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At least 109 records · Page 6

Autonomous Restoration of Networked Microgrids Using Communication-Free Smart Sensing and Protection Units

Here this paper presents autonomous restoration of networked microgrids using distributed energy resources (DERs), inverter-based resources (IBRs) in general, and controllable assets of intelligence without communication to achieve a extremely resilient power system restoration. The main innovation of this work lies in use of real-time smart sensing and decision making that enable autonomous recombination of islanded microgrids, which are individually black-started by local grid-forming (GFM) inverter units. The smart circuit breakers (SCBs) designed and demonstrated here play critical roles in the restoration process to achieve autonomy; the autonomous restoration scheme is not pre-engineered and may be subject to encounter overloading, live or downed segments as the boundary of the microgrids dynamically expands without prior knowledge and only with local measurement. We demonstrate autonomous microgrid restoration both in simulation of a modified IEEE 13-bus system, and in a hardware testbed comprising 24 GFM-IBRs and 6-SCBs, depicting several scenarios to evaluate their functionalities and interoperability. This work validates high potential of extremely resilient microgrid using novel approaches for inverter-based bottom-up system restoration in a communication-free paradigm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗

A Self-Organizing Nano Grid (SONG) for Energy Access Clusters

In this paper, a bottom-up dc Self-Organizing Nano Grid (SONG) for rural electrification at ultra-low-cost through a flexible and scalable topology is presented. The proposed nano grid requires no communication and uses dc-bus signaling to convey excess energy in the system through the bus voltage, allowing independent agents to conduct energy transactions based on their needs in a decentralized manner. Moreover, this article proposes a concept that uses a novel multi-source, multi-segment droop control strategy with demand coordination, allowing for dynamic self-balancing of the system under fluctuating operating conditions. The unique use of a surplus photovoltaic (PV) power droop mode precisely estimates energy availability to minimize load chattering that helps in stabilizing the dc-bus. In addition, this architecture uses standard dc/dc converters for a low-cost, modular, Plug and Play ( PnP ) solution with highly automated operation, enabling local assembly, operation, and maintenance by non-technical personnel. The proposed SONG concept was validated in simulation and with a 700W, laboratory-scale, custom made nano grid system. The simulation and experimental test cases show the feasibility of the SONG system by demonstrating the proposed multi-source, multi-segment droop control strategy without load chattering under varying operating conditions.

dc-dc converter↗

A hybrid machine-learning approach for analysis of methane hydrate formation dynamics in porous media with synchrotron CT imaging

Fast multi-phase processes in methane hydrate bearing samples pose a challenge for quantitative micro-computed tomography study and experiment steering due to complex tomographic data analysis involving time-consuming segmentation procedures. This is because of the sample's multi-scale structure, which changes over time, low contrast between solid and fluid materials, and the large amount of data acquired during dynamic processes. Here, a hybrid approach is proposed for the automatic segmentation of tomographic data from time-resolved imaging of methane gas-hydrate formation in sandy granular media, which includes a deep-learning 3D U-Net model. To prepare a training dataset for the 3D U-Net, a technique to automate data labeling based on sample-specific information about the mineral matrix immobility and occasional fluid movement in pores is proposed. Automatic segmentation allowed for studying properties of the hydrate growth in pores, as well as dynamic processes such as incremental flow and redistribution of pore brine. Results of the quantitative analysis showed that for typical gas-hydrate stability parameters (100 bar methane pressure, 7°C temperature) the rate of formation is slow (less than 1% per hour), after which the surface area of contact between brine and gas increases, resulting in faster formation (2.5% per hour). Hydrate growth reaches the saturation point after 11 h of the experiment. Finally, the efficacy of the proposed segmentation scheme in on-the-fly automatic data analysis and experiment steering with zooming to regions of interest is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

On Practical Aspects of Variational Consistency in Contact Dynamics

Usage of contact mechanics methodologies is a pervasive modeling requirement in dynamic simulations. While for some trivial problems, solutions taken from analytical geometry are available, use of a finite element framework is common to achieve formulation generality. This work explores two dynamic contact formulations: one based on the traditional node-to-segment (NTS) approach, and a variationally consistent segment-to-segment (STS) mortar formulation. The NTS formulation employed here enforces the constraints kinematically (i.e., the interpenetration is enforced to the solver tolerance), whereas the mortar approach uses Lagrange multipliers to enforce the contact constraints. Both approaches are implemented in the open-source finite element framework Multiphysics Object-Oriented Simulation Environment (MOOSE). The results highlight two relevant contact-interface-related dynamic phenomena in finite element simulations. First, stabilization of contact constraints is discussed, taking into account the evolution of the total energy in a benchmark problem. Second, the influence of finite element discretization on both of the aforementioned contact formulations is analyzed by exercising a large-deformation example with continuous relative sliding. Variationally consistent contact approaches such as the mortar formulation lead to improved energy preservation and avoid spurious excitation of the system's frequencies. This is especially relevant in settings where inertia and vibrations are of importance.

