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At least 109 records · Page 6

Resolving electrochemically triggered topological defect dynamics and structural degradation in layered oxides

Understanding topological defects-controlled structural degradation of layered oxides—a key cathode material for high-performance lithium-ion batteries—plays a critical role in developing next-generation cathode materials. Here, by constructing a nanobattery in an electron microscope enabling atomic-scale monitoring of electrochemcial reactions, we captured the electrochemically driven atomistic dynamics and evolution of dislocations—a most important topological defect in material. We deciphered how dislocations nucleate, move, and annihilate within layered cathodes at the atomic scale. Specifically, we found two types of dislocation configurations, i.e., single dislocations and dislocation dipoles. Both pure dislocation glide/climb and mixed motions were captured, and the dislocation glide and climb velocities were first experimentally measured. Moreover, dislocation activity-mediated structural degradation such as crack nucleation, phase transformation, and lattice reorientation was unraveled. Our work provides deep insights into the atomistic dynamics of electrochemically driven dislocation activities in layered oxides.

Wang, Chunyang (ORCID:0000000184613952)↗

2D-Covalent Organic Frameworks with Interlayer Hydrogen Bonding Oriented through Designed Nonplanarity

We report the synthesis and characterization of a new class of 2D-covalent organic frameworks, called COFamides, whose layers are held together by amide hydrogen bonds. To accomplish this, we have designed monomers with a nonplanar structure that arises from steric crowding, forcing the amide side groups out of plane with the COF sheets orienting the hydrogen bonds between the layers. Here, the presence of these hydrogen bonds provides significant structural stabilization as demonstrated by comparison to control structures that lack hydrogen bonding capability, resulting in lower surface area and crystallinity. We have characterized both azine and imine-linked versions of these COFs, named COFamide-1 and -2, respectively, for their surface areas, pore sizes, and crystallinity. In addition to these more conventional characterization methods, we also used variable temperature infrared spectroscopy methods and van der Waals density functional calculations to directly observe the presence of hydrogen bonding.

36 MATERIALS SCIENCE↗

Grid Forming Inverter: Laboratory-Scale Hardware Test Bed Setup and Weak Grid Operation

In recent times, the concept of grid forming inverters has gained popularity. Grid forming inverters have proven to be a promising alternative to the grid following inverters. In this paper, we present the hardware test bed implementation of grid forming inverter in islanding mode as well as in grid connected mode. The control structure includes inverter-level inner current control and outer voltage control, and plant-level P - f and Q - V droop control. The Q - V droop provides the voltage command, whereas P - f droop provides the frequency command and is also key for the synchronization process. While it is straightforward to set up the test bed for the islanded operation, it is a challenging process to set up the grid-forming inverter in the grid-connected mode. We present the key technologies and demonstrate the start-up process and weak grid operation using the hardware experiment results. Results from EMT model developed in MATLAB/SimPowerSystems are also presented for side-by-side comparison.

Mittal, Ratik↗

High‐Performance Al–S Batteries by Spin Polarization Modulation via Catalytic Ni‐MoS 2 Nanosheets

Aluminum–sulfur (Al–S) batteries catalysts with adsorption and catalytic capabilities can effectively improve the slow redox kinetics, but the current research often ignores the effect of optimizing the electronic structure of the catalyst on improving charge transfer and adsorption. Here, in this study, Ni-doped monolayer MoS 2 nanosheets are synthesized and used as a catalytic additive for the sulfur cathode. The addition of Ni promotes spin splitting of 4d orbital of Mo, thereby affecting polarization degree of the basal plane sulfur and making it change from a low spin state to a high spin one. This high spin configuration raises the electron energy level and provides an active electron state to react with aluminum polysulfides (AlPSs), which optimizes the adsorption energy. At the same time, it accelerates electron transfer and lowers the energy barrier for the overall conversion of the polysulfides. Benefiting from these features, Al–S batteries based on rationally designed S@Ni-MoS 2 /C cathodes exhibit a high initial capacity (1603.0 mAh g −1 at 0.5 A g −1 ) and extraordinary cycling stability (0.035% capacity decay rate during 2000 cycles). This study showcases a spin-polarized electronic structure control strategy to enhance catalytic activity, providing a viable approach for developing efficient catalysts for practical Al–S batteries.

