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At least 631 records · Page 35

Extending SLUSCHI for Automated Diffusion Calculations

We present an extension of the SLUSCHI package (Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces) to enable automated diffusion calculations from first-principles molecular dynamics. While the original SLUSCHI workflow was designed for melting temperature estimation via solid-liquid coexistence, we adapt its input and output handling to isolate the volume search stage and generate one production trajectory suitable for diffusion analysis. Post-processing tools parse VASP outputs, compute mean-square displacements (MSD), and extract tracer diffusivities using the Einstein relation with robust error estimates through block averaging. Diagnostic plots, including MSD curves, running slopes, and velocity autocorrelations, are produced automatically to help identify diffusive regimes. The method has been validated through representative case studies: self-diffusion in Al-Cu liquid alloys, sublattice melting in Li7La3Zr2O12 and Er2O3, interstitial oxygen transport in bcc and fcc Fe, and oxygen diffusivity in Fe-O liquids with variable Si and Al contents. Viscosity and diffusivity are linked through the Stokes-Einstein relation, with composition dependence assessed via simple linear mixing. This capability broadens SLUSCHI from melting-point predictions to transport property evaluation, enabling high-throughput, fully first-principles datasets of diffusion coefficients and viscosities across metals and oxides.

36 MATERIALS SCIENCE↗

Meeting sustainable aviation fuel policy targets through first generation corn biorefineries

This paper investigates options to produce low carbon and renewable aviation fuel through existing commercial first generation biorefineries, which could be strategic given the rapid growth of the electric vehicle market for personal mobility. We evaluate the environmental impact of retrofitting a first generation biorefinery to produce aviation fuel through chemical process simulation. The analysis investigates the potential for reducing greenhouse gas (GHG) emissions and displacing fossil fuel (petroleum-based jet kerosene) in the aviation fuel industry through using corn feedstocks in dry grind biorefineries to convert sugars to 1,4-dimethylcyclooctane (DMCO), which qualifies as renewable jet-A fuel blend and is infrastructure compatible. Further, the average life cycle GHG emissions for a baseline case and a scenario with carbon capture and storage (CCS) of fermentative CO 2 are 36 and 5g CO 2 e/MJ DMCO, respectively. Investment in CCS at the biorefinery and adoption of crop best management practices on farms are essential for mitigating the risks of induced land use change GHG emissions for existing corn biorefineries. DMCO as a low-carbon aviation fuel could be a strategic fuel product for retrofitting existing corn dry grind facilities. For aviation fuel supply, corn dry grind facilities could displace about 12% of jet fuel demand in the near term, which would meet sustainable aviation fuel policy targets. We conclude that corn-to-DMCO shows promise for near-term low-carbon fuel markets in the aviation industry and as a bridge to developing biomass-based jet fuel in the future.

09 BIOMASS FUELS↗

Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. Here in this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Additive manufacturing↗

Climate change is intensifying rainfall erosivity and soil erosion in West Africa

Soil erosion is a critical environmental challenge with significant implications for agriculture, water quality, and ecosystem stability. Understanding its dynamics is essential for sustainable environmental management and societal welfare. Here, we analyze rainfall erosivity and erosion patterns across West Africa (WAF) during the historical (1982–2014), near future (2028–2060), and far future (2068–2100) periods under Shared Socioeconomic Pathways (SSPs 370 and 585). Using bias-corrected-downscaled (BCD) climate models validated against reference data, we ensure an accurate representation of rainfall—a key driver of erosivity (R-factor) and soil erosion. We compare Renard's approach and the Modified Fournier Index (MFI) to calculate the R-factor and note a strong correlation. However, Renard's method shows slightly lower accuracy in Sierra Leone, Guinea, and The Gambia, likely due to its inability to capture high-intensity, short-duration rainfall events. In contrast, the MFI, utilizing continuous rain gauge data, proves more reliable for these regions. We also attribute fluctuations in erosivity, such as those seen during the 2003 West Africa floods, to synoptic weather patterns influenced by multiple climate processes. Furthermore, our analysis reveals regions where future soil erosion could exceed 20 t/ha/yr due to climate change. Under the SSP 370 scenario, soil erosion in WAF is projected to rise by 14.84 % in the near future and 18.65 % in the far future, increasing further under SSP 585 to 19.86 % and 23.49 %, respectively. The most severe increases are expected in Benin and Nigeria, with Nigeria potentially facing a 66.41 % rise in erosion by the far future under SSP 585. These findings highlight the region's exposure to intensified climatic conditions and underscore the urgent need for targeted soil management and climate adaptation strategies to mitigate erosion's ecological and socioeconomic impacts.