42 ENGINEERING↗

Enhanced Ion Transport and Molecular Packing Stability in Asymmetric 2D Nanostructured π‐Conjugated Thieno[3,2‐b]Thiophene‐Based Liquid Crystal

Organic semiconductors based on liquid crystal (LC) molecules have attracted increasing interest. Here, in this work, two linear LCs based on 2,5‐bis(thien‐2‐yl)thieno[3,2‐b]thiophene (BTTT) mesogen are designed and synthesized, including BTTT/dEO3 with two symmetrically attached tri(ethylene oxide) groups and BTTT/mEO6 with one asymmetrically attached hexa(ethylene oxide) group. These two molecules have comparable functional‐group compositions but different molecular geometries, leading to their moderately different material performances. Both LCs show smectic mesophases with relatively low transition temperatures as confirmed by differential scanning calorimetry and polarized optical microscopy. A combination of experimental grazing incidence wide‐angle X‐ray scattering and molecular dynamics (MD) simulations reveals a herringbone packing motif of BTTT segments in both LCs while a smaller molecular tilt angle in BTTT/mEO6. Ionic conductivities are measured by doping LCs with different amounts of ionic dopants, lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). BTTT/mEO6 shows better smectic phase stability to higher LiTFSI doping ratios. Both LCs exhibit similar ionic conductivities in the smectic phases, but BTTT/mEO6 outperforms BTTT/dEO3 by a factor of three in the amorphous phase at higher temperatures. MD simulations, performed to examine the ion solvation environment, reveal that BTTT/mEO6 is more efficient in coordinating Li‐ions and screening their interactions with TFSI‐ions which further promote ionic transport.

grazing incidence wide-angle X-ray scattering↗

Disentangling Ferroelectric Wall Dynamics and Identification of Pinning Mechanisms via Deep Learning

Field-induced domain-wall dynamics in ferroelectric materials underpins multiple applications ranging from actuators to information technology devices and necessitates a quantitative description of the associated mechanisms including giant electromechanical couplings, controlled nonlinearities, or low coercive voltages. While the advances in dynamic piezoresponse force microscopy measurements over the last two decades have rendered visualization of polarization dynamics relatively straightforward, the associated insights into the local mechanisms have been elusive. This work explores the domain dynamics in model polycrystalline materials using a workflow combining deep-learning-based segmentation of the domain structures with nonlinear dimensionality reduction using multilayer rotationally invariant autoencoders (rVAE). The former allows unambiguous identification and classification of the ferroelectric and ferroelastic domain walls. Here, the rVAE discovers the latent representations of the domain wall geometries and their dynamics, consequently providing insight into the intrinsic mechanisms of polarization switching, that can further be compared to simple physical models. The rVAE disentangles the factors affecting the pinning efficiency of ferroelectric walls, offering insights into the correlation of ferroelastic wall distribution and ferroelectric wall pinning.

36 MATERIALS SCIENCE↗

Instability of an electron-plasma shear layer in an externally imposed strain flow

The E x B shear instability of a two-dimensional (2D) filament (i.e., a thin, rectangular strip perpendicular to the magnetic field) of magnetized pure electron plasma is investigated experimentally in the presence of an externally imposed strain flow. Data are acquired using a specialized Penning–Malmberg trap in which strain flows can be applied in 2D by biasing segmented electrodes surrounding the plasma. The E x B drift dynamics are well-described by the Drift-Poisson equations, which are isomorphic to the 2D Euler equations describing ideal fluids. Thus, the experimental results correspond to the Rayleigh instability of a shear layer in a 2D ideal fluid, where the electron density is analogous to the fluid vorticity. Shear layers are prepared by stretching initially axisymmetric electron vortices using a strong, applied strain flow. The data at early times are in quantitative agreement with a linear model which extends Rayleigh’s work to account for the influence of an external strain flow. In the presence of weak strain, the system approximately maintains a phase relationship that corresponds to an instantaneous Rayleigh eigenmode. The instability develops into the nonlinear regime later in time and at smaller spatial scales as the strain rate is increased. A secondary vortex pairing instability is observed, but it is suppressed when the strain-to-vorticity ratio exceeds roughly 0.025. In this way, vorticity transport perpendicular to the filament is diminished due to the applied strain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum algorithm to simulate Lindblad master equations

