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Effectiveness of nature-based solutions to reduce flooding in Quad Cities Metro Area (QCMA) using SWMM-HEC based flood model

Nature-based solutions (NbS) have gained significant attention as strategies for addressing urban environmental challenges, particularly since the establishment of the UN Sustainable Development Goals (SDGs) for 2030. However, the current research on NbS for urban flood management lacks comprehensive methodological approaches for identifying suitable areas and evaluating their effectiveness across different urban settings. Here, this study attempts to fill this gap by proposing a methodological framework integrating multi-criteria analysis with a SWMM-HEC-based hydrologic and hydraulic (HH) model to assess the suitability of NbS for the Quad Cities Metro Area (QCMA), consisting of Davenport, Bettendorf, Moline, and Rock Island. Eight NbS options-green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels/cisterns - were considered based on volumetric efficiency and runoff reduction efficiency. The study reveals that implementing the proposed NbS could have substantially reduced flood depths in key historical flood events by 21% in 1993, 15% in 2008, 16% in 2011, 23% in 2014, 40% in 2019, and 10% in 2023. The findings highlight a critical trade-off between peak runoff and NbS implementation: while NbS effectively reduce flood impacts, they also enhance volumetric efficiency by approximately 43%. In high-density areas of the QCMA, flood depth reductions of around 20% suggest that NbS are a viable solution for dense urban environments with limited space. This shows the potential for integrating NbS into existing infrastructure, offering a promising approach for cities facing increasing flooding risks. The proposed methodology provides a practical framework for incorporating NbS into urban stormwater management, addressing gaps in optimizing NbS performance, and offering a pathway to scale their application in other urban areas with various environmental and social contexts.

CMIP6

Accelerating the Discovery of New, Single Phase High Entropy Ceramics via Active Learning

High-entropy ceramics have garnered interest due to their remarkable hardness, compressive strength, thermal stability, and fracture toughness; yet the discovery of new high-entropy ceramics (out of a tremendous number of possible elemental permutations) still largely requires costly, inefficient, trial-and-error experimental and computational approaches. The entropy forming ability (EFA) factor was recently proposed as a computational descriptor that positively correlates with the likelihood that a 5-metal high-entropy carbide (HECs) will form the desired single phase, homogeneous solid solution; however, discovery of new compositions is computationally expensive. If you consider 8 candidate metals, the HEC EFA approach uses 49 optimizations for each of the 56 unique 5-metal carbides, requiring a total of 2744 costly density functional theory calculations. Here, we describe an orders-of-magnitude more efficient active learning (AL) approach for identifying novel HECs. To begin, we compared numerous methods for generating composition-based feature vectors (e.g., magpie and mat2vec), deployed an ensemble of machine learning (ML) models to generate an average and distribution of predictions, and then utilized the distribution as an uncertainty. Here we then deployed an AL approach to extract new training data points where the ensemble of ML models predicted a high EFA value or was uncertain of the prediction. Our approach has the combined benefit of decreasing the amount of training data required to reach acceptable prediction qualities and biases the predictions toward identifying HECs with the desired high EFA values, which are tentatively correlated with the formation of single phase HECs. Using this approach, we increased the number of 5-metal carbides screened from 56 to 15,504, revealing 4 compositions with record-high EFA values that were previously unreported in the literature. Our AL framework is also generalizable and could be modified to rationally predict optimized candidate materials/combinations with a wide range of desired properties (e.g., mechanical stability, thermal conductivity).

36 MATERIALS SCIENCE

Experimental investigation of thermal conductivity of high entropy ceramics

In this talk, we will present the experimental investigation of thermal conductivity of high entropy carbides (HEC) and borides (HEB) with different compositions. Thermal conductivity determines the capability of a material to transport thermal energy and is considered as one critical physical property, specially in the energy industry. Due to the presences of disordered cation sublattice, it is expected that thermal conductivity of high entropy ceramics is lower than the counterparts with simpler compositions, but the experimental studies are relatively few. Using laser-based spatial-domain and frequency-domain thermoreflectance technique, we measured thermal conductivity of HECs and HEBs in a temperature range from 77K to 773K. Furthermore, by focusing the laser using an objective lens, we were able to perform the thermal property mapping on samples with the spatial resolution of micrometer. Such measurements could reveal important microstructure information in a rapid and efficient way without using scanning electron microscopy. The high spatial resolution also enables thermal conductivity measurements on ion-irradiated HECs with the damage layer of merely 1.1µm. These measurements can provide valuable information to predict the performances of HECs and HEBs with different compositions and from different manufacturing processes, and in the extreme environments such as nuclear reactors.