54 ENVIRONMENTAL SCIENCES↗

Entangled Photon Spectroscopy

Conspectus The enhanced interest in quantum-related phenomena has provided new opportunities for chemists to push the limits of detection and analysis of chemical processes. As some have called this the second quantum revolution, a time has come to apply the rules learned from previous research in quantum phenomena toward new methods and technologies important to chemists. While there has been great interest recently in quantum information science (QIS), the quest to understand how nonclassical states of light interact with matter has been ongoing for more than two decades. Our entry into this field started around this time with the use of materials to produce nonclassical states of light. Here, the process of multiphoton absorption led to photon-number squeezed states of light, where the photon statistics are sub-Poissonian. In addition to the great interest in generating squeezed states of light, there was also interest in the formation of entangled states of light. While much of the effort is still in foundational physics, there are numerous new avenues as to how quantum entanglement can be applied to spectroscopy, imaging, and sensing. These opportunities could have a large impact on the chemical community for a broad spectrum of applications. Here, we discuss the use of entangled (or quantum) light for spectroscopy as well as applications in microscopy and interferometry. The potential benefits of the use of quantum light are discussed in detail. From the first experiments in porphyrin dendrimer systems by Dr. Dong-Ik Lee in our group to the measurements of the entangled two photon absorption cross sections of biological systems such as flavoproteins, the usefulness of entangled light for spectroscopy has been illustrated. These early measurements led the way to more advanced measurements of the unique characteristics of both entangled light and the entangled photon absorption cross-section, which provides new control knobs for manipulating excited states in molecules. The first reports of fluorescence-induced entangled processes were in organic chromophores where the entangled photon cross-section was measured. These results would later have widespread impact in applications such as entangled two-photon microscopy. From our design, construction and implementation of a quantum entangled photon excited microscope, important imaging capabilities were achieved at an unprecedented low excitation intensity of 10 7 photons/s, which is 6 orders of magnitude lower than the excitation level for the classical two-photon image. New reports have also illustrated an advantage of nonclassical light in Raman imaging as well. From a standpoint of more precise measurements, the use of entangled photons in quantum interferometry may offer new opportunities for chemistry research. Experiments that combine molecular spectroscopy and quantum interferometry, by utilizing the correlations of entangled photons in a Hong–Ou–Mandel (HOM) interferometer, have been carried out. The initial experiment showed that the HOM signal is sensitive to the presence of a resonant organic sample placed in one arm of the interferometer. In addition, parameters such as the dephasing time have been obtained with the opportunity for even more advanced phenomenology in the future.

36 MATERIALS SCIENCE↗

An Evaluation of Actinide Reactivity with CO 2 , O 2 , and O 2 /He Gases using Inductively Coupled Plasma Tandem Mass Spectrometry: Application to Simultaneous Measurement of 241 Am/ 241 Pu Ratios in Unseparated Complex Matrices

Accurate actinide measurements are critical within the field of nuclear science. Traditional methods for actinide quantification require time-consuming sample processing prior to analysis. There is a need for rapid analytical techniques that still maintain a high degree of accuracy. In this work, actinide reactivity was assessed for multiple oxygen-containing reaction gases using quadrupole inductively coupled plasma tandem mass spectrometry (Q-ICP-MS/MS) to evaluate actinide analysis in complex sample matrices without analyte-matrix separation. A novel method was developed to measure 241 Am/ 241 Pu in complex sample matrices using O 2 /He reaction gas with no matrix removal or analyte pre-concentration. This inline method reduces matrix-derived polyatomic interferences that complicate traditional ICP-MS analyses by mass-shifting to 241 Am 16 O + and 241 Pu 16 O 2 + , allowing Am and Pu to be mass separated for simultaneous analysis. While mass shifting is efficient, a small portion of Am + (<1.3%) and Pu + (<1.4%) react to from AmO 2 + and PuO + , respectively. Therefore, a mass balance approach was used, in combination with reactivity determined from 242 Pu and 243 Am standard solutions, to correct for residual 241 PuO + and 241 AmO 2 + . The method was validated by measuring 241 Am/ 241 Pu in Pu isotope standards CRM-136 and CRM-137 (separated in March/April 1970 and February 2022, respectively) in both neat solutions and complex matrices containing diluted soil (NIST SRM 2711a, >1000 µg·g -1 ). Method detection limits of 15.9 and 9.6 fg·g -1 were determined for 241 Am and 241 Pu, respectively, and 241 Am/ 241 Pu ratios were measured with accuracies within <3.5%. In conclusion, this work presents the first direct analysis of 241 Am/ 241 Pu in unseparated complex matrices, advancing capabilities for rapid actinide measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetics of Direct Olefin Synthesis from Syngas over Mixed Beds of Zn–Zr Oxides and SAPO-34