Aluminum-sulfur batteries↗

High Interfacial-Energy and Lithiophilic Janus Interphase Enables Stable Lithium Metal Anodes

The stability of solid electrolyte interphase (SEI) layers is critical for developing lithium (Li) metal batteries. However, the fabrication of stable SEI layers is plagued by un-controlled structures, properties, and functions. In this work a controllable design of an ordered LiF-rich and lithiophilic hybrid Janus interphase (LiF-HJI) is reported using organic fluorination reagent as a functional SEI precursor. The LiF-HJI with a lower crystalline LiF layer and an upper Li organosulfide layer provides high interfacial energy with the Li metal and strong Li-ion affinity, allows homogenous Li-ion distribution, fast and uniform Li-ion transport, and excellent mechanical and passivation properties, enabling stable Li metal anodes under harsh conditions, such as high deposition capacities (6 mA h cm -2 ), current densities (10 mA cm -2 ), and rates (5 C). Stable LiF-HJI@Li greatly improves cycling stability and capacity retention (80.1% after 300 cycles) of Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 cells at a commercial-level areal capacity (≈4.2 mA h cm -2 ). Even under a lean-electrolyte condition of 3 g Ah -1 , 80% capacity retention can be maintained after 100 cycles, demonstrating excellent cycling performance under such harsh conditions.

25 ENERGY STORAGE↗

Signal-Compensation-Based Adaptive PID Control for Fused Magnesia Smelting Processes

For fused magnesia smelting processes, the proportional-integral-derivative (PID) controller is difficult to regulate the smelting currents within desired ranges due to unexpected variations of the dynamics caused by material feeding operations. To solve this problem, we first proposed its dynamic model composed of a linear model and an uncertain nonlinear dynamic system that describes the unknown time-varying dynamics of nonlinearity and strong couplings among controlled variables. Then, using the accurately calculated value of the uncertain part at the previous sampling time instant and the tracking error that reflects the influence of its change rate, we developed a feedforward and a one-step optimal control to obtain two signal compensators to eliminate the impact of frequent variations of the uncertainties. For the compensators, we proposed a weight selection method to minimize the sum of the squared tracking error with ensured closed-loop stability. Based on the abovementioned modeling and control structure, we finally developed a novel adaptive PID controller augmented with signal compensators to control the whole process. Industrial applications have shown that the proposed method can always keep the tracking error and the control input within their targeted ranges, leading to a significantly reduced energy consumption per ton and increased fused magnesia production.

Wang, Weizhou↗

Iterative Learning Control for Video-rate Atomic Force Microscopy

We present a control scheme for video-rate atomic force microscopy with rosette pattern. The controller structure involves a feedback internal-model-based controller and a feedforward iterative learning controller. The iterative learning controller is designed to improve tracking performance of the feedback-controlled scanner by rejecting the repetitive disturbances arising from the system nonlinearities. We investigate the performance of two inversion techniques for constructing the learning filter. We conduct tracking experiments using a two-degree-of-freedom microelectromechanical system (MEMS) nanopositioner at frame rates ranging from 5 to 20 frames per second. Furthermore, the results reveal that the algorithm converges rapidly and the iterative learning controller significantly reduces both the transient and steady-state tracking errors. We acquire and report a series of high-resolution time-lapsed video-rate AFM images with the rosette pattern.

42 ENGINEERING↗

Practical Challenges in Real-Time Demand Response

We report on a real-time demand response experiment with 100 controllable devices. The experiment reveals several key challenges in the deployment of a real-time demand response program, including time delays, uncertainties, characterization errors, multiple timescales, and nonlinearity, which have been largely ignored in previous studies. To resolve these practical issues, we develop and implement a two-level multi-loop control structure integrating feed-forward proportional-integral controllers and optimization solvers in closed loops, which eliminates steady-state errors and improves the dynamical performance of the overall building response. Furthermore, the proposed methods are validated by Hardware-in-the-Loop (HiL) tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling and control of cascaded bridgeless multilevel rectifier under unbalanced load conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality. The complete design process of the proposed converter is developed step by step in order to meet all the desired objectives. The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to mathematically derive requirements for the number of partially controlled and fully controlled H-bridges in the proposed H-bridge converter. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. After exploring various well-established control methods, a novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization, power factor correction, and elimination of zero crossing current distortion under both balanced and unbalanced load conditions. The converter can also be used for reactive power compensation in a grid tied power system if a sufficient number of fully controlled H-bridge modules are included. Processor-In-the-Loop (PIL) simulation has been the utilized to validate the performance of discrete control structure. Simulation and experimental results validate the models and control method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Recent experimental explorations of non-classical nucleation

Nucleation, the early stage of crystallization, is a key step in producing functional materials, but nucleation processes have yet to be understood in detail. Recent advanced characterization techniques, especially atomic force microscopy, liquid-cell transmission electron microscopy (TEM) and cryo-TEM, enable scientists to observe previously inaccessible nucleation details at the nanoscale. In this review, we summarize newly suggested non-classical nucleation models with respect to mechanistic understanding from experimental views, which highlight multi-step nucleation mechanisms. Different intermediated phases such as clusters at the pre-nucleation stage, liquid-like precursors, amorphous phases and even oligomers have been revealed, which play vital roles in nucleation and structure control. Moreover, these intermediated phases practically contribute in general to the structural variances of materials for nanoscience and nanotechnology. Overall, these studies ultimately enable us to control nucleation processes for materials synthesis.