36 - MATERIALS SCIENCE

From high-entropy ceramics to compositionally complex ceramics and beyond

Over the past decade, the field of high-entropy ceramics (HECs) has expanded rapidly to encompass a broad range of oxides, borides, silicides, and other ceramic solid solutions. In 2020, we proposed extending HECs to compositionally complex ceramics (CCCs), where non-equimolar compositions and the presence of long- or short-range order, although reducing configurational entropy, create new opportunities to tailor and enhance properties, often surpassing those of higher-entropy counterparts. Along these lines, several fundamental scientific questions arise. Is the entropy in HECs truly high? Is maximizing entropy always desirable? In this perspective article, I revisit key concepts and terminologies and highlight emerging directions, including dual-phase CCCs, ultrahigh-entropy phases, and novel processing routes such as ultrafast reactive sintering. I propose that exploring compositional complexity across vast non-equimolar spaces, together with exploiting correlated disorder (coupled chemical and structural short-range order), represents a transformative strategy for designing ceramics with superior performance.

36 MATERIALS SCIENCE

Computational Analysis of Hydraulic Efficiency of Michigan DOT Covers J and K

Drainage structures are used in urban street and highway systems to capture stormwater runoff. These structures typically consist of catch basins fitted with grates, inlets, or combination grate/inlet configurations that collect runoff and convey it through buried drainage systems. They are strategically placed within curb-and-gutter systems to enhance public safety by efficiently removing water from roadways and thereby reducing the risk of hydroplaning. The performance of drainage structures is commonly evaluated in terms of hydraulic efficiency, defined as the percentage of flow captured by the basin relative to the total flow reaching the structure. Understanding the hydraulic performance of these structures allows designers to properly space inlets, resulting in cost-effective designs that also help ensure the safety of the traveling public. MDOT uses a variety of drainage structures for runoff capture, as documented in Michigan Department of Transportation (MDOT) Drainage Manual. Many of these structures incorporate sinusoidal-type grates that are not addressed in HEC-22. Because physical modeling of these structures has been limited, further analysis is needed to verify their capture efficiency. Under current MDOT practice, the capture efficiency of these grates is estimated by assuming performance similar to that of a comparably sized reticuline grate described in HEC22. The first phase of this effort, titled Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C, focused on evaluating the hydraulic performance of MDOT’s Cover C grate. Cover C was selected as the initial test candidate because its sinusoidal pattern is representative of other MDOT grates, while it is typically used in high-volume, higher-speed applications. A similar version, Cover CX, is used on interstate highways but does not include transverse bars for bicycle safety. The current second phase of the study expands this work to evaluate MDOT’s Covers J and K. These grates were selected for additional analysis to further assess the hydraulic performance of MDOT drainage structures that are not directly represented by grate configurations in HEC-22. The results of this phase will build on the findings from the Cover C analysis and support improved understanding of the capture efficiency of MDOT’s standard drainage grates. This report is intended to serve as a companion document to the earlier study, Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C [3]. The present work applies the same overall CFD-based evaluation approach to MDOT Covers J and K and compares the resulting performance trends with those previously identified for Cover C. In particular, both studies assess on-grade interception efficiency, sag-location hydraulic capacity, and the effects of partial obstruction relative to HEC-22-based design estimates.

42 ENGINEERING

Intercomparison of flood inundation models across land use types and hydrological flood stages

Flood Inundation Mapping (FIM) model selection is a key operational decision because accurate, rapid mapping underpins early warning and resource allocation. FIM performance is context-dependent and can vary with hydrograph phase, land-use/land-cover (LULC), and the evaluation benchmark. Intercomparison studies typically assess a single near-peak snapshot against one reference dataset. Here, we provide a context-stratified intercomparison across (i) multiple hydrograph phases, (ii) LULC classes, and (iii) benchmark types, for five FIM approaches spanning a wide range of physical complexity and operational cost (TRITON, LISFLOOD-FP, HEC-RAS 2D, ARC-Curve2Flood, and OWP HAND-FIM). We use the Hurricane Matthew flood (2016) in the Neuse River Basin, North Carolina, USA, as a case study. Using high-resolution remote sensing-derived flood inundation maps, hand-labeled points, and building footprints, we assess model skill across two rising and two falling hydrograph limbs and across major LULC types. Results show that model rankings shift systematically across contexts: LISFLOOD-FP ranks highest in three of four flood phases, while TRITON leads during one rising limb phase; LISFLOOD-FP performs best in vegetated areas, whereas HEC-RAS improves relative performance in agricultural and urban areas; and benchmark choice influences conclusions, with LISFLOOD-FP performing best for flooded-building detection in the late falling limb, while TRITON ranks highest against hand-labeled points. We also report representative wall-clock runtimes for each workflow to provide use-case context for operational feasibility. Together, these results offer transferable guidance for model selection and for designing large-scale, benchmark-aware FIM intercomparison studies.

