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At least 163 records · Page 9

Manufacturing of Continuous Microporous Polymeric Fibers for Separation Applications

Polyolefin plastic waste, particularly polypropylene, is one of the most prevalent components in the plastic waste stream generated globally. However, only a small fraction of this waste is recycled and reintegrated into second applications. These materials have significant embedded energy that could be used for additional productivity if recycled properly. Therefore, there is a critical need to develop scalable processing techniques with high throughput to effectively recycle it. We report the continuous manufacturing of microporous fibers using waste polypropylene plastic and melt-processable lignin, a plant biomass constituent produced as a byproduct in paper mills or biorefineries, as a template to create pores. Further, these filaments with hierarchical porosity─created by controlled microphase separation during high-speed extensional flow followed by removal of lignin─exhibit exceptional capillary action for hydrophobic liquids. The resulting porous fibers can be used for various separation applications. For example, the oil uptake of the fibers is 9.59 ± 0.82 g/g for applications in oil recovery in bodies of water. In addition, polyethylenimine infiltration within these nanoporous fibers introduces cyclic room temperature sorption and thermal desorption potential of acidic gases such as CO 2 in a bench-scale experiment. The fibers exhibit multiple cycles of CO 2 absorption, with a range of 0.15 to 0.17 mmol/g. Thus, these polyethylenimine-infiltered nanoporous polypropylene fibers can also be used in removing acidic gases from a gas mixture.

36 MATERIALS SCIENCE↗

A stoichiometrically conserved homologous series with infinite structural diversity

Here, we describe a compositionally guided structural evolution within a stoichiometrically conserved framework, BaSbQ 3 (Q = Te 1−x S x ), where each value of x gives rise to a distinct phase. The fundamental building blocks, A 1 (BaSbSTe 2 ) and B n (Ba n Sb n S n−1 Te 2n+1 ), were composed of modular double rocksalt slabs stacked with functional polytelluride zigzag chains, with each phase differing only in the size and assembly of these blocks. Ten compounds were synthesized that maintained a coherent chemical identity that arose from this isovalent, isoelectronic substitution of Te and S. We envision that the phase formation at a molecular level unfolds in stages of extension, termination, and assembly and propose a design concept of “anionic disparity,” where phase homologies and polytelluride hierarchical networks can be controlled by leveraging differences in anion electron affinity and sizes.

Zhao, Hengdi [Argonne National Laboratory (ANL), A↗

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

distribution network↗

Investigation of Hierarchical Structure Formation in Merocyanine Photovoltaics

Merocyanines (MCs) are a versatile class of small-molecule dyes. Their optoelectronic properties are easily tunable by chemically controlling their donor–acceptor strength, and their structural properties can be tuned by simple side-chain substitution. This paper demonstrates a novel series of MCs featuring an indoline donor with varying hydrocarbon side-chain length (from 6 to 12 carbons) and a tert-butyl-thiazole acceptor, labeled InTBT. Bulk heterojunction organic photovoltaics are fabricated with a [6,6]-phenyl-C 61 -butyric acid methyl ester (PCBM) acceptor and characterized. Films composed of I8TBT:PCBM and I9TBT:PCBM produced the highest power conversion efficiency of 4.5%, which suggests that the morphology is optimized by controlling the side-chain length. Hierarchical structure formation in InTBT:PCBM films is studied using grazing incidence X-ray diffraction (GIXRD), small-angle neutron scattering (SANS), and atomic force microscopy (AFM). When mixed with PCBM, InTBTs with ≤8 side-chain carbons form pure crystalline domains, while InTBTs with ≥9 side-chain carbons mix well with PCBM. SANS demonstrates that increasing side-chain length increases the InTBT-rich domain size. In addition, a branched hexyl–dodecyl side-chain IHDTBT:PCBM film was studied and found to exhibit the worst-performance organic photovoltaic (OPV) device. The large-branched side chain inhibited mixing between IHDTBT and PCBM resulting in large segregated phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pushing and Pulling: A Dual pH Trigger Controlled by Varying the Alkyl Tail Length in Heme Coordinating Peptide Amphiphiles

Some organisms in nature that undergo anaerobic respiration utilize 1D nanoscale arrays of densely packed cytochromes containing the molecule heme. The assemblies can be mimicked with 1D nanoscale fibrils composed of peptide amphiphiles designed to coordinate heme in dense arrays. To create such materials and assemblies it is critical to understand the assembly process and what controls the various aspects of hierarchical assembly. MD simulations suggest that shorter alkyl chains on the peptide lead to more dynamic structures than the peptides with longer chains that yield kinetically trapped states. The hydration parameters manifest themselves experimentally through the observation of a dual pH trigger which controls the peptide assembly rate, the heme binding affinity, and heme organization kinetics. Great strides in understanding the relative complexity of the self-assembly process in relation to incorporating a functional moiety like heme opens up many possibilities in developing abiotic assemblies for bioelectronic devices and assemblies

