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At least 1,333 records · Page 74

Multibody for Everybody (M4E) - A Linearization Approach to Enable Frequency Domain Analysis, Time Integration and Control Co-Design

1.1 Background/Objectives: Marine energy represents a promising yet underexploited source of power. To increase the harvested power, significant efforts have been made to improve wave energy converter (WEC) modeling capabilities and optimize power take-off (PTO) performance; however, these efforts have often treated WEC dynamics, PTO design, and controller development sequentially. In contrast, control co-design (CCD) is emerging as a promising strategy to address these issues directly, creating a growing need for fast analysis tools suitable for repeated simulation and parametric studies [1]. To support this need, this work presents the Multibody for Everybody (M4E) [2] linearization module, which employs a symbolic toolbox to provide deeper insight of WEC design parameters. The objective is to demonstrate that a minimal-coordinate linearization of articulated WEC dynamics can provide accurate wave response predictions and substantial computational savings relative to nonlinear time-domain simulation, while preserving compatibility with broader wave-energy analysis workflows, enabling CCD. 1.2 Approach/Activities: The proposed approach linearizes the equations of motion, generated by M4E, in minimal coordinates about a selected operating point and combines the resulting system with frequencydomain hydrodynamic terms to incorporate the reduced mass, damping, stiffness, and forcing operators. The linearized model is used for both impedance-based response amplitude operator (RAO) prediction and rapid regular-wave time integration. The methodology is demonstrated on a single-flap device and a FOSWEC configuration, with linearized M4E responses compared against the corresponding nonlinear M4E simulations and WEC-Sim results. Regular-wave time histories, RAO trends, and runtime differences are assessed. The framework is also compatible with broader wave-energy workflows, including coupling to WecOptTool, although that capability is not the focus of this work [3]. 1.3 Results/Lessons: The linearized M4E model reproduces key regularwave response characteristics such as integration and Response Amplitude over multiple frequencies. This module matches nonlinear M4E and WEC-Sim results while substantially reducing integration cost. Thus, the proposed framework can serve as a rapid analysis layer for articulated WEC design, parameter studies, and controls-oriented workflows. The analysis is most appropriate in the near-equilibrium regime, about the linearization point.

16 TIDAL AND WAVE POWER↗

Enhanced polymorph metastability drives glycine nucleation in aqueous salt solutions

Crystal nucleation from aqueous solutions influences countless geological, biochemical, astrophysical, environmental, and materials science–related phenomena, including ice formation, the manufacturing of active pharmaceutical ingredients, development of diseases such as Alzheimer’s and the origin of life itself. Understanding and controlling nucleation is essential for designing materials with specific properties, developing strategies to inhibit or promote crystallization in various contexts and preventing pathological aggregation in neurodegenerative diseases. Similar to the protein structure prediction problem—where a single amino acid sequence can in theory adopt one most stable conformation but in practice may sample multiple competing conformations—crystal nucleation faces a parallel challenge: the same chemical species can form diverse polymorphs under different environmental conditions (e.g., temperature, pressure, solvent). Each polymorph presents its own set of physical and chemical properties, highlighting the importance of understanding and controlling polymorph selection in fields ranging from pharmaceuticals to materials design. Despite advances in experimental and computational methods for studying phase transitions and polymorph stability, nucleation remains challenging due to its nanoscale nature. Furthermore, in practical settings, salts and impurities can further influence crystal nucleation in diverse contexts, from scaling in pipelines and desalination plants to the durability of concrete and the efficiency of battery materials. This can lead to the formation of polymorphs that may differ from the most stable phase in pure solutions. Or, even though the final structure might appear same irrespective of whether the environment contained impurities or not, the mechanism through which it was formed might be completely different and not intuitive.

Wang, Ruiyu [University of Maryland, College Park,↗

Dynamic Distribution System Restoration Strategy for Resilience Enhancement: Preprint

In electric power distribution systems, distributed energy re-sources (DERs) can act as controllable power sources and support utility operators to minimize power outages after ex-treme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influ-ences of extreme events and the capabilities of DERs are dy-namic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/disturbance information and the availabil-ity of DERs. In this paper, we propose a new dynamic distribu-tion system restoration strategy to enhance system resilience against potential hazards. An efficient reconfiguration algo-rithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER opera-tion setpoints based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Binary Quantum Control Optimization with Uncertain Hamiltonians