Nikrou, Parvaneh [University of Alabama]

Effects of irradiation damage on the hardness and elastic properties of quaternary and high entropy transition metal diborides

Multi-principal component transition metal (TM) diborides represent a class of high-entropy ceramics (HECs) that have received considerable interest in recent years owing to their promising properties for extreme environment applications that include thermal/ environmental barriers, hypersonic vehicles, turbine engines, and next-generation nuclear reactors. While the addition of chemical disorder through the random distribution of TM elements on the cation sublattice has offered opportunities to tailor elastic stiffness and hardness, the effects of irradiation-induced structural damage on the physical properties of these complex materials have remained largely unexplored. To this end, changes in the hardness and elastic moduli of a high-entropy TM diboride (Hf 0.2 Nb 0.2 Ta 0.2 Ti 0.2 Zr 0.2 )B 2 and three of its quaternary subsets following irradiation with 10 MeV gold (Au) ions to fluences of up to 6 × 10 15 Au cm -2 are investigated at the micrometer and sub-micrometer length-scales via the dispersion of laser-generated surface acoustic waves (SAW) and nanoindentation, respectively. The nanoindentation measurements show that the TM diborides exhibit an initial increase in hardness following irradiation with energetic Au ions, with a subsequent decrease in hardness following further irradiation. One quaternary composition, (Hf 1/3 Ta 1/3 Ti 1/3 )B 2 , exhibits a notable exception to the trend and continues to exhibit an increase in hardness with ion irradiation fluence. Although differences in the absolute values of the effective elastic moduli obtained from the measured SAW dispersion and nanoindentation are observed (and attributed to microstructural variations at the measurement length-scale), both techniques yield similar trends in the form of an initial reduction and subsequent saturation in the elastic modulus with increasing ion irradiation fluence. The quaternary TM diboride (Hf 1/3 Ta 1/3 Ti 1/3 )B 2 again exhibits a departure from this trend. The high-entropy TM diboride (Hf 0.2 Nb 0.2 Ta 0.2 Ti 0.2 Zr 0.2 )B 2 exhibits the greatest recovery in hardness and modulus when irradiated to high ion fluences following initial changes at low fluence, indicating superior resistance to radiation-induced damage over its quaternary counterparts. Opportunities for designing HECs with superior hardness and modulus for enhanced radiation resistance (compared to their single constituent counterparts) by tailoring chemical disorder and bond character in the lattice are discussed.

36 MATERIALS SCIENCE

Effects of irradiation damage on the elastic properties and hardness of complex transition metal diborides

Multi-principal component transition metal (TM) diborides represent a class of high-entropy ceramics (HECs) that have received considerable interest in recent years owing to their promising properties for extreme environment applications that include thermal/ environmental barriers, hypersonic vehicles, turbine engines, and next-generation nuclear reactors. While the addition of chemical disorder through the random distribution of TM elements on the cation sublattice has offered opportunities to tailor elastic stiffness and hardness, the effects of irradiationinduced structural damage on the physical properties of these complex materials have remained largely unexplored. To this end, changes in the hardness and elastic moduli of a high-entropy TM diboride (Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)B2 and three of its quaternary subsets following irradiation with 10 MeV gold (Au) ions to fluences of up to 6 × 10^15 Au cm-2 are investigated at the micrometer and sub-micrometer length-scales via the dispersion of laser-generated surface acoustic waves (SAW) and nanoindentation, respectively. The nanoindentation measurements show that the TM diborides exhibit an initial increase in hardness following irradiation with energetic Au ions, with a subsequent decrease in hardness following further irradiation. One quaternary composition, (Hf1/3Ta1/3Ti1/3)B2, exhibits a notable exception to the trend and continues to exhibit an increase in hardness with ion irradiation fluence. Although differences in the absolute values of the effective elastic moduli obtained from the measured SAW dispersion and nanoindentation are observed (and attributed to microstructural variations at the measurement length-scale), both techniques yield similar trends in the form of an initial reduction and subsequent saturation in the elastic modulus with increasing ion irradiation fluence. The quaternary TM diboride (Hf1/3Ta1/3Ti1/3)B2 again exhibits a departure from this trend. The high-entropy TM diboride (Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)B2 exhibits the greatest recovery in hardness and modulus when irradiated to high ion fluences following initial changes at low fluence, indicating superior resistance to radiation-induced damage over its quaternary counterparts. Opportunities for designing HECs with superior hardness and modulus for enhanced radiation resistance (compared to their single constituent counterparts) by tailoring chemical disorder and bond character in the lattice are discussed.