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Collaborative Distribution System Restoration Planning and Real-Time Dispatch Considering Behind-the-Meter DERs

Modern distribution systems are becoming more resilient against power outages thanks to the flexible generation capacity provided by the increasing integration of distributed energy resources (DERs). Compared to utility-scale DERs, which can be directly controlled by system operators, small-scale, behind-the-meter DERs are much more difficult to coordinate despite being the vast majority. Two major obstacles to the implementation of DERs for service restoration are the coordination of behind-the-meter DERs and the management of uncertainty. In this paper, a novel distribution system restoration strategy is proposed to overcome these two obstacles. The flexibility of be-hind-the-meter DERs is quantified and integrated into the restoration planning models within a hierarchical structure. The model predictive control technique is employed to enable adaptive restoration planning solution adjustments to accommodate fault scenarios and forecast errors. Besides, real-time power dispatch models are proposed to maintain power balance using available DER capability. Comprehensive integration of adaptive restoration planning schemes and real-time dispatch results are achieved through a collaborative restoration framework. Finally, the effectiveness of the proposed restoration strategy is verified through a modified IEEE 123-bus system and a real-world utility system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Robust hierarchical dispatch for residential distribution network management considering home thermal flexibility and model predictive control

In the transactive energy (TE) paradigm, the devices of participative consumers, or prosumers, may be aggregated and employed to drive operational objectives at the network level. Home heating, ventilation and air-conditioning (HVAC) systems in particular are well-suited to modulate their behaviours based on both home thermal flexibility and requests from the utility grid. This paper develops a robust, hierarchical power dispatch scheme in the context of a residential distribution network. The formulation couples a unique, multiphase linear distribution optimal power flow (OPF) at the upper level with model predictive control (MPC)-based HVAC fleet controllers at the lower level. The proposed approach is tested on nearly 2000 homes with a three-phase distribution network in an intraday market setting, where two major applications are explored and analysed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reversal of Catalytic Material Substrate Selectivity through Partitioning of Polymers in Hierarchically Ordered Virus-like Particle Frameworks

Control over the selectivity of catalytic materials is a topic of growing interest. Virus-like particle (VLP) based materials such as protein macromolecular frameworks (PMFs) are promising for catalytic applications due to their ease of assembly, modular ability to encapsulate a variety of enzymes, and ease of separation from a reaction mixture. Here we demonstrate the reversal of the initially negative material charge through the titration of a positively charged polymer into the material, causing the reversal of guest molecule uptake and enzymatic activity of PMFs. The charge-inverse material partitions a charged enzyme substrate to concentrate the substrate near an enzyme incorporated within the material, generating up to 5.9-fold increases in enzyme activity toward the partitioned substrate over the excluded substrate. Here we also show that the polymer distributes heterogeneously through the material up to a point of saturation and the effects of guest macromolecules on the lattice parameters of PMFs.

36 MATERIALS SCIENCE↗

Post-Modification of Crystalline Peptoid Nanomembranes with Active Nanoparticles for Efficient Photooxidation of a Mustard Gas Simulant

Peptoids (or poly-N-substituted glycines) hold immense potential for assembling into hierarchically structured functional materials via controlled molecular interactions. To create self-assembled materials with tailored functionalities, peptoid sequences are often conjugated with reactive or recognition motifs to enable applications including specific binding, biomimetic catalysis, and fluorescence imaging. However, the direct integration of bulky functional motifs into peptoid sequences can disrupt assembly processes and structural outcomes. Herein, we present a post-modification strategy for functionalizing pre-formed 2D crystalline assemblies. Through introducing clickable active sites, such as azide, alkyne, or thiol groups into a peptoid sequence, site-specific conjugation is achieved post-assembly via efficient “click”-type reactions. This strategy enables the ordered alignment of functional groups and gold nanoparticles (Au NPs) on the surface of 2D peptoid nanomaterials with controlled density, while preserving their high crystallinity and structural integrity. Furthermore, we demonstrated that nanomembranes functionalized with both Au NPs and porphyrins enhance the efficiency and selectivity of the photooxidation of 2-chloroethyl ethyl sulfide, a simulant of sulfur mustard. This innovative strategy lays the groundwork for advancing peptoid-based functional materials across diverse applications, from catalysis to biomedicine.

