Review of Small-Signal Converter-Driven Stability Issues in Power Systems
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42 ENGINEERING↗
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Multiscale Cryo Electron Microscopy Reveals Interfacial Degradation and Stabilization in Battery Electrodes
Electrochemical interfaces are dynamic systems, evolving based on their local environment and reactant surface structures. The electrode-electrolyte interface in Li-ion batteries can be protective, limiting parasitic reactions with the electrolyte to passivate the surface [1]. Additionally, this interphase has an impact on the Li-ion transport through that layer based on its composition, bonding environment, and thickness. These parameters are challenging to collect and may vary depending on the electrode surface site investigated relative to its spatial position in a coin cell. This study will detail a multiscale cryogenic electron microscopy approach where millimeter-scale cross-sections through the coin cell batteries were made using a cryogenic stage within a fs-laser plasma focused ion beam (laser PFIB) with complementary energy dispersive X-ray spectroscopy able to detect variations in the composition at electrode interfaces [2]. Microscale cross-sectioning and lamella sample preparation of battery electrodes was conducted at the Center for Integrated Nanotechnologies using a Ga-ion focused ion beam (FIB) with air-free and cryo-transfer [3], followed by nanoscale mapping of composition and bonding within the CEI through cryo-scanning transmission electron microscopy (cryo-STEM) electron energy loss spectroscopy [4]. This multiscale approach enabled identification of millimeter-scale features of a battery stack with visualization of degradation in electrodes such as cracks in cathode particles, gas evolution, and SEI evolution; microscale interfacial characteristics, such as heterogeneity in the SEI or barrier layer and identification of electrolyte networks to the electrode surfaces; and nanoscale measurement of the CEI thickness, mapping of transition metal bonding within the cathode particles to identify loss of active materials, and identification of beneficial electrolyte additives incorporated into the CEI structure. This multiscale approach allows for a statistical understanding of the primary mechanisms and parasitic degradation pathways that impact performance by limiting the ion transport pathways within Li+ batteries.
36 MATERIALS SCIENCE↗
Unraveling Morphology and Chemistry Dynamics in Fluoroethylene Carbonate Generated Silicon Anode Solid Electrolyte Interphase Across Delithiated and Lithiated States: Relative Cycling Stability Enabled by an Elastomeric Polymer Matrix
The silicon solid electrolyte interphase (SEI) faces cyclical cracking and reconstruction due to the ∼350% volume expansion. Understanding the SEI dynamic morphology and chemistry evolution from delithiated to lithiated states is thereby paramount to engineering a stable Si anode. Fluoroethylene carbonate (FEC) is a preferred additive with widely demonstrated enhancement of the Si cycling. Thus, insights into the dynamics of the FEC-SEI may provide hints toward engineering the Si interface. Herein, complementary ATR-FTIR, AFM, tip IR, and XPS probing reveal the presence of an elastomeric polycarbonate-like matrix in the FEC-generated SEI which is absent from the FEC-free SEI. Adding FEC to the baseline 1 M LiPF 6 in EC:EMC (1:1) electrolyte promotes formation of a thinner and more conformal SEI, and subdues morphology and chemistry changes between consecutive half-cycles. From AFM, morphological stabilization of the FEC-SEI occurs earlier. Furthermore, conventional SEI biproducts such as Li 2 CO 3 and LiEDC appear in reduced quantities in the FEC-SEI implying a reduced quantity of Li-consuming species. The thin polymeric FEC-SEI enables deeper (de)lithiation of silicon. In conclusion, the enhanced mechanical compliance, chemical invariance, and reduced Li inventory consumption of the FEC-SEI are logically the key features underlying the Si cycling enhancement by FEC.