A packed bed containing a physical mixture of both Zn–Zr mixed oxide catalyst and SAPO-34 converts syngas directly into a mixture of C 2 –C 5 olefins and paraffins. Specifically, the mixed oxide catalyst is responsible for intermediate oxygenate synthesis from syngas while the molecular sieve catalyzes olefin synthesis from the oxygenate intermediates. Kinetic measurements with cofed propylene over each catalyst independently confirm olefin hydrogenation activity over both components of the composite bed. The addition of either water or CO to the feed drops the activity of propylene hydrogenation over the Zn–Zr oxide. In sum, under reaction conditions of syngas feed and produced water, olefin hydrogenation predominantly occurs over the SAPO-34 catalyst, rather than over the catalyst responsible for hydrogenating CO into oxygenate intermediates. Here, a developed kinetic model consistent with this conclusion describes measurements at differing feed compositions, temperatures, space velocities, and bed catalyst mixing ratios. Technoeconomic analysis of the process indicates that the olefin-to-paraffin ratio is a key performance metric for commercial scale syngas conversion and highlights the importance of considering olefin hydrogenation rates over the molecular sieve component.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning Copolymer Microstructure Using Ring-Opening Cross-Metathesis Polymerization

The capability of ring-opening cross-metathesis (RO/CM) polymerization to produce alternating copolymers was studied. By treating commercial polybutadiene (PB) with bulky oxanorbornene monomers and Ru-based olefin metathesis catalysts, alternating copolymers were produced under mild conditions with high sequence fidelities. Here, we found that alternating copolymers could be produced starting from a variety of butadiene sources including PB, cyclooctadiene (COD), or t,t,t-1,5,9-cyclododecatriene (CDT), highlighting for the first time the kinetic pathway independence of this process. Kinetic copolymerization analysis of an oxanorbonene monomer with CDT revealed that much higher monomer conversions were obtained compared with the analogous homopolymerizations and showed evidence of alternating monomer incorporation. Copolymerization of these monomers also enabled good control when targeting different molecular weights. Copolymer thermal analysis revealed a strong correlation between thermal behavior and alternating sequence fidelity, providing a second lever beyond composition to tune thermal behavior. These data demonstrate that a broad variety of polymer microstructures can be accessed via RO/CM polymerization and highlight the potential of CDT in alternating copolymer synthesis.

Foster, Jeffrey C. [Oak Ridge National Laboratory ↗

Facile Room-Temperature Electrodeposition of Rare Earth Metals in a Fluorine-Free Task-Specific Electrolyte

Electrochemical deposition of rare earth metals at room temperature has attracted increasing interest due to its advantage in energy efficiency over traditional hydrometallurgical and pyrometallurgical processes. Recent progress has been made with fluorinated electrolyte systems; however, the formation of an electrode-passivating fluoride layer by electrolyte decomposition is often overlooked. Such a passivation layer causes significant and rapid decay of the deposition current and significantly hinders practical application. To address this issue, we demonstrate a fluorine (F)-free task-specific electrolyte utilizing the borohydride anion for the efficient electrodeposition of rare earth metals. By eliminating the passivation effect, the deposition process exhibits a stable current and accumulates a thick neodymium deposit on the electrode. Raman spectroscopy of the electrolyte reveals a synergetic effect between rare earth borohydride and lithium borohydride which promotes the dissociation of both borohydride salts, resulting in significantly increased ionic conductivity and electrochemical performance. Cyclic voltammetry and in-depth X-ray photoelectron spectroscopy of the deposits suggest that the electrodeposition of rare earth metals could undergo a Li-mediated reduction process. Finally, quantitative analysis of the deposits reveals that the overall concentration of the rare earth elements reaches 75% which contains 40–48% metallic phase.

