20 Apr 2026

A Simple Room-Temperature Refurbishment Method for Sulfated Lead-Acid Batteries Using Ammonium Acetate Treatment

Abstract: Current recycling paradigms of lead-acid batteries (LABs) involve the use of toxic, polluting, and energy- demanding processes. Here we report a novel strategy to refurbish LABs which failed due to the formation of hard sulfation on the anodes. We used ammonium acetate (NH4Ac) to selectively dissolve the water-insoluble lead sulfate (PbSO4) crystals which cause the hard sulfation from commercial LAB anodes and electrodeposit metallic lead on a new surface. The remarkable removal of hard sulfation was characterized by a combination of X-ray diffraction (XRD) and scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDX). The treatment replenished a fresh LAB anode surface, recovering the capacity from ~0 % to 99 %. The dissolved Pb2+ was retrieved with an efficiency of >99.9 % through electrodeposition, completing a refurbishing process that minimizes the release of heavy metals into the environment. We demonstrated a proof-of-concept refurbishing of a full commercial LAB, which recovered 35 % of its capacity. With a noteworthy capacity renewal and minimal release of hazardous materials, NH4Ac refurbishing promises to be an environment-friendly and economic alternative recycling paradigm for the LAB industry.

20 Apr 2026

Permafrost Pore Structure and its Influence on Microbial Diversity: Insights from X-Ray Computed Tomography

Abstract: Soil pore structure plays a critical role in shaping soil microbial communities, which directly influence biogeochemical cycling. A notable impact of soil pore structure on microbial communities is the inverse relationship between microbial diversity and hydrological pore connectivity, where increased hydrological pore connectivity reduces microbial diversity. Although well-studied in temperate systems, the importance of hydrological pore connectivity on soil microbial community diversity in permafrost soils is largely unknown. Although once thought to be devoid of microbial activity, more recent advances demonstrate permafrost is an active ecosystem albeit less than most unfrozen soil. Thus, these principles that govern unfrozen soils could remain impactful in permafrost. In this study, our objective was to quantify permafrost pore structure and determine if the inverse relationship between soil hydrological pore connectivity and microbial diversity persists in permafrost. To address these objectives, we analyzed eight permafrost cores from three distinct sites in Alaska. To quantify soil pore characteristics, we scanned intact permafrost using X-ray computed tomography. The Euler characteristic number was used to measure pore connectivity and serve as a proxy for potential hydrological connectivity, as direct measurement of hydrological connectivity was not possible. DNA and RNA were extracted from the scanned permafrost and analyzed via amplicon sequencing of the 16S region to quantify the total and active microbial community diversity. We found that permafrost soil shares characteristics with temperate soils despite limits in our analytical resolution (i.e., at an instrument scanning resolution of 20 µm, only macro-scale features (>75 µm) could be quantified). For example, we found that pores in the range of 75–1000 µm are the dominant pore size class and a positive relationship between total porosity and pore connectivity. Additionally, we identified pore connectivity as a potential driver of microbial diversity and provided evidence that conditions before the formation of permafrost exert a strong legacy effect on currently observed permafrost microbial diversity. These insights help to explain how soil physical structure acts to influence microbial communities in this extreme environment.

17 Apr 2026

Restoring the Flexible Pavement Test Track to Monitor Impact of Military Ground Vehicles

Abstract: Full-scale tests for pavement design, construction, evaluation, and maintenance benefit from designated facilities where pavement elements can be controlled and monitored. A loop test track at the US Army Engineer Research and Development Center (ERDC) Vicksburg campus was constructed between September 1986 and September 1988. This report describes activities to restore that pavement test track through reconstruction. ERDC constructed a road structure consisting of 4 in. of asphalt concrete over 6 in. of aggregate base course over native subgrade material on the site of the original test track. The pavement structure was instrumented with earth pressure cells and moisture probes at the subgrade, or base, course interface. Material testing and as-constructed properties are documented herein to allow future traffic studies that use the constructed test track to create numerical simulations and calibrate their embedded models with real-world data. This report details construction activities and material properties for future reference.

15 Apr 2026

Satellite Image Quality Classification with ImageNet Transfer Learning and Data Fusion

Abstract: This Coastal and Hydraulics Engineering Tech Note (CHETN) documents the development of a convolutional neural network (CNN) to automate quality control on image classification, a process previously done by subject matter experts (SMEs), within the Littoral Zone Maneuver Support Tool (LZMST). LZMST was created to support rapid exploration of an unknown littoral region by analyzing global satellite data and wave and current models to best estimate the coastal conditions and help identify potential hazards. In support of this mission, images from Landsat-8 (Roy et al. 2014) and Sentinel-2a/2b (Drusch et al. 2012) are graded on their predicted usefulness for LZMST, which is usually done by expert selection. A CNN model is developed to automate this task, by utilizing transfer learning on a CNN using ImageNet (Krizhevsky et al. 2017) weights combined with a small data set of classifications from the CoastSat (Vos et al. 2019) python application. Because the expert selection of images is incredibly time consuming, the data set used to develop this tool was small (approximately 3,500 images), which can make creation of a data-driven algorithm difficult. This CHETN highlights the usefulness of using transfer learning to eliminate the need for large data sets and demonstrates that ImageNet weights can be successfully used to assist in quality detection on multispectral imagery from the Landsat-8 and Sentinel-2a/2b missions.