Optimizing the controls of quantum systems plays a crucial role in advancing quantum technologies. The time-varying noises in quantum systems and the widespread use of inhomogeneous quantum ensembles raise the need for high-quality quantum controls under uncertainties. In this paper, we consider a stochastic discrete optimization formulation of a discretized binary optimal quantum control problem involving Hamiltonians with predictable uncertainties. We propose a sample-based reformulation that optimizes both risk-neutral and risk-averse measurements of control policies, and solve these with two gradient-based algorithms using sum-up-rounding approaches. Furthermore, we discuss the differentiability of the objective function and prove upper bounds of the gaps between the optimal solutions to binary control problems and their continuous relaxations. We conduct numerical simulations on various sized problem instances based on two applications of quantum pulse optimization; we evaluate different strategies to mitigate the impact of uncertainties in quantum systems. In conclusion, we demonstrate that the controls of our stochastic optimization model achieve significantly higher quality and robustness compared with the controls of a deterministic model.

conditional value-at-risk (CVaR)↗

Synthesis and Advanced Characterization of Polymer–Protein Core–Shell Nanoparticles

Enzyme immobilization techniques are widely researched due to their wide range of applications. Polymer–protein core–shell nanoparticles (CSNPs) have emerged as a promising technique for enzyme/protein immobilization via a self-assembly process. Based on the desired application, different sizes and distribution of the polymer–protein CSNPs may be required. This work systematically studies the assembly process of poly(4-vinyl pyridine) and bovine serum albumin CSNPs. Average particle size was controlled by varying the concentrations of each reagent. Particle size and size distributions were monitored by dynamic light scattering, ultra-small-angle X-ray scattering, small-angle X-ray scattering and transmission electron microscopy. Results showed a wide range of CSNPs could be assembled ranging from an average radius as small as 52.3 nm, to particles above 1 µm by adjusting reagent concentrations. In situ X-ray scattering techniques monitored particle assembly as a function of time showing the initial particle growth followed by a decrease in particle size as they reach equilibrium. The results outline a general strategy that can be applied to other CSNP systems to better control particle size and distribution for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design Considerations of a Coordinative Demand Charge Mitigation Strategy

This paper presents a coordinative demand charge mitigation (DCM) strategy for reducing electricity consumption during system peak periods. Available DCM resources include batteries, diesel generators, controllable loads, and conservation voltage reduction. All resources are directly controlled by load serving entities. A mixed integer linear programming based energy management algorithm is developed to optimally coordinate of DCM resources considering the load payback effect. To better capture system peak periods, two different kinds of load forecast are used: the day-ahead load forecast and the peak-hour probability forecast. Five DCM strategies are compared for reconciling the discrepancy between the two forecasting results. The DCM strategies are tested using actual utility data. Simulation results show that the proposed algorithm can effectively mitigate the demand charge while preventing the system peak from being shifted to the payback hours. We also identify the diminishing return effect, which can help load serving entities optimize the size of their DCM resources.

Hu, Rongxing↗

Light controlled reversible Michael addition of cysteine: a new tool for dynamic site-specific labeling of proteins

Cysteine-based Michael addition is a widely employed strategy for covalent conjugation of proteins, peptides, and drugs. The covalent reaction is irreversible in most cases, leading to a lack of control over the process. Utilizing spectroscopic analyses along with X-ray crystallographic studies, we demonstrate Michael addition of an engineered cysteine residue in human Cellular Retinol Binding Protein II (hCRBPII) with a coumarin analog that creates a non-fluorescent complex. UV-illumination reverses the conjugation, yielding a fluorescent species, presumably through a retro-Michael process. Furthermore, this series of events can be repeated between a bound and non-bound form of the cysteine reversibly, resulting in the ON–OFF control of fluorescence. The details of the mechanism of photoswitching was illuminated by recapitulation of the process in light irradiated single crystals, confirming the mechanism at atomic resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Technical Routes to Achieve High Circular Polarized Luminescence in Chiral Perovskites: A Mini‐Review

Chiral hybrid organic-inorganic perovskites (HOIPs) have emerged as promising materials for optoelectronic and spintronic applications, leveraging unique properties such as circularly polarized luminescence (CPL), circularly polarized nonlinear optical (NLO) emission, and chiral-induced spin selectivity (CISS). However, challenges remain in stabilizing these materials under environmental stresses and precisely controlling chirality for scalable use. This review summarizes five main strategies to induce chirality in HOIPs, i.e., direct incorporation of chiral cations, surface modification with chiral ligands, ion doping, template-induced chirality, and chiral metasurfaces. Each approach offers distinct advantages for optimizing CPL efficiency and device stability, paving the way for next-generation applications in CPL detectors, information encryption, spintronic devices, etc.