Jin, Biao↗

PROACTIVE Focus Area 4: Structured Decision Metrics Analysis (Final Report)

A structured decision metrics analysis was developed as one of the tasks under PROACTIVE’s Focus Area 4 (FA4) and used structured decision metrics for processes, items, and facilities (PIF) to determine the efficacy of an M&V system in meeting treaty goals and technical objectives. The method starts with the functional decomposition of a “treaty” with the M&V system overlaid on it. A Functional Decomposition Rubric (FDR) for each PIF is used to determine a score ranging from 0 (weak) to 4 (strong) for assurance, security, and burden. The individual scores are combined to provide an overall Verification System Score (VSS) which assesses the overall verification system’s suitability given goals; scores for each step of the process are also given. The outcome of the evaluation is to identify needs or modifications to the enterprise model, verification system, or proposed testbed capabilities. VeriScore was used to evaluate FA4’s Spiral 0 exercise; those results are included in this report. The VeriScore and FDR framework can also be used in a non-treaty environment, as any goal/objective/method structure will work, thus expanding its applicability beyond traditional arms control structures.

99 GENERAL AND MISCELLANEOUS↗

Single Stage PLL-less Decoupled Active and Reactive Power Control for Weak Grid Interactive Inverters

This paper presents a single stage phase locked loop-less (PLL-less) active and reactive power (PQ) control for single-phase weak grid interactive inverters. The absence of the PLL requirement in the proposed PQ control enhances the stability margin comparing to conventional current control approaches in both the stationary or the synchronous reference frame. Additionally, the proposed control scheme enables direct PQ control with a single loop control structure. This paper demonstrates that the proposed PLL-less PQ control scheme is asymptotically stable if the controller gains are positive. The necessary conditions for supplying the rated active power into the weak grid are derived. The provided analysis shows that certain amount of reactive power injection is necessary to avoid point of common coupling (PCC) voltage collapse when the rated active power is injected into the weak grid. Several case studies are provided to demonstrate the performance of the proposed PLL-less PQ control scheme under weak grid condition.

Khan, Ahmad↗

Wind turbine blade design with airfoil shape control using invertible neural networks

Wind turbine blade design is a highly multidisciplinary process that involves aerodynamics, structures, controls, manufacturing, costs, and other considerations. More efficient blade designs can be found by controlling the airfoil cross-sectional shapes simultaneously with the bulk blade twist and chord distributions. Prior work has focused on incorporating panel-based aerodynamic solvers with a blade design framework to allow for airfoil shape control within the design loop in a tractable manner. Including higher fidelity aerodynamic solvers, such as computational fluid dynamics, makes the design problem computationally intractable. In this work, we couple an invertible neural network trained on high-fidelity airfoil aerodynamic data to a turbine design framework to enable the design of airfoil cross sections within a larger blade design problem. We detail the methodology of this coupled framework and showcase its efficacy by aerostructurally redesigning the IEA 15-MW reference wind turbine blade. The coupled approach reduces the cost of energy by 0.9% compared to a more conventional design approach. This work enables the inclusion of high-fidelity aerodynamic data earlier in the design process, reducing cycle time and increasing certainty in the performance of the optimal design.

17 WIND ENERGY↗

Polymorphism and Phase Control in Dion–Jacobson 2D 3-(Aminomethyl)piperidinium-Based Metal Iodide Perovskites

Two-dimensional halide perovskites exhibit rich structural diversity and tunable optoelectronic properties, making them promising materials for energy, sensing, and photonic applications. In this work, we report the structural mapping of four distinct polymorphs, γ (P2 1 /c), β (P4/mbm), α (P4/mmm), and δ (Cmcm) in the two-dimensional iodoplumbate, iodostannate, and iodogermanate perovskite so-called Dion-Jacobson series (3AMP)MI4 (M = Sn, Pb, Ge), where 3AMP is 3-(aminomethyl)piperidinium. The phases exhibit systematic evolution in octahedral distortion, lattice symmetry, and metal–halide geometry, enabling structural control over optoelectronic properties. Notably, the α-phase of (3AMP)SnI 4 represents a rare, ambient-stable, high-symmetry structure for Sn-based perovskites, without a phase transition down to 100 K. Variable-temperature single-crystal diffraction, powder x-ray diffraction (PXRD), and calorimetry reveal metal- and temperature-dependent polymorph interconversions, including the emergence of long range supercell reflections in Pb-rich compositions at low temperature. Optical spectroscopy and photoelectron yield spectroscopy confirm band gap tunability and band alignment trends, highlighting symmetry-dependent shifts and anomalous band gap bowing in mixed-metal systems, verified by electronic structure calculations. Calculations additionally indicate that the higher symmetry phases have reduced electron and hole effective masses compared to the lower symmetry phases.