36 MATERIALS SCIENCE↗

Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix Into the Future

The concept of sustainability inherently spans multiple spatial scales, sectors, variables, and time horizons. This study links a recently developed method of assessing present-day agricultural sustainability across environmental, economic, and social dimensions with a process-based integrated assessment model, in order to allow forward-looking analysis of sustainability by region and scenario. The sustainable agriculture matrix estimates present-day agricultural sustainability at the national level using 18 indicator variables, of which this study estimates nine to the year 2100, using an enhanced version of the Global Change Analysis Model. Scenarios include a reference scenario, and scenarios that apply the following measures, both individually and in combination, that are thought to improve sustainability: yield intensification, transition toward more plant-based (“flexitarian”) diets, and economy-wide greenhouse gas emissions mitigation. The scenarios illustrate considerable complexity and tradeoffs inherent to efforts to improve agricultural sustainability in all regions globally. For example, yield intensification typically increases nitrogen pollution, flexitarian diets can reduce agricultural output, and greenhouse gas mitigation efforts may either increase deforestation or crowd out crop and livestock production due to consequent bioenergy demands. However, there is considerable inter-regional heterogeneity in the responses, and the importance of such secondary responses also differs by region. The analysis and post-processing methods developed in this study allow quantification and visualization of the absolute and relative magnitude of the tradeoffs between agricultural sustainability indicator variables across regions, time periods, and scenarios.

54 ENVIRONMENTAL SCIENCES↗

Monitoring Seasonal Shear Wave Velocity Changes in the Top 6 m at Garner Valley in Southern California With Borehole Data

Abstract Subsurface structures play important roles in seismic ground motion, crustal hydrology, stability of the built environment, and more. Constraining temporal changes of subsurface shear wave velocity ( V S ) can provide useful information to all these topics and the growing field of hydrological monitoring with seismic velocity. Using borehole records at Garner Valley, CA, we estimate seasonal subsurface V S variations from impulse response functions (IRFs) of earthquake data (2005–2018) along with IRFs and cross‐correlation of cross‐hole experiment data (2015–2018). The inferred V S variations are up to ∼25% in the top 6 m and ∼10% at 2–5 m in depth. The V S variations correlate strongly with the water table depth changes, suggesting that the changes are mostly due to fluctuations of pore pressure in the shallow material. The shallow velocity changes alter the near‐surface conditions, can affect seismic hazard estimation, and may be improperly attributed to deeper processes without careful analysis.

58 GEOSCIENCES↗

Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed

Abstract Discontinuous permafrost environments exhibit strong spatial heterogeneity at scales too small to be driven by weather forcing or captured by Earth System Models. Here we analyze effects of observed spatial heterogeneity in soil and vegetation properties, hydrology, and thermal dynamics on ecosystem carbon dynamics in a watershed on the Seward Peninsula in Alaska. We apply a Morris global sensitivity analysis to a process‐rich, successfully tested terrestrial ecosystem model (TEM), ecosys , varying soil properties, boundary conditions, and weather forcing. We show that landscape heterogeneity strongly impacts soil temperatures and vegetation composition. Snow depth, O‐horizon thickness, and near‐surface water content, which vary at scales of O(m), control the soil thermal regime more than an air temperature gradient corresponding to a 140 km north–south distance. High shrub productivity is simulated only in talik (perennially unfrozen) soils with high nitrogen availability. Through these effects on plant and permafrost dynamics, landscape heterogeneity impacts ecosystem productivity. Simulations with near‐surface taliks have higher microbial respiration (by 78.0 gC m −2 yr −1 ) and higher net primary productivity (by 104.9 gC m −2 yr −1 ) compared to runs with near‐surface permafrost, and simulations with high shrub productivity have outlying values of net carbon uptake. We explored the prediction uncertainty associated with ignoring observed landscape heterogeneity, and found that watershed net carbon uptake is 60% larger when heterogeneity is accounted for. Our results highlight the complexity inherent in discontinuous permafrost environments and demonstrate that missing representation of subgrid heterogeneity in TEMs could bias predictions of high‐latitude carbon budget.