14 SOLAR ENERGY↗

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗

Guest Editorial: Special issue on flexible and resilient urban energy systems

This guest editorial summarizes the topics and the papers selected for the Special Issue on Flexible and Resilient Urban Energy Systems. After rigorous reviewing process, 21 papers are accepted for publication. These 21 accepted papers cover various aspects of urban energy systems and are distributed as following: situational awareness of urban energy systems (2 papers), quantification metrics of flexibility and resilience of urban energy systems (3 papers), vulnerability modeling of urban energy systems under various extreme events (3 papers), planning of flexible and resilient urban energy systems (4 papers), robust and resilient operation and control of urban energy systems (4 papers), recovery and restoration strategy of urban energy systems (2 papers), and coordination and interoperability of interconnected energy systems (3 papers). The Guest Editorial Board hopes this Special Issue can provide a valuable information for future research and advancements in the field of flexible and resilient urban energy systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Synthesis of multicomponent oxygen evolution reaction coatings via block copolymer templating with vapor- and solution-phase precursors

Porous mixed transition metal oxide heterostructures are promising electrocatalysts due to their high surface area. However, achieving conformal multicomponent oxide coatings with controlled nanoscale architectures remains challenging. Here, we report a synthesis strategy that integrates solution-based swelling infiltration (SBI) with gas-phase sequential infiltration synthesis (SIS) in a block copolymer template to fabricate porous, high-surface-area, conformal mixed-oxide electrocatalytic coatings. In this approach, a PS75-P4VP25 block copolymer (BCP) film is first infiltrated with transition metal acetylacetonate precursors via SBI, followed by exposure to gas phase precursors of ZnO via SIS process. Thermal annealing of the infiltrated BCP films converts them into all-inorganic Fe–ZnO, Fe–Co–ZnO, and Fe–Ni–ZnO coatings. Electrochemical testing on 70 nm thick conformal coatings demonstrates promising oxygen evolution reaction (OER) activity in alkaline media, with mass-specific current densities up to 1.0 × 10 5 mA/g at an overpotential of 330 mV (vs. RHE) at ultralow loading (~0.005 g/cm 2 ). Among the compositions, Fe–Co–ZnO and amorphous Fe–Ni–ZnO show the best OER performance, delivering current densities of 2.00 and 3.04 mA/cm 2 , respectively, compared to 1.52 mA/cm 2 for Fe–ZnO.. This work establishes SBI–SIS as a versatile route for fabricating nm-thin, high-performance multicomponent oxide heterostructures on cost-efficient supports, enabling efficient catalyst utilization in electrochemical energy conversion application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RNA–Polymer Conjugates via Direct Incorporation of the Chain Transfer Agent and PET–RAFT Polymerization

Covalent conjugation of RNA with synthetic polymers has emerged as a powerful approach for creating bioconjugates with synergistically enhanced properties. However, conventional methods require solid-phase synthesis to preinstall functional groups in RNA, significantly limiting practical applications. Here, we present a novel approach for synthesizing RNA–polymer conjugates via direct incorporation of chain transfer agent (CTA) into RNA through acylation chemistry and reversible addition–fragmentation chain transfer (RAFT) polymerization. A CTA-functionalized acyl imidazole reagent was synthesized to facilitate direct and covalent modification of various RNAs by reacting with their 2′-hydroxyl groups. Subsequent RAFT polymerization using RNA–CTA as a macro-CTA enabled direct grafting-from RNA, yielding RNA conjugates with controlled molecular weight and low dispersity. Notably, this postsynthetic modification strategy was successfully extended to modify biomass RNA, yielding thermoresponsive conjugates and biodegradable hydrogels. Overall, this advance allowed for the direct modification of synthetic and biomass RNAs, significantly enhancing the accessibility of functional RNA–polymer materials.

biomass↗

(111) Faceted Metal Oxides: A Review of Synthetic Methods

Material design and synthesis have made tremendous impacts in the scientific community by unleashing a material's true potential via enhanced properties and applications. Over the years, advanced synthetic strategies have emerged and have been expanded to not only control the size and shape of nanoparticles but also to control the preferential growth of surface facets, paving the way for new materials with facet-dependent properties. Metal oxide (111) facets as compared to their potentially more stable counterpart facets (e.g., (100), (110)) have recently exhibited enriched chemical properties owing to their unique surface arrangement. As a result, metal oxide (111) faceted surfaces have been used in applications such as catalysis, sorbents, batteries, etc. This work aims to provide a perspective on the synthetic processes utilized to expose (111) surfaces and the governing factors/synthetic parameters that expose them across various metal oxides of different crystal structures as well as some of their applications.