36 - MATERIALS SCIENCE

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation

Era of entropy: Synthesis, structure, properties, and applications of high-entropy materials

The field of high-entropy materials (HEMs) has emerged as a dynamic area of scientific exploration, driven by the exceptional properties arising from their compositional complexity. Encompassing both high-entropy alloys (HEAs) and high-entropy ceramics (HECs), these materials have garnered significant attention across diverse research domains. From investigations into phase evolution and mechanical characteristics to studies of ionic, electronic, and magnetic behaviors, HEMs demonstrate remarkable potential for a wide array of applications. These range from catalysis and tribology to energy storage and superconductivity. Fundamental research has shed light on crucial phenomena such as configurational entropy, lattice distortion, and sluggish diffusion. These discoveries are paving the way for materials design strategies that enable new functional tunability and resistance to application-specific harsh environments. This burgeoning field promises to revolutionize material design and performance across numerous technological sectors. Here, this special collection between Applied Physics Letters and the Journal of Applied Physics provides a timely overview of the latest research in this area. It highlights the growing interest in understanding the impact of high compositional complexity on conventional structure–process–property–performance relationships in HEMs.

36 MATERIALS SCIENCE

Bioenergy pathways within United States net-zero CO 2 emissions scenarios in the Energy Modeling Forum 37 study

The Energy Modeling Forum 37 study is organized around carbon dioxide (CO 2 ) mitigation scenarios reaching net-zero CO 2 emissions by 2050 in the United States. Here, this paper summarizes the potential contribution of bioenergy use in the electric power, transportation, industrial, and buildings sectors toward meeting that target based on model results. Thirteen modeling teams reported bioenergy consumption in the Reference and Net Zero scenarios. Consumption of bioenergy increased over time in the Reference scenario, from an average across models of 3.2 exajoules (EJ) in 2020 to 3.8 EJ in 2050. Average bioenergy consumption in 2050 increased further to 7.3 EJ in the Net Zero scenario. All scenarios that reach net-zero emissions required some form of carbon dioxide removal to offset emissions that are difficult to reduce. Carbon dioxide removal using bioenergy with CO 2 capture and storage (BECCS) varies widely across models, up to 1000 Mt CO 2 in 2050. Some models rely instead on direct air carbon capture and storage (DACCS), up to 2200 Mt CO 2 , and others use a combination of BECCS and DACCS. Model results show a strong inverse relationship between the amounts of BECCS and DACCS deployed. All modeling teams assumed a carbon sink from land use, land use change, and forestry, further offsetting a portion of emissions from fossil fuels and industry that are expensive to eliminate. Bioenergy consumption in 2050 decreased by an average of 1.5 EJ across eight models in a Net Zero+ scenario relative to the Net Zero scenario, due in part to a lower equilibrium carbon price resulting from optimistic cost assumptions for all energy technologies.

09 BIOMASS FUELS

Transportation in net-zero emissions futures: Insights from the EMF-37 model intercomparison study

Transportation is currently the largest source of U.S. anthropogenic CO 2 emissions, at about a third of the total. Achieving net-zero emissions by mid-century will require substantial reductions in transportation emissions across passenger and freight travel. Here we leverage a model intercomparison study to explore the role of transportation in scenarios achieving net-zero economy-wide CO 2 emissions by 2050. We find the transport sector is poised to play the most significant role in reducing demand-side emissions, mostly driven by technology substitution, as modeling results suggest a limited role for mode shifting and for reduced use of personal car travel in the U.S. Among various technology solutions, models show agreement that passenger on-road vehicles will largely transition to electric vehicles (EVs), while solutions to decarbonize heavier travel modes are more diverse and include greater use of liquid biofuels and hydrogen. Research should continue to investigate the evolution of on-road electrification, the role of biofuels and hydrogen across heavier travel modes, and the role of mode shifting and travel behavior change to support personal transportation decarbonization at national and regional scales to temper the rapid growth in clean fuel and electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY