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At least 1,009 records · Page 56

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗

Pursuing graphite-based K-ion O 2 batteries: a lesson from Li-ion batteries

The replacement of lithium metal by lithium intercalated graphite was crucial for developing safe lithium-ion batteries. Superoxide-based potassium–oxygen batteries represent an exciting metal–oxygen battery with the highest energy efficiencies. However, using potassium metal is a more serious safety threat than lithium. Herein, we explore the possibility of graphite-intercalation anodes for potassium-ion oxygen batteries (PIOBs) with enhanced safety. This work demonstrates for the first time that establishing an artificial potassium salt-rich solid electrolyte interphase (SEI) enables a reversible graphite-intercalation anode (249.6 mA h g -1 after 600 cycles) in a potassium bis(trifluoromethanesulfonyl)imide (KTFSI)-based localized high-concentration electrolyte. Such an electrolyte is stable with the superoxide cathode. The PIOB delivers energy efficiencies above 90% at a depth of discharge (DOD) of 25% for 80 cycles. A three-electrode measurement shows that its overpotential mainly comes from the anode. The lifespan is limited to the gradual degradation of the artificial SEI caused by oxygen crossover. This work represents a step towards achieving holistic anode–electrolyte–cathode compatibility in a PIOB and its realistic evaluation under a controlled DOD.

25 ENERGY STORAGE↗

Th IV –Desferrioxamine: characterization of a fluorescent bacterial probe

Diversifying our ability to guard against emerging pathogenic threats is essential for keeping pace with global health challenges, including those presented by drug-resistant bacteria. Some modern diagnostic and therapeutic innovations to address this challenge focus on targeting methods that exploit bacterial nutrient sequestration pathways, such as the desferrioxamine (DFO) siderophore used by Staphylococcus aureus (S. aureus) to sequester Fe III . Building on recent studies that have shown DFO to be a versatile vehicle for chemical delivery, we show proof-of-principle that the Fe III sequestration pathway can be used to deliver a potential radiotherapeutic. Our approach replaces the FeIII nutrient sequestered by H 4 DFO + with Th IV and made use of a common fluorophore, FITC, which we covalently bonded to DFO to provide a combinatorial probe for simultaneous chelation paired with imaging and spectroscopy, H 3 DFO_FITC. Combining insight provided from FITC-based imaging with characterization by NMR spectroscopy, we demonstrated that the fluorescent DFO_FITC conjugate retained the Th IV chelation properties of native H4DFO+. Fluorescence microscopy with both [Th(DFO_FITC)] and [Fe(DFO_FITC)] complexes showed similar uptake by S. aureus and increased intercellular accumulation as compared to the FITC and unchelated H 3 DFO_FITC controls. Collectively, these results demonstrate the potential for the newly developed H 3 DFO_FITC conjugate to be used as a targeting vector and bacterial imaging probe for S. aureus. The results presented within provide a framework to expand H 4 DFO + and H 3 DFO_FITC to relevant radiotherapeutics (like 227Th).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prussian blue as a co-catalyst for enhanced Cr (VI) photocatalytic reduction promoted by titania-based nanoparticles and aerogels

Hexavalent chromium (Cr(VI)) is an noxious and highly toxic heavy metal that presents a serious threat to human health if present even in low concentrations in drinking water. Photocatalytic reduction of Cr(VI) to its less toxic Cr(III) state is a potential strategy to combat Cr(VI) pollution, but the efficiency of the process is low, especially in the absence of hole scavenger organic reagents. To address this issue and prepare efficient photocatalysts for Cr(VI) removal from water, in this study, we explored Prussian blue (PB) as a co-catalyst for improving the photoreduction performance of different high surface area TiO 2 -based materials (titania or silica–titania nanoparticles and aerogels). Here, the photocatalyst nanomaterials were surface-modified with nanocrystalline PB using the photodeposition route. The PB layer acts as an effective electron acceptor/mediator between the semiconductor photocatalyst and Cr(VI) species. All the PB-modified photocatalysts exhibit higher photocatalytic activity (up to 9 times faster) as compared to the unmodified photocatalysts towards reduction of Cr(VI). Importantly, the PB-modified photocatalysts exhibited high photocatalytic performance (98–99% reduction in 40 min for pH = 5.6 and in 10 min for pH = 3) without addition of organic reagents. The simple approach reported herein can be followed to prepare new PB-photocatalyst systems with improved photocatalytic performance towards Cr(VI) reduction and other target applications.

36 MATERIALS SCIENCE↗

Highly selective cross ketonization of renewable acids over magnesium oxide

The rising demand for linear alkylbenzene surfactants (LAS) poses an environmental threat as LAS are industrially produced from petroleum using corrosive acid catalysts. Cross ketonization is a promising route of converting furans and fatty acids to oleo-furansulfonates, precursors for renewable, performance-enhanced LAS replacements. Here, we explore various alkaline earth metals and mixed metal oxides for the cross-ketonization reaction and find that MgO achieves ~90% yield by minimizing the decarboxylation side reaction. Here, we illustrate the role of molecular structure on the cross-ketonization reaction and the role of complex formation over alkaline-earth metal oxides in minimizing side reactions. We overcome catalyst deactivation by regeneration over multiple runs. This research demonstrates the effectiveness of heterogeneous catalysts for cross ketonization toward developing renewable surfactants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase instability-coupled fracture behavior in garnet LLZO solid electrolytes: a machine learning-enabled atomistic study

Fracture in the garnet-type solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) poses a critical threat to both the performance and safety of solid-state batteries. To unravel the coupled chemomechanical processes that govern fracture in LLZO under external loading, we carry out large-scale molecular-dynamics simulations with a validated machine-learning force field. Our results demonstrate that triaxial stresses at crack flanks trigger a localized cubic-to-tetragonal phase transformation, which is accompanied by Li-ion rearrangement. The emergent tetragonal domains feature lattice contraction normal to the fracture plane, imposing coherent misfit strains that provide an additional driving force for further crack propagation. Crucially, introducing Li deficiencies stabilizes the cubic phase, postponing the phase transition and thereby delaying fracture initiation. These findings highlight the role of intrinsic phase instability in dictating LLZO's fracture resistance and its critical connection to local Li concentration. This chemomechanical coupling points toward targeted strategies to enhance the mechanical robustness of garnet electrolytes, including tuning Li content, ensuring dopant homogeneity, and refining processing protocols.

Materials science↗

Strategy for distributed controller defence: Leveraging controller roles and control support groups to maintain or regain control in cyber-adversarial power systems

Distributed controllers play a prominent role in electric power grid operation. The coordinated failure or malfunction of these controllers is a serious threat, where the resulting mechanisms and consequences are not yet well-known and planned against. If certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the system to an unsafe state. The authors present a strategy for distributed controller defence (SDCD) for improved grid tolerance under conditions of distributed controller compromise. The work of the authors’ first formalises the roles that distributed controllers play and their control support groups using controllability analysis techniques. With these formally defined roles and groups, the authors then present defence strategies for maintaining or regaining system control during such an attack. A general control response framework is presented here for the compromise or failure of distributed controllers using the remaining, operational set. The SDCD approach is successfully demonstrated with a 7-bus system and the IEEE 118-bus system for single and coordinated distributed controller compromise; the results indicate that SDCD is able to significantly reduce system stress and mitigate compromise consequences.

97 MATHEMATICS AND COMPUTING↗

Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

Abstract Man‐in‐The‐Middle (MiTM) attacks present numerous threats to a smart grid. In a MiTM attack, an intruder embeds itself within a conversation between two devices to either eavesdrop or impersonate one of the devices, making it appear to be a normal exchange of information. Thus, the intruder can perform false data injection (FDI) and false command injection (FCI) attacks that can compromise power system operations, such as state estimation, economic dispatch, and automatic generation control (AGC). Very few researchers have focused on MiTM methods that are difficult to detect within a smart grid. To address this, we are designing and implementing multi‐stage MiTM intrusions in an emulation‐based cyber‐physical power system testbed against a large‐scale synthetic grid model to demonstrate how such attacks can cause physical contingencies such as misguided operation and false measurements. MiTM intrusions create FCI, FDI, and replay attacks in this synthetic power grid. This work enables stakeholders to defend against these stealthy attacks, and we present detection mechanisms that are developed using multiple alerts from intrusion detection systems and network monitoring tools. Our contribution will enable other smart grid security researchers and industry to develop further detection mechanisms for inconspicuous MiTM attacks.