36 MATERIALS SCIENCE↗

Constraining maximum event magnitude during injection-triggered seismicity

Abstract Understanding mechanisms controlling fluid injection-triggered seismicity is key in defining strategies to ameliorate it. Recent triggered events (e.g. Pohang, Mw 5.5) have exceeded predictions of average energy release by a factor of >1000x, necessitating robust methodologies to both define critical antecedent conditions and to thereby constrain anticipated event size. We define maximum event magnitudes resulting from triggering as a function of pre-existing critical stresses and fluid injection volume. Fluid injection experiments on prestressed laboratory faults confirm these estimates of triggered moment magnitudes for varied boundary conditions and injection rates. In addition, observed ratios of shear slip to dilation rates on individual faults signal triggering and may serve as a measurable proxy for impending rupture. This new framework provides a robust method of constraining maximum event size for preloaded faults and unifies prior laboratory and field observations that span sixteen decades in injection volume and four decades in length scale.

58 GEOSCIENCES↗

PLEXUS: A Pattern-Oriented Runtime System Architecture for Resilient Extreme-Scale High-Performance Computing Systems

For high-performance computing (HPC) system designers and users, meeting the myriad challenges of next-generation exascale supercomputing systems requires rethinking their approach to application and system software design. Among these challenges, providing resiliency and stability to the scientific applications in the presence of high fault rates requires new approaches to software architecture and design. As HPC systems become increasingly complex, they require intricate solutions for detection and mitigation for various modes of faults and errors that occur in these large-scale systems, as well as solutions for failure recovery. These resiliency solutions often interact with and affect other system properties, including application scalability, power and energy efficiency. Therefore, resilience solutions for HPC systems must be thoughtfully engineered and deployed.In previous work, we developed the concept of resilience design patterns, which consist of templated solutions based on well-established techniques for detection, mitigation and recovery. In this paper, we use these patterns as the foundation to propose new approaches to designing runtime systems for HPC systems. The instantiation of these patterns within a runtime system enables flexible and adaptable end-to-end resiliency solutions for HPC environments. The paper describes the architecture of the runtime system, named Plexus, and the strategies for dynamically composing and adapting pattern instances under runtime control. This runtime-based approach enables actively balancing the cost-benefit trade-off between performance overhead and protection coverage of the resilience solutions. Based on a prototype implementation of PLEXUS, we demonstrate the resiliency and performance gains achieved by the pattern-based runtime system for a parallel linear solver application.

Hukerikar, Saurabh↗

AmeriFlux FLUXNET-1F US-xJR NEON Jornada LTER (JORN)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xJR NEON Jornada LTER (JORN). This is the FLUXNET version of the carbon flux data for the site US-xJR NEON Jornada LTER (JORN) produced by applying the standard ONEFlux (1F) software. Site Description - Land use at Jornada has contrasting livestock grazing histories (including ungrazed lands), dating back to 1902, which are representative of the pervasive land use in desert-southwest wildlands. Historical accounts of the region report significant changes in vegetation starting in the late 1800s coincident with the expansion of livestock grazing. By 1912, sufficiently dramatic changes lead area scientists and private landowners to convince the U.S. government to set aside Public Domain Lands for the Jornada Range Reserve for the purpose of scientific investigation on shrub invasion and subsequent loss of forage grasses. Much of this early research focused on quantifying utilization levels for forage species, developing livestock production strategies to deal with drought, and developing methods for shrub control and grass recovery. Exclosures were constructed and long-term plots were established throughout the range to monitor the continued expansion of shrubs across the landscape. Over the decades, numerous trials of various remediation approaches were implemented, from manual and mechanical shrub removal to herbicide application to construction of terraces or other means of redirecting surface flow of runoff.

Network), NEON (National Ecological Observatory↗

Structural and Dynamical Design Principles for Iron-Sulfur Clusters in Sequence Defined Polymers

This integrated synthetic and computational effort uses sequence defined polymers such as peptoids, and triazines, capable of mimicking a flexible protein environment to control the positioning of side chains around redox cofactors. This strategy will allow modulation of redox properties through both direct and indirect mechanisms. To this end the aim is defined to test the underlying hypothesis: that principles and critical functionalities governing the binding and tuning of naturally occurring electron carrier co-factors can be identified and used to predictably design and synthesize maquettes based on non-natural polymers resulting in new modular biomimetic scaffolds for Electron Transfer Materials. This will be achieved through design and synthesis of ligands that can stabilize iron-sulfur clusters and tune the redox potential based on sequence.

36 MATERIALS SCIENCE↗

ICALEPCS 2025: Managing Technical Debt Across Large-Scale Control Systems

This presentation provides an overview of technical debt in the context of control systems for large-scale physics facilities. We explore various forms, common causes, and potential consequences on system reliability, maintainability, and extensibility. Drawing on experiences from multiple projects, including the ACORN control system modernization at Fermilab, we present a range of strategies for proactively managing technical debt, including best practices in design, development, testing, and documentation, as well as reactive approaches for identifying and mitigating existing issues.

Watts, Adam [Fermilab]↗