36 MATERIALS SCIENCE↗

Robust trajectory-constrained frequency control for microgrids considering model linearization error

Grid supportive modes integrated within inverter-based resources can improve the frequency response of renewable-rich microgrids. The synthesis of grid supportive modes to guarantee frequency trajectory constraints under a predefined disturbance set is challenging but essential. To tackle this challenge, a numerical optimal control (NOC)-based control synthesis methodology is proposed. Without loss of generality, a wind-diesel fed microgrid is studied, where we aim to design grid supportive functions in the wind turbine. In the control design, linearized models are used, and the linearization-induced errors are quantitatively analyzed by reachability and interval arithmetics and represented in the form of interval uncertainties. Then, the NOC problem can be formulated into a robust mixed-integer linear program. The control structure is strategically configured into two levels to realize online deployment. The proposed control is verified on the modified 33-node microgrid with a full-order three-phase nonlinear model in Simulink. In conclusion, the simulation results show the effectiveness of the proposed control paradigm and the necessity of considering linearization-induced uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Local Distortions and Metal–Semiconductor–Metal Transition in Quasi-One-Dimensional Nanowire Compounds AV 3 Q 3 O δ (A = K, Rb, Cs and Q = Se, Te)

Metal cluster compounds have garnered renewed interest in the search for novel superconductors and topological semimetals owing to structural instabilities of metal-cluster geometries and broken symmetries. Here we synthesized needle-like crystals of the V-cluster-based quasi-one-dimensional (Q1D) materials AV 3 Q 3 O δ (A = K, Rb, Cs, Q= Se, Te) which can also be viewed as being composed of parallel nanowires. We examine how changes in their average and local structure control their electronic properties. All compounds crystallize in the TIFe 3 Te 3 -type structure (P6 3 /m space group) with infinite (V 3 )Q 3 ) - double-walled columnar chains separated by A + cations. Our single-crystal and synchrotron powder diffraction studies indicate oxygen atoms partially occupy the center site of the V 6 octahedral metal cluster cages in KV 3 Te 3 O 0.33 , RbV 3 Te 3 O 0.32 , and CsV 3 Te 3 O 0.35 , whereas KV 3 Se 3 is structurally oxygen-free. Our synchrotron X-ray pair distribution function (PDF) analyses indicate that the oxygen-free V 6 cluster octahedra in KV 3 Se 3 are highly distorted perpendicular to the chain direction even at room temperature, reducing the symmetry of the average structure from hexagonal P6 3 /m to monoclinic P2 1 /m. Our theoretical calculation supports this P2 1 /m distortion and suggests the structure further distorts to P2 1 or P2 1 /c at lower temperatures. In contrast, the oxygen-centered V-cluster in KV 3 Te 3 O 0.33 exhibits a V-3-triangle-trimerization along the chain direction. This feature is discernible from the local PDF and is consistent with lattice dynamical calculations based on density functional theory. Resistivity measurements indicate that KV 3 Se 3 exhibits metallic behavior, whereas a dramatic metal-semiconductor-metal transition emerges in KV 3 Te 3 O 6.33 , RbV 3 Te 3 O 0.32 , and CsV 3 Te 3 O 0.35 because of oxygen disorder and changes in local structure captured from our electronic structure analyses of the Fermi surface. Our investigation of the AV 3 Q 3 O 6 family demonstrates the importance of understanding local changes in structure driven by electronic instabilities, which can guide the search for new quantum materials in other low-dimensional cluster-compound materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insights into Supported Subnanometer Catalysts Exposed to CO via Machine-Learning-Enabled Multiscale Modeling

Subnanometer catalysts offer high noble metal utilization and superior performance for several reactions. However, understanding their structures and properties on an atomic scale under working conditions is challenging due to the large configurational space. Here, we introduce an efficient multiscale framework to predict their stability exposed to an adsorbate. The framework integrates a comprehensive toolset including density functional theory (DFT) calculations, cluster expansion, machine learning, and structure optimization. The end-to-end machine-learning workflow guides DFT data generation and enables significant computational acceleration. We demonstrate the approach for CO-adsorbed Pdn (n = 1–55) clusters on CeO 2 (111). Simulation results reveal that CO can facilitate restructuring by stabilizing smaller planar structures and bilayer structures of specific intermediate sizes, consistent with experimental reports. Metal–support interactions, preferential CO adsorption, and metal nuclearity and structure control catalyst stability. As a result, the framework allows automatic discovery of stable catalyst structures and a systematic strategy to exploit properties in the subnanometer scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