Chemistry↗

Supramolecular Assembly of U(IV) Clusters and Superatoms with Unconventional Countercations

Superatoms are nanometer-sized molecules or particles that form ordered lattices, mimicking their atomic counterparts. Hierarchical assembly of superatoms gives rise to emergent properties in lattices of quantum dots, p-block clusters, and fullerenes. In this report, we introduce a family of uranium-oxysulfate cluster anions whose hierarchical assembly in water is controlled by two parameters: acidity and the lanthanide or transition-metal countercation. In acid, larger Ln III (Ln = La–Ho) link hexamer (U 6 ) oxoclusters into body-centered cubic frameworks, while smaller Ln III (Ln = Er–Lu and Y) promote linking of 14 U 6 clusters into hollow superclusters (U 84 superatoms). U 84 assembles into superlattices including cubic-closest packed, body-centered cubic, and interpenetrating networks, bridged by interstitial countercations and U 6 clusters. Divalent transition metals (TM = Mn II and Zn II ) charge-balance and promote the fusion of 10 U 6 and 10 U monomers into a wheel-shaped cluster (U 70 ). Dissolution of U 70 in organic media shows (by small-angle X-ray scattering) that differing supramolecular assemblies are accessed, controlled by TM II -linking of U 70 clusters. Magnetic measurements of these assemblies reveal Curie–Weiss behavior at high temperatures, without pairing of the 5f 2 -electrons down to 2 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Randomization-Based, Zero-Trust Cyberattack Detection Method for Hierarchical Systems

This paper demonstrates a novel randomization-based approach for verifying power system control signals with application to detecting cyberattacks. We consider fully connected hierarchical systems containing multiple local agents and a global "trust" agent. The global agent uses a time-varying randomized assignment scheme to identify corrupt network links based on principles of zero trust and majority rule. To evaluate the performance of this detection approach, we implement our algorithm in MATLAB and run it against nearly 43 million unique attack scenarios spanning a range of system sizes. For each scenario, the algorithm determines whether the identified corruptions satisfy a set of validity constraints reflecting network topology and uses that result to say whether the recovered state value for one or more local agents is malicious. We compare the algorithm's determination to the true state of the system to assess performance and find that classification accuracy converges to 100% as system size increases, suggesting that the validity constraints become more difficult to satisfy for larger systems. We further explore the scenarios that evade detection to understand practical implications for employing this detection approach.

cybersecurity↗

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation

This paper combines model-based and data-driven methods to develop a hierarchical, decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level and hence significantly speed up the computational time. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system, and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗

Multilayered Ordered Protein Arrays Self-Assembled from a Mixed Population of Virus-like Particles

Biology shows many examples of spatially controlled assembly of cells and biomacromolecules into hierarchically organized structures, to which many of the complex biological functions are attributed. While such biological structures have inspired the design of synthetic materials, it is still a great challenge to control the spatial arrangement of individual building blocks when assembling multiple types of components into bulk materials. Here, in this study, we report self-assembly of multilayered, ordered protein arrays from mixed populations of virus-like particles (VLPs). We systematically tuned the magnitude of the surface charge of the VLPs via mutagenesis to prepare four different types of VLPs for mixing. A mixture of up to four types of VLPs selectively assembled into higher-order structures in the presence of oppositely charged dendrimers during a gradual lowering of the ionic strength of the solution. The assembly resulted in the formation of three-dimensional ordered VLP arrays with up to four distinct layers including a central core, with each layer comprising a single type of VLP. A coarse-grained computational model was developed and simulated using molecular dynamics to probe the formation of the multilayered, core-shell structure. Our findings establish a simple and versatile bottom-up strategy to synthesize multilayered, ordered materials by controlling the spatial arrangement of multiple types of nanoscale building blocks in a one-pot fabrication.

59 BASIC BIOLOGICAL SCIENCES↗

A hierarchical gray-box dynamic modeling methodology for direct-expansion cooling systems to support control stability analysis; Méthodologie de modélisation dynamique hiérarchique de type boîte grise pour les systèmes de refroidissement à détente directe afin de soutenir l'analyse de stabilité de la commande

In this paper, a gray-box dynamic modeling approach for direct-expansion cooling systems is presented. The overall approach incorporates a multi-stage training procedure that consists of 1) identification of component sub-models from quasi-steady-state performance data, 2) system model integration with estimation of refrigerant charge and 3) fine tuning of thermal capacitances of the evaporator and condenser to capture the system dynamic responses. Compared to traditional physics-based models, the proposed modeling approach has advantages including reduced engineering efforts in the model development phase, improved computational efficiency and enhanced prediction accuracy. The modeling method was validated using a 3-ton variable-speed heat pump and proved to be capable of accurately predicting the system transient behaviors over a wide range of operating conditions. The established dynamic model was then applied for control stability analysis, with a specific goal of determining a proper control execution time step. The case study results showed that the stable control execution time step could change significantly, from 3 sec to 19 sec, as the operating conditions and control settings vary, and a proper selection of the execution time step is critical to ensure stable and reliable operations.

42 ENGINEERING↗