cement plants, heating plants, and other utility or industrial sites that burn natural gas, biomass, coal, shredded tires, municipal waste, and combinations of these fuels. These field tests produced 95-99% CO2 capture with CO2 purities of 99+% and initial CO2 contents that range from 4 to 28%. SES currently seeks to scale the system to merchant scale (10-80 tonnes of CO2 per day). In the process of doing so, SES has demonstrated the potential for CCC to contribute to energy storage and direct air capture in innovative and cost-effective ways. This presentation discusses the overall process and highlights results from field and in-house tests. These include (a) measured CO2 capture rates and operating conditions from in-house and field tests, and (b) predicted utility-scale costs and energy demands. This discussion also includes the application of the CCC technology to energy storage and direct air capture.

20 FOSSIL-FUELED POWER PLANTS↗

Quantum Optimization: Potential, Challenges, and the Path Forward

Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum algorithms has developed in many areas, with optimization being one of the most pronounced domains. Across computer science and physics, there are a number of algorithmic approaches, often with little linkage. This is further complicated by the fragmented nature of the field of mathematical optimization, where major classes of optimization problems, such as combinatorial optimization, convex optimization, non-convex optimization, and stochastic extensions, have devoted communities. With these aspects in mind, this work draws on multiple approaches to study quantum optimization. Provably exact versus heuristic settings are first explained using computational complexity theory — highlighting where quantum advantage is possible in each context. Then, the core building blocks for quantum optimization algorithms are outlined to subsequently define prominent problem classes and identify key open questions that, if answered, will advance the field. The effects of scaling relevant problems on noisy quantum devices are also outlined in detail, alongside meaningful benchmarking problems. We underscore the importance of benchmarking by proposing clear metrics to conduct appropriate comparisons with classical optimization techniques. Lastly, we highlight two domains – finance and sustainability – as rich sources of optimization problems that could be used to benchmark, and eventually validate, the potential real-world impact of quantum optimization.

97 MATHEMATICS AND COMPUTING↗

Editorial: Advances in observations and modeling of snow, forest-snow processes and snow hydrology

Seasonal snowpack plays a pivotal role in the regional water cycle. In Western mountainous regions, where precipitation predominantly occurs as snow during winter and is limited in the summer months when water demand peaks, snowpack serves as a critical water source essential for sustaining water supply, ecosystems, agriculture, and industries. Additionally, snowpack dynamically influences extreme events, such as floods, droughts, and wildfires, through intricate land-atmosphere feedback. Nevertheless, significant knowledge gaps persist within this field due to data limitations and the complexity of the physics involved in modeling snow and snow hydrology (i.e., snow acts as a critical upstream hydrological process). Here, this research topic presents a collection of manuscripts that address some of these important research gaps.

54 ENVIRONMENTAL SCIENCES↗

Intraseasonal Variations in Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20oN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Ramey, Holly S.↗

Relationships Between Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes on Intraseasonal Time Scales

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20oN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Ramey, Holly S.↗

Relationships Between Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes on Intraseasonal Time Scales

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20degN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Ramey, Holly S.↗

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Spear, Ashley D.↗