Wlazlo, Patrick↗

Inferring adversarial behaviour in cyber‐physical power systems using a Bayesian attack graph approach

Abstract Highly connected smart power systems are subject to increasing vulnerabilities and adversarial threats. Defenders need to proactively identify and defend new high‐risk access paths of cyber intruders that target grid resilience. However, cyber‐physical risk analysis and defense in power systems often requires making assumptions on adversary behaviour, and these assumptions can be wrong. Thus, this work examines the problem of inferring adversary behaviour in power systems to improve risk‐based defense and detection. To achieve this, a Bayesian approach for inference of the Cyber‐Adversarial Power System (Bayes‐CAPS) is proposed that uses Bayesian networks (BNs) to define and solve the inference problem of adversarial movement in the grid infrastructure towards targets of physical impact. Specifically, BNs are used to compute conditional probabilities to queries, such as the probability of observing an event given a set of alerts. Bayes‐CAPS builds initial Bayesian attack graphs for realistic power system cyber‐physical models. These models are adaptable using collected data from the system under study. Then, Bayes‐CAPS computes the posterior probabilities of the occurrence of a security breach event in power systems. Experiments are conducted that evaluate algorithms based on time complexity, accuracy and impact of evidence for different scales and densities of network. The performance is evaluated and compared for five realistic cyber‐physical power system models of increasing size and complexities ranging from 8 to 300 substations based on computation and accuracy impacts.

Sahu, Abhijeet↗

Decentralised Reinforcement Learning for Dynamic Cyberattack Response in Microgrid Networks

Microgrids rely on communication networks for reliable operation, which makes them inherently vulnerable to cyberattacks. Such attacks can destabilise system dynamics and drive states away from their nominal operating trajectories. Although several physics-informed and machine learning-based strategies have been developed to counter these threats, the rapidly evolving cyber landscape enables adversaries to bypass static defences or rules-based mitigation approaches. This paper proposes a dynamic, online-trained and fully decentralised reinforcement learning (RL)-based cyberattack response framework to protect microgrids from evolving cyberattacks. The proposed framework deploys multiple deep Q-networks (DQNs), each associated with a distributed energy resource (DER), to enable localised and adaptive attack mitigation. In this framework, each DQN processes local voltage and frequency measurements—combined with intrusion detection system (IDS) alerts—as observations and rewards to guide decision-making. Extensive simulation studies demonstrate the robustness of the proposed framework under diverse attack scenarios and varying IDS-induced detection delays. Comparative analysis highlights its superiority over existing static or preexisting rules-based mitigation approaches. Finally, we present an analysis that shows the framework's scalability to real-life microgrids with more interacting agents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Guest Editorial: Planning and operation of resilient distribution system for integrated multi-energy

Resilience is the ability of power systems to prepare for and adapt to low-probability, high-impact incidents and withstand and recover rapidly from disruptions. With the ageing of electricity distribution infrastructure and increasing threats of weather-related incidents and natural disasters, the need to effectively enhance the resilience of the electricity distribution system has become urgent and has attracted worldwide attention. Although there are an increasing number of publications related to enhancing resilience strategies, resilience is an emerging concept in power systems. Existing practices are mostly focused on deploying distributed energy resources (DERs) and microgrids, hardening the existing infrastructures and building redundant capacities. However, from a broader perspective, resilience enhancement of power distribution system is a systematic engineering, involving long-term system planning and upgrading (e.g., deployment of smart grid technologies and intelligent switches), short-term proactive scheduling, real-time robust and resilient control of DERs, and post-event restoration and recovery strategies. Based on this point, this Special Issue in IET Energy System Integration focuses on soliciting the most recent and original technologies, scheduling and control strategies for improving the resilience of power distribution system. Eight papers are presented in this Special Issue, covering various aspects related to resilience enhancement of power distribution system, including fault-tolerant frequency measurement, robust scheduling of integrated electricity and district heating systems, robust control of DERs, efficient methods for safety verification as well as novel graph theory-based approach to restore the distribution systems after multiple simultaneous faults. A brief introduction of these 8 papers is provided below.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cross-Layered Distributed Data-Driven Framework for Enhanced Smart Grid Cyber-Physical Security