25 ENERGY STORAGE↗
Dataset for Cruz-O'Byrne et al (2026): "Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry"
Hydrologic disturbances from accelerated sea-level rise and the increasing frequency and intensity of storms and tidal flooding are altering biogeochemical processes in upland coastal forests, transforming these ecosystems into wetlands. However, the initial effects of flooding on belowground biogeochemistry and the mechanisms driving greenhouse gas dynamics and soil organic matter stability during the early stages of this transition remain poorly understood. This dataset presents the results of a mesocosm experiment conducted in a controlled, highly instrumented laboratory environment, in which freshwater and brackish water pulses were applied to intact soil monoliths from a temperate upland coastal forest to examine how floodwater chemistry influences soil biogeochemistry and organo-mineral interactions. All data files are plain-text CSV (comma-separated value), and no special software is required to read them. Details about the content of each file are available in the document “Dataset_readme”. The dataset consists of the following data: • rcruzobyrne_moisture: Soil volumetric water content (VWC) • rcruzobyrne_GHG: Headspace greenhouse gas (GHG) concentration and fluxes • rcruzobyrne_methane_isotopes: Headspace methane isotope signature • rcruzobyrne_porewater: Porewater chemistry • rcruzobyrne_CDOM: Porewater colored dissolved organic matter (CDOM) • rcruzobyrne_FTIR: Soil Fourier-transform infrared (FTIR) spectroscopy Details of the experimental setup, data collection, and data analysis are provided in the manuscript by Cruz-O’Byrne et al (2026) Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry. Biogeochemistry. https://doi.org/10.1007/s10533-026-01340-0
EARTH SCIENCE > ATMOSPHERE > GREENHOUSE GAS↗
Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar) (Final Technical Report)
Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power systems operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) - are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power system steady-state and dynamic performance. This project helps meet and exceed the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for power grid planning and operation. We have developed a temporally comprehensive, closed-loop simulation model, named Multi-timescale Integrated Dynamics and Scheduling (MIDAS), that seamlessly simulates power system operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). For schedules with very high levels of inverter-based resources (IBRs), up to and including 100%, the stability of grid controls has been evaluated through electromagnetic transient (EMT) simulations and power-hardware-in-the-loop (PHIL) simulations of key transient events at key schedule points. Specifically, MIDAS provides: 1) a closed-loop simulation framework for simulating timescales from economic scheduling to dynamic stability analysis; 2) machine learning-based stability assessment; 3) EMT modeling and analysis for large-scale power systems; 4) MIDAS PHIL test bed. We worked with Hawaii Electric Companies to apply the MIDAS study framework to a Maui grid study. The entire island's transmission system was modeled in detail - from a yearly scheduling model, to a second-level frequency dynamic model, down to a sub-second-scale EMT model to address critical stability issues. The project demonstrated how MIDAS can help system planners and operators assess system reliability and stability while the power grid is marching toward a high-renewable, high-IBR future. In this Maui grid study, we found that 100% instantaneous IBR operation is achievable in EMT simulation and PHIL testing, and grid planners and operators might need new analysis/simulation tools to assess grid reliability and stability in the scheduling stage. MIDAS will bring Maui and other systems closer to 100% clean and stable energy futures. (In this study, we examined transient stability. Other topics necessary for 100% IBR operation, such as protection and resource adequacy, were not examined.)
100% Renewables↗
A New Distributed Model-Free Control Strategy to Diminish Distribution System Voltage Violations
This paper proposes a new distributed model-free control (MFC) strategy for dynamic voltage control to diminish distribution systems' voltage violations. The objective is to maintain all critical load bus voltages within the acceptable ANSI Range A (+/- 5% of nominal). The distributed MFC strategy, which only requires local voltage measurements from designated load buses, controls online the reactive power generation of available synchronous generator (SG)-based and photovoltaic (PV)-based distributed generators (DGs). The distributed MFC strategy is computationally efficient and does not require modelling of the different system components and disturbances. Time-domain dynamic simulations are conducted for the 21-bus test distribution system fed by multiple DGs to verify the performance of the proposed MFC strategy, and the results are compared against the conventional model-based microgrid voltage stabilizer (MGVS) control strategy. The simulation results show that the distributed MFC strategy provides minimal voltage violations and achieves the dynamic voltage stability of the system under diverse disturbances.