15 Apr 2026

Field Evaluation of the Automated Barge Clearing Deterrent (ABCD): Hydrodynamic, Navigation, and Fish Response Effects

Abstract: The escape and subsequent spread of invasive carp (notably, bighead carp [Hypophthalmichthys nobilis] and silver carp [H. molitrix]) from aquaculture ponds and sewage lagoons into the Mississippi and Illinois Rivers poses a significant risk to further spread of these fish into the Great Lakes. Prior research demonstrated that commercial tows can transport juvenile invasive carp through locks and other barriers to fish migration. A recent physical model study recommended a linear array of bubble diffusers, the Automated Barge Clearing Deterrent (ABCD), for further evaluation in mitigating the transport of small fish in commercial tows. The present field study evaluated the ABCD for navigation safety and barge junction flushing capacity. An instrumented commercial tow executed 119 lock approaches with the ABCD both operating and idle. Pilot interviews and tow trajectory analysis indicated no significant navigation safety issues. The measured velocity data, fish recapture data, and a simple fish displacement model indicated that the ABCD produced sufficient flow to expel all passive objects and many small juvenile invasive carp. However, the ABCD is less likely to expel large juvenile invasive carp due to their stronger swimming ability. The ABCD and two alternative configurations prove strong contenders for further development and application.

14 Apr 2026

Performance Assessment of Microencapsulated Phase Change Materials with Low to High Thermoregulation Range in Asphalt Binder

Abstract: This study aims to assess the impact of microencapsulated phase change materials (MPCMs) on thermoregulation effect and binders’ performance. Accordingly, three MPCMs with melting points 6°C, 28°C, and 37°C were blended with PG 58-28 and PG 64-22 binders at dosages of 5%–20% by binder weight. Subsequently, laboratory experiments were conducted to examine impact on thermoregulation and rheological parameters including enthalpy change, complex modulus, Glover- Rowe parameter, creep stiffness, creep slope, fatigue, and rut factors. The findings showed that increasing MPCMs’ dosage in both control binders led to increased enthalpy change, indicating successful thermoregulation and capsules’ survival during blending. Rheological investigation depicted increasing complex modulus, creep stiffness and Glover-Rowe parameter in modified binders compared to control binders regardless of MPCMs’ thermoregulation range. However, Dynamic shear rheometer and Bending beam rheometer may not adequately capture their thermoregulation impact under steady-state conditions, necessitating use of temperature sweep test to validate influence on complex modulus and phase angle due to their thermoregulation capability. Temperature sweep test showed that within thermoregulation range, MPCMs with melting points 6°C and 28°C showed comparable fatigue resistance to respective control binders up to 10% dosage. Meanwhile, around melting point, MPCM with 37°C melting point enhanced rutting resistance.

14 Apr 2026

Physics-enhanced Machine Learning Models for Streamflow Discharge Forecasting

Abstract: Accurate river discharge forecasts for short to intermediate time intervals are crucial for decision-making related to flood mitigation, the seamless operation of inland waterways management, and optimal dredging. River routing models that are physics based, such as RAPID (‘routing application for parallel computation of discharge’) or its variants, are used to forecast river discharge. These physics-based models make numerous assumptions, including linear process modeling, accounting for only adjacent river inflows, and requiring brute force calibration of hydrological input parameters. As a consequence of these assumptions and the missing information that describes the complex dynamics of rivers and their interaction with hydrology and topography, RAPID leads to noisy forecasts that may, at times, substantially deviate from the true gauged values. In this article, we propose hybrid river discharge forecast models that integrate physics-based RAPID simulation model with advanced data-driven machine learning (ML) models. They leverage runoff data of the watershed in the entire basin, consider the physics-based RAPID model, take into account the variability in predictions made by the physics-based model relative to the true gauged discharge values, and are built on state-of-the-art ML models with different complexities. We deploy two different algorithms to build these hybrid models, namely, delta learning and data augmentation. The results of a case study indicate that a hybrid model for discharge predictions outperforms RAPID in terms of overall performance. The prediction accuracy for various rivers in the case study can be improved by a factor of four to seven.