Smart Grid (SG) research and development has drawn much attention from academia, industry and government due to the great impact it will have on society, economics and the environment. Securing the SG is a considerably significant challenge due the increased dependency on communication networks to assist in physical process control, exposing them to various cyber-threats. In addition to attacks that change measurement values using False Data Injection (FDI) techniques, attacks on the communication network may disrupt the power system's real-time operation by intercepting messages, or by flooding the communication channels with unnecessary data. Addressing these attacks requires a cross-layer approach. In this paper a cross-layered strategy is presented, called Cross-Layer Ensemble CorrDet with Adaptive Statistics(CECD-AS), which integrates the detection of faulty SG measurement data as well as inconsistent network inter-arrival times and transmission delays for more reliable and accurate anomaly detection and attack interpretation. Numerical results show that CECD-AS can detect multiple False Data Injections, Denial of Service (DoS) and Man In The Middle (MITM) attacks with a high F1-score compared to current approaches that only use SG measurement data for detection such as the traditional physics-based State Estimation, Ensemble CorrDet with Adaptive Statistics strategy and other machine learning classification-based detection schemes.

cyber-physical security↗

Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-DT workflow effectively generates scenarios that enhance resilience in the built environment by facilitating informed decision making. Furthermore, this study serves as a bridge between advanced scan-to-BIM methodologies and the practical strategies needed to improve built infrastructure resilience.

Built environment↗

Thermodynamic Properties of Aggregate Coated by Different Types of Waste Plastic: Adhesion and Moisture Resistance of Asphalt-Aggregate Systems

The utilization of acidic aggregates in hot-mix asphalt (HMA) is often inevitable due to the limited supply of locally available aggregates, posing a potential threat of moisture damage to asphalt pavements. In this regard, the use of urban waste plastic to coat the low-quality aggregates is a promising way to improve the moisture resistance. This study fundamentally evaluated the compatibility between asphalt and plastic-coated aggregate by measuring surface energy, and for the first time compared the effects of different types of waste plastic including high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyethylene terephthalate (PET), polyvinyl chloride (PVC), and polypropylene (PP). The plastic-coating significantly altered the chemistry of aggregate surface by increasing the nonpolar components and reducing the polar components. Such changes remarkably increased the dry adhesion energy between asphalt and aggregate and enhanced the wettability of aggregate. For the acidic aggregates, the polymeric treatment could decrease the value of wet adhesive, which indicated the debonding tendency in the presence of water was reduced. Finally, the energy ratios of the asphalt-aggregate combinations significantly increased by the surface pretreatment, which proved the effect of waste plastic coating on improving the moisture damage resistance of asphalt mixtures. By comparison, the HDPE coating was the most effective way to enhance the compatibility with asphalt, followed by PP and LDPE coatings. The PVC and PET coatings were investigated as the least effective way. In conclusion, this study cannot only contribute to the potential large-scale utilization of waste plastic but also remove the obstacles of using large quantities of acidic natural aggregate in asphalt pavements.

36 MATERIALS SCIENCE↗

Atomistic mechanisms for catalytic transformations of NO to NH3, N2O, and N2 by Pd

The industrial pollutant NO is a potential threat to the environment and to human health. Thus, selective catalytic reduction of NO into harmless N2, NH3, and/or N2O gas is of great interest. Among many catalysts, metal Pd has been demonstrated to be most efficient for selectivity of reducing NO to N2. However, the reduction mechanism of NO on Pd, especially the route of N−N bond formation, remains unclear, impeding the development of new, improved catalysts. We report here the elementary reaction steps in the reaction pathway of reducing NO to NH3, N2O, and N2, based on density functional theory (DFT)-based quantum mechanics calculations. We show that the formation of N2O proceeds through an Eley-Rideal (E−R) reaction pathway that couples one adsorbed NO* with one non−adsorbed NO from the solvent or gas phase. This reaction requires high NO* surface coverage, leading first to the formation of the trans-(NO)2* intermediate with a low N−N coupling barrier (0.58 eV). Notably, trans-(NO)2* will continue to react with NO in the solvent to form N2O, that has not been reported. With the consumption of NO and the formation of N2O* in the solvent, the Langmuir-Hinshelwood (L-H) mechanism will dominate at this time, and N2O* will be reduced by hydrogenation at a low chemical barrier (0.42 eV) to form N2. In contrast, NH3 is completely formed by the L-H reaction, which has a higher chemical barrier (0.87 eV). Our predicted E-R reaction has not previously been reported, but it explains some existing experimental observations. In addition, we examine how catalyst activity might be improved by doping a single metal atom (M) at the NO* adsorption site to form M/Pd and show its influence on the barrier for forming the N−N bond to provide control over the product distribution.