Hatipoglu, Kenan↗
Efficient and Robust Dynamic Crosslinking for Compatibilizing Immiscible Mixed Plastics through In Situ Generated Singlet Nitrenes
Abstract Creating a sustainable economy for plastics demands the exploration of new strategies for efficient management of mixed plastic waste. The inherent incompatibility of different plastics poses a major challenge in plastic mechanical recycling, resulting in phase‐separated materials with inferior mechanical properties. Here, this study presents a robust and efficient dynamic crosslinking chemistry that effectively compatibilizes mixed plastics. Composed of aromatic sulfonyl azides, the dynamic crosslinker shows high thermal stability and generates singlet nitrene species in situ during solvent‐free melt‐extrusion, effectively promoting C─H insertion across diverse plastics. This new method demonstrates successful compatibilization of binary polymer blends and model mixed plastics, enhancing mechanical performance and improving phase morphology. It holds promise for managing mixed plastic waste, supporting a more sustainable lifecycle for plastics.
Chemistry↗
Single Atoms Anchored in Hexagonal Boron Nitride for Propane Dehydrogenation from First Principles
We report single-atom catalysts embedded in N-doped graphene have attracted great interest recently, but the hexagonal boron nitride (h-BN) is much less explored as a support. Using first principles density function theory and molecular dynamics, here we investigate the stability of Pt, Au, and Ru single atoms anchored at B and N vacancies on h-BN. We find that Pt and Ru single atoms are much more stable than Au on h-BN. We further examine propane dehydrogenation on these single-atom catalysts and find that Pt 1 at the B vacancy in h-BN and Ru 1 at the N vacancy in h-BN show excellent activity for propane dehydrogenation, as evidenced by low energy barriers for both dehydrogenation steps. Our work suggests that Pt and Ru single atoms anchored at vacancy sites in h-BN could be promising for propane dehydrogenation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Hygrothermal aging and recycling effects on mechanical and thermal properties of recyclable thermoplastic glass fiber composites
Abstract Glass fiber‐reinforced polymer composites are widely used in marine applications, including renewable energy devices and submarines, due to their strength‐to‐weight ratios and corrosion resistance. As sustainability becomes more important, recyclable thermoplastic composites are gaining attention in marine energy applications. These materials face harsh conditions such as high chloride water, UV radiation, pressurization, and thermal cycling, which can affect their durability and recyclability. This study examines the impact of hygrothermal aging on the recyclability of an Elium glass fiber (GF) composite. Samples were mechanically ground for recycling, and mechanical and thermal properties were compared between aged and unaged samples. After seawater aging, the tensile strength and modulus of the unaged composite dropped by 25% and 13% respectively, due to water ingress along the fiber‐matrix interface. The recycled composite showed reduced flexural strength as the long fiber composite was converted into short fibers during the process. Differential scanning calorimetry (DSC) revealed no change in glass transition temperature after aging. Weight loss (25%) was attributed to the thermal stability of the glass fibers. Dynamic mechanical analysis (DMA) showed that the storage modulus increased with aging, and fracture analysis confirmed a mixed mode of failure for aged composites. Highlights Hygrothermal aging lowers mechanical performance of Elium® GF composites. Failure mechanism tends to be matrix cracking and interface bonding. Glass transition temperature is not reduced by hygrothermal aging. Fractured composite was successfully recycled via thermoforming. Flexural strength of the recycled composite is lower.