54 ENVIRONMENTAL SCIENCES↗

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

97 MATHEMATICS AND COMPUTING↗

Martensite decomposition during rapid heating of Ti-6Al-4V studied via in situ synchrotron X-ray diffraction

Martensite, α‘, commonly appears in Ti-6Al-4V upon rapid cooling from above the β-transus temperature. It is known that α‘ decomposes into α and β at high temperatures but well below the β-transus temperature. Here, we study the decomposition of martensitic Ti-6Al-4V under rapid laser heating, employing in situ synchrotron X-ray diffraction. A comparison is made with post-annealed Ti-6Al-4V under heating to elucidate changes without martensite decomposition. The fast acquisition of X-ray diffraction data at 250 Hz temporally resolves the decomposition process initiated by annihilating dislocations in α‘. The recovery process is accompanied by structural changes in martensite, followed by the phase transformation to β. Thermal profiles estimated from the lattice parameter data reveal the influence of heating rates and dislocation densities on the decomposition process. Throughout the analysis of the diffraction profiles with respect to estimated temperature, we propose a straightforward method for approximating the initiation temperature of martensite decomposition.

42 ENGINEERING↗

High-purity Polypropylene from Disposable Face Masks via Solvent-Targeted Recovery and Precipitation

The high use of disposable face masks since the start of COVID-19 has globally generated 4.68–6.24 million tons per year of waste from personal protective equipment. Disposable face masks are generally disposed of in landfills. Polypropylene (PP) is the main component in face masks, which is one of the least recycled plastics but has a high market value. In this work, we extract high-quality PP from face masks using solvent-targeted recovery and precipitation (STRAP) with 90 wt% recovery. N,N-Dimethylacetamide removed the color from the recovered PP to produce a clear high-purity PP, as verified by CIELAB color space. The decolored PP shows similar thermochemical properties and color to virgin PP resin. Here, a techno-economic analysis of the process indicates that high-purity PP recovery can be economically viable at a scale of 5000 tons per year or higher.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The integration of heterogeneous resources in the CMS Submission Infrastructure for the LHC Run 3 and beyond

While the computing landscape supporting LHC experiments is currently dominated by x86 processors at WLCG sites, this configuration will evolve in the coming years. LHC collaborations will be increasingly employing HPC and Cloud facilities to process the vast amounts of data expected during the LHC Run 3 and the future HL-LHC phase. These facilities often feature diverse compute resources, including alternative CPU architectures like ARM and IBM Power, as well as a variety of GPU specifications. Using these heterogeneous resources efficiently is thus essential for the LHC collaborations reaching their future scientific goals. The Submission Infrastructure (SI) is a central element in CMS Computing, enabling resource acquisition and exploitation by CMS data processing, simulation and analysis tasks. The SI must therefore be adapted to ensure access and optimal utilization of this heterogeneous compute capacity. Some steps in this evolution have been already taken, as CMS is currently using opportunistically a small pool of GPU slots provided mainly at the CMS WLCG sites. Additionally, Power9 processors have been validated for CMS production at the Marconi-100 cluster at CINECA. This note will describe the updated capabilities of the SI to continue ensuring the efficient allocation and use of computing resources by CMS, despite their increasing diversity. The next steps towards a full integration and support of heterogeneous resources according to CMS needs will also be reported.

Pérez-Calero Yzquierdo, Antonio↗

Trap passivation of 4H-SiC/SiO 2 interfaces by nitrogen annealing

We report an N 2 based annealing treatment to passivate interface traps (D it ) in n- and p-type 4H-SiC. The process has the potential to replace the commonly used hazardous and expensive gas nitric oxide (NO). N 2 postoxidation annealing reduces D it in both the upper and lower halves of the 4H-SiC bandgap, with a greater impact at the valence band edge. N 2 annealing at 1500 °C is observed to be more effective in passivating traps and positive fixed charges than NO annealing for p-type devices, whereas for n-type devices, the opposite is true. The breakdown voltages for these devices are found to be lower than that of NO annealed devices. X-ray photoelectron spectroscopy has been performed to estimate the nitrogen areal density at the interface. D it is measured as a function of nitrogen areal densities in the near interfacial regions for the different processes. Additionally, theoretical analysis through density functional theory is consistent with the measured D it profiles by showing the generation of additional states near the valence band edge due to increased nitrogen concentration. In addition to reporting the effect of N 2 annealing on both n- and p-type 4H-SiC, this work correlates the nitrogen areal densities at the interface to the D it and explains the difference in D it characteristics with nitrogen areal density between n- and p-type interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