Physics↗

Application of cross-beam energy transfer to control drive symmetry in ICF implosions in low gas fill Hohlraums at the National Ignition Facility

Cross beam energy transfer (CBET), invoked by setting a wavelength difference, Δλ, between inner and outer beam cones, can be used to increase the drive on the waist in indirectly driven inertial confinement fusion experiments at the National Ignition Facility (NIF). Historically, hot spot symmetry control in capsule implosions in high (≥0.9 mg/cm 3 4 He) gas fill Hohlraums was enabled by substantial CBET. However, these implosion designs suffered from inflight symmetry swings, high SRS backscatter on the inner cones, and significant hot electron generation posing a threat to DT fuel preheat. Subsequent experiments in larger, low (≤0.6 mg/cm 3 4 He) gas fill Hohlraums demonstrated round implosions by varying the inner cone fraction throughout the laser drive at Δλ = 0 Å while keeping backscatter and hot electron generation very low. To enable driving larger capsules at a given Hohlraum size, additional tools for implosion symmetry control are required. With this goal in mind, here we present a detailed experimental study of using CBET in low gas fill Hohlraums near NIF's current peak power capability. We find a ~2.5× higher sensitivity of the P 2 Legendre mode with respect to Δλ changes compared to that of high gas fill designs. We attribute this observation to the fact that backscatter remains very low and that CBET remains in a linear regime, as suggested by simulations. As a result, a much smaller Δλ of order 1 Å is sufficient for sustaining implosion symmetry while keeping laser-to- Hohlraum coupling high and hot electron generation very low. While this study used plastic ablator capsules, our findings can be generalized to other ablator materials and, hence, show great promise for using wavelength detuning as a strong lever for implosion symmetry control in future low gas fill designs that require smaller case to capsule ratios in order to increase the energy coupled to the capsule.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tri-molybdenum phosphide (Mo 3 P) and multi-walled carbon nanotube junctions for volatile organic compounds (VOCs) detection

Detection and analysis of volatile organic compounds' (VOCs) biomarkers lead to improvement in healthcare diagnosis and other applications such as chemical threat detection and food quality control. Here, we report on tri-molybdenum phosphide (Mo3P) and multiwalled carbon nanotube (MWCNT) junction-based vapor quantum resistive sensors (vQRSs), which exhibit more than one order of magnitude higher sensitivity and superior selectivity for biomarkers in comparison to pristine MWCNT junctions based vQRSs. Transmission electron microscope/scanning tunneling electron microscope with energy dispersive x-ray spectroscopy, x-ray diffraction, and x-ray photoelectron spectroscopy studies reveal the crystallinity and the presence of Mo and P elements in the network. The presence of Mo3P clearly enhanced the performance of vQRS as evidenced in sensitivity and selectivity studies. The vQRSs are stable over extended periods of time and are reproducible, making them a potential candidate for sensing related applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Internal rotation of ELM filaments on NSTX

Edge localized modes (ELMs) are a threat to tokamaks due to their high heat and particle loads on plasma facing components. A significant portion of this energy is carried and deposited by the emerging ELM filaments, whose dynamics are directly connected to their impact. Therefore, understanding their underlying physics is important for the operation of future fusion reactors. Our paper extends our knowledge of ELM filaments by reporting on their internal rotation (spinning) around the magnetic field lines along which they are extended. Our analysis of gas-puff imaging data on National Spherical Torus Experiment shows that ELM filaments are characterized by internal rotation in the direction of the ion-gyromotion with ω = 15:2 krad/s median angular velocity, which is approximately three times faster than the blob rotation in the background turbulence. The characteristic size of the ELM filament was also assessed and found to be similar to the blobs. A nearly linear trend was found between the angular velocity and the radial velocity of the ELM filament. The angular velocity was found to be linearly dependent on the distance of the filament from the separatrix, as well. An analytical model called the shear-induced rotation model was identified as a candidate for explaining the physics of the observations. Our results show that the modeled mechanism could significantly influence the rotation of the ELM filament; however, it cannot be a sole contributor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