17 WIND ENERGY↗
Slow manifolds of classical Pauli particle enable structure-preserving geometric algorithms for guiding center dynamics
Since variational symplectic integrators for the guiding center was proposed, structure-preserving geometric algorithms have become an active research field in plasma physics. We found that the slow manifolds of the classical Pauli particle enable a family of structure-preserving geometric algorithms for guiding center dynamics with long-term stability and accuracy. This discovery overcomes the difficulty associated with the unstable parasitic modes for variational symplectic integrators when applied to the degenerate guiding center Lagrangian. It is a pleasant surprise that Pauli's Hamiltonian for electrons, which predated the Dirac equation and marks the beginning of particle physics, reappears in classical physics as an effective algorithm for solving an important plasma physics problem. This technique is applicable to other degenerate Lagrangians reduced from regular Lagrangians.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Energy migration and scintillation kinetics in compositionally complex (Gd 1/4 Y 1/4 Tb 1/4 Lu 1/4 ) 3 Al 5 O 12 :Ce single crystal scintillator
It is well-established that compositional tuning through binary admixture can improve scintillation performance in several materials systems, including Ce-activated garnets. Although recent work on ternary or quaternary cation admixture shows promise, the impact of this increased compositional complexity on thermal stability and carrier-defect dynamics has not been addressed. Here, we investigate a compositionally complex garnet, (Gd 1/4 Y 1/4 Tb 1/4 Lu 1/4 ) 3 Al 5 O 12 :Ce (GYTLAG), grown by the Czochralski method using temperature-dependent photoluminescence (PL), PL decay, and thermoluminescence (TL). PL and PL decay measurements support a thermally activated Tb 3+ -Ce 3+ energy transfer, where Tb 3+ emission dominates below 60 K, but Ce 3+ emission increases from 20-300 K. Thermal quenching of Ce 3+ emission occurs around T 50 = 508 K, with an activation energy of 0.6 eV. TL and wavelength-resolved TL spectra from 20–500 K show that GYTLAG contains similar trap groups to LuAG but with a broader distribution of glow peaks below room temperature, possibly caused by quaternary cation mixing. A combination of dose dependence, partial cleaning and initial rise, and glow curve fitting to a first order continuous Gaussian distribution model are used to understand the contribution of electronic point defects to scintillation decay and afterglow at room temperature. Furthermore, these results inform how increased compositional complexity influences recombination dynamics in garnet scintillators.
Compositionally complex↗
Synthesis and Characterization of Radio-Halogenated Talazoparib Analogues for Imaging and Radioligand Therapy
Abstract Talazoparib (TZ) is a potent poly(ADP-ribose) polymerase 1/2 (PARP1/2) inhibitor that uniquely traps PARP complexes at sites of single-strand DNA damage thereby offering opportunities for targeted radioligand therapy. Radiolabeled halogenated TZ derivatives were synthesized using boronic ester precursors to enable incorporation of diagnostic and therapeutic radionuclides: 18F for PET imaging, 77Br for Auger electron radiotherapy, and 211At for targeted alpha radiotherapy. Copper-mediated radio-halogenation afforded racemic 18F-TZ, 77Br-TZ, and 211At-TZ in sufficient radiochemical yields (4.3 ± 2.6%, n = 33; 29.0 ± 12.0%, n = 4; 3.6 ± 3.8%, n = 9, respectively), ∼99% radiochemical purity and proven stability under formulation conditions. Molecular dynamics simulations of halo-TZ derivatives predicted an inverse relationship between halogen size and PARP1 binding affinity. Indeed, cell uptake of radio-halogenated TZ analogues indicated selective uptake in a panel of cell types that correlated with PARP1 levels but was inversely related to the atomic radii of the halogen series. Despite modest specific activity and specific uptake, 77Br-TZ showed significant cytotoxicity. Further investigation of 18F-TZ with 77Br-TZ as a radiotheranostic pair will be facilitated by the synthetic schemes herein.
Muzzioli, Riccardo [The University of Texas MD And↗
A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture
Metal-organic frameworks (MOFs) exhibit great promise for CO 2 capture. However, finding the best performing materials poses computational and experimental grand challenges in view of the vast chemical space of potential building blocks. Here, we introduce GHP-MOFassemble, a generative artificial intelligence (AI), high performance framework for the rational and accelerated design of MOFs with high CO 2 adsorption capacity and synthesizable linkers. GHP-MOFassemble generates novel linkers, assembled with one of three pre-selected metal nodes (Cu paddlewheel, Zn paddlewheel, Zn tetramer) into MOFs in a primitive cubic topology. GHP-MOFassemble screens and validates AI-generated MOFs for uniqueness, synthesizability, structural validity, uses molecular dynamics simulations to study their stability and chemical consistency, and crystal graph neural networks and Grand Canonical Monte Carlo simulations to quantify their CO 2 adsorption capacities. We present the top six AI-generated MOFs with CO 2 capacities greater than 2m mol g -1 , i.e., higher than 96.9% of structures in the hypothetical MOF dataset.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations
Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.