14 Apr 2026

A Synthesis of Freshwater Forested Wetland Soil Organic Carbon Storage

Abstract: Freshwater forested wetlands account for ~76% of the total global wetland extent. However, freshwater forested wetlands are difficult to distinguish from upland forest due to canopy coverage, the abundance of wetland-nonwetland mosaics, seasonal hydropatterns, and fewer readily observable connections to large surface water bodies relative to marshes and other emergent habitats. Therefore, freshwater forested wetland ecosystems are often misclassified as upland forests in carbon accounting models, underestimating soil organic carbon storage. This study highlights freshwater forested wetland SOC accounting challenges and presents SOC densities/stocks from a global literature synthesis across different freshwater forested wetland types. We reviewed 374 forested wetland articles, compiling and calculating carbon densities by depth from 90 freshwater forested wetland studies to construct a database of 334 study sites including nine countries. The median SOC stock was 91.2 ± 46.4 Mg C ha−1 and 235.3 ± 125.6 Mg C ha−1 in the top 30 cm and 100 cm of soil, respectively. The tidal freshwater forested wetland had highest SOC stock in the upper 100 cm soil profile followed by rainforest, non-tidal swamps, and floodplain forested wetlands. Within the conterminous United States forest type groups, the Tsuga/Picea group had the highest median SOC stocks in the top 100 cm of soil followed by Quercus/Pinus and Quercus/Liquidambar/Taxodium groups, likely driven by variability in litter degradability, wetland hydroperiod, geomorphic positions, and regional climatic factors. This literature synthesis highlights SOC accounting in freshwater forested wetland carbon pools when estimating carbon stocks and fluxes. Results can be used to improve carbon modeling outcomes, as well as inform regional, national, and global management of wetland carbon resources.

14 Apr 2026

Changes in Permafrost Bacterial Community Composition After Thaw Across Multiple Alaskan Locations

Abstract: Increasing temperatures due to climate change are causing extensive permafrost thaw, impacting microbial communities and their processes. We conducted a laboratory thaw study comprising six Alaskan permafrost samples collected across a variety of locations to investigate how microbiome communities from different locations shift when experiencing the same thaw regime (stepwise increases in temperature over an 8-week incubation). The samples varied in bulk soil pH (4.45–6.59), water content (28%–265%), and carbon content (1%–29%). We surveyed the microbial community structure at each location pre- and post-thaw and determined whether communities were driven by stochastic or deterministic ecological assembly processes. We found that community composition and community assembly all varied by location. Dominant phyla were Firmicutes, followed by Actinobacteria and Proteobacteria. The deterministic process, homogeneous selection, was observed for five sites and was the most prevalent community assembly process at three of those sites, both pre- and post-thaw. At the two other sites, a combination of deterministic and stochastic processes influenced pre- and post-thaw community structure, with a large increase in drift post-thaw. Collectively, our findings suggest that permafrost attributes, such as edaphic conditions and pre-thaw community structure, exert an influence on the composition of microbial communities after thaw. However, the extent of this influence varies with location. The heterogeneous response of permafrost communities to thaw disturbance poses a significant challenge in accurately predicting the trajectory of microbial communities in response to climate change.

14 Apr 2026

Verification and Validation of Modeling of Fluid–Solid Interaction in Explosion-Resistant Designs Using Material Point Method

Abstract: Verifying and validating explosion-resistant design models are challenging tasks due to the difficulties in accurately capturing the failure evolution within a setup influenced by the combined effects of fluid–solid interactions, blast waves, fragmentation, and impact. Curtain wall system, as a key structural component, is widely used in various types of buildings for its aesthetic appeal and weather protection. Hence, optimizing the explosion-resistance of such systems is necessary to improve building safety. In this work, we develop computational procedures that can be used to enhance the design of blast-resistant structures. This paper focuses on studying a representative component from a typical curtain wall system, as well as a small-scale modeling of shock tube testing. For that, the material point method simulations are verified against the finite element method simulations, and the computational results are validated against shock tube testing. The work objective is to evaluate the simulation fidelity of explosion responses in several case studies. The first case study demonstrates how the MPM captures damage and fragmentation in a typical confined explosion event involving FSI, thus, providing an improved physical description compared to the FEM. The second case study qualitatively compares the MPM’s ability to simulate the shock tube response with experimental observations. Since the second study validates that the MPM solution is qualitatively consistent with the experimental data, the MPM model is then used in the third case study to establish an FEM model that could capture the same physics. This FEM model can be scaled up to model field experiments. The fourth case study involves the development of an FEM model for a representative curtain wall system component, which is validated against experimental results and then scaled down and employed to validate a corresponding MPM model. The proposed procedure provides a feasible approach to verifying and validating explosion-resistant designs for more general cases.