AI↗
Evolution of size-selected Pt cluster catalysts on prototypical oxide supports
The current quest for new pathways into sustainable, efficient and durable energy conversion technologies makes the used for a fundamental understanding of the atomic-scale phenomena underlying catalytic processes ever more pressing. In this context, characterizing catalyst particles in situ provides valuable information about the evolution of their composition, structure, oxidation state and charge state during an ongoing process. To disentangle the influence of individual parameters – temperature, pressure, gas composition, cluster size, as well as support acidity, redox state and defect density – it is crucial to control them precisely and separately in experiments. At the example of size-selected Pt n clusters – i.e. sub-nm particles defined to the exact number of atoms – on flat oxide supports, we follow their rich evolution phenomena via (synchrotron-based) X-ray photoelectron spectroscopy (XPS) and scanning tunnelling microscopy (STM) during temperature ramps and in various gas environments. Here, we present our experience with these highly defined, yet complicated-to-create samples in ultra-high vacuum (UHV) and at mbar pressures. We discuss their stability during transport to synchrotrons and under reaction conditions on three prototypical oxide supports and show the various phenomena that can be disentangled. Ptn clusters on the non-reducible silicon dioxide, SiO 2 , remain size-selected and show remarkable stability. Doping strongly influences the size-dependent binding energy shifts and changes the Pt response to oxidative and reaction conditions, which we attribute to different cluster geometries: p-type doping leads to wetting, enhanced sinter resistance and a diminished response to oxidative environments, compared to clusters on n-type doped samples. We compare the system with our previous findings of a similar change in dimensionality for Pt 20 clusters on the reducible ceria, CeO 2 (111), support, induced by modulation of its O vacancy density. The Pt n /CeO 2 system is particularly interesting for strategies to stabilize and redisperse Pt clusters dynamically. Finally, we study the evolution of Pt n clusters on another reducible oxide support, magnetite, Fe 3 O 4 (001), in 0.1 mbar alternating redox conditions at RT and elevated temperature. In analogy to findings previously reported for Pt/TiO 2 (110), the clusters either become encapsulated by a thin oxide film via strong metal–support interaction (SMSI) or deeply buried in the magnetite. Overall, our approach of following the evolution of size-selected clusters on oxide supports leads to fundamental atomic-scale insights on nano-scale catalyst materials, on our path to sustainable, dynamic and self-repairing catalysts.
Falling, Lorenz J. [Technical Univ. of Munich (Ger↗
Experimental and theoretical examination of shock-compressed copper through the fcc to bcc to melt phase transitions
Recent studies show a face-centered cubic (fcc) to body-centered cubic (bcc) transformation along the shock Hugoniot for several metals (i.e., Cu, Au, and Ag). Here, we combine laser-shock compression of Cu foils on nanosecond timescales with in situ x-ray diffraction (XRD) to examine the microstructural changes with stress. We study the fcc phase and the phase transition from fcc to bcc (pressures greater than 180 GPa). Textural analysis of the azimuthal intensities from the XRD images is consistent with transformation into the bcc phase through the Pitsch-distortion mechanism. We use embedded atom model molecular dynamics simulations to determine the stability of the bcc phase in pressure–temperature space. Finally, our results indicate that the bcc phase is stabilized only at high temperatures and remains stable at pressures greater than 500 GPa.
36 MATERIALS SCIENCE↗
A Novel Secondary Frequency Regulation with Optimal Priority Selection of AGC Contributions
Automatic generation control (AGC) is used to maintain acceptable frequencies during operation owing to fluctuations in load and variable resources. In conventional industry applications, the AGC signal is allocated to each generator according to the predispatched frequency regulation capacity or the order of economic efficiency. However, with the increasing integration of inverter-based resources (IBRs), the retirement of conventional synchronous generators (SGs) has posed new challenges to frequency control schemes because fewer of them are optional for AGC regulation. In this paper, we propose a novel model predictive control (MPC)-based frequency regulation model to reduce control cost and ensure stability, by considering different critical dynamic factors when optimally selecting the AGC units. The proposed control model – developed in a general form – comprehensively embeds characteristics such as generator ramping rates, reserve capacity, and operation cost. The model predictive control–based two-timescale AGC scheme enhances the capability of immunizing the power disturbance from types of resources by coordinating the control signals between faster IBRs and slower SGs. The case study’s proposed model is verified to be effective in synergistically enforcing different dynamic properties of AGC units into the frequency regulation scheme.
Jiang, Sufan [The University of North Carolina at ↗