We present a quantum algorithm for simulating a family of Markovian master equations that can be realized through a probabilistic application of unitary channels and state preparation. Our approach employs a second-order product formula for the Lindblad master equation, achieved by decomposing the dynamics into dissipative and Hamiltonian components and replacing the dissipative segments with randomly compiled, easily implementable elements. The sampling approach eliminates the need for ancillary qubits to simulate the dissipation process and reduces the gate complexity in terms of the number of jump operators. We provide a rigorous performance analysis of the algorithm. We also extend the algorithm to time-dependent Lindblad equations, generalize the family of Markovian master equations it can be applied to, and explore applications beyond the Markovian noise model. A new error bound, in terms of the diamond norm, for second-order product formulas for time-dependent Liouvillians is provided that might be of independent interest. Published by the American Physical Society 2025

Borras, Evan (ORCID:000900017709037X)↗

Ionic-content-driven restructuring of spirobisindane ionene networks: implications for mechanics, self-healing, and gas transport

Polymers of intrinsic microporosity (PIMs) offer exceptional gas permeability but remain brittle and susceptible to physical aging, limiting their durability in separation applications. Here, we introduce a reconfigurable microporous polymer network that uniquely integrates permanent PIM microporosity with autonomous, intrinsic self-healing driven by imidazolium-based ionic motifs. Spirobisindane units generate the intrinsic free-volume architecture, while an imidazolium-containing polyamide ionene supplies dynamic ionic and hydrogen-bonding interactions that reorganize under mild activation. Incorporation of imidazolium-based ionic liquids further tunes cohesion, mobility, and densification, enabling the network to relax, re-associate, and retain microporosity without structural collapse. Through a comprehensive multiscale approach combining spectroscopy, scattering, thermal and mechanical characterization with all-atom molecular dynamics and density functional theory calculations, we elucidate how ionic content, as a single control parameter that reshapes free-volume distributions, modulates local coordination environments, and governs relaxation and healing kinetics. At intermediate ionic loadings, the networks achieve rapid, repeatable self-healing while maintaining CO$_2$ selectivity, demonstrating an optimal balance between segmental mobility and structural integrity. By establishing how hierarchical ionic interactions couple structure, dynamics, and transport in microporous ionene networks, this work provides generalizable design rules for adaptive soft-matter systems that require simultaneous mechanical resilience, reconfigurability, and selective gas transport.

36 MATERIALS SCIENCE↗

ReaxFF reactive force field model enables accurate prediction of physiochemical and mechanical properties of crystalline and amorphous shape‐memory polyurethane

Abstract We investigate reactive force field (ReaxFF) prediction of physiochemical and mechanical properties, and stimuli response behavior of a shape‐memory polyurethane (SMPU) rigid segment. We used SMPUs as a platform to link the rigid/hard segment domain crystallinity with properties that can also be experimentally measured. Specifically, we developed models for crystalline and amorphous forms of a common rigid segment of SMPUs, for example, 4,4′‐diphenylmethane diisocyanate (MDI) with n‐butanediol (BDO), denoted as MDI‐BDO. ReaxFF molecular dynamics simulations with equilibrium dynamics are performed by controlling mass, temperature, and pressure or volume to predict the structural and physiochemical properties of crystalline and amorphous rigid segments of SMPU systems, followed by simulating their XRD and FTIR patterns, respectively. Non‐equilibrium ReaxFF simulations are implemented by using uniaxial box deformation technique to study response‐behavior of crystalline SMPU under tensile loading and during stress‐relaxation. The model and simulation scheme presented in this study demonstrates a robust theoretical pathway toward application‐dictated, on‐demand design of high‐performance SMPUs in applications such as soft robotics.

Afroz, Mohammad M.↗

Coupling sensor to enzyme in the voltage sensing phosphatase

Voltage-sensing phosphatases (VSPs) dephosphorylate phosphoinositide (PIP) signaling lipids in response to membrane depolarization. VSPs possess an S4-containing voltage sensor domain (VSD), resembling that of voltage-gated cation channels, and a lipid phosphatase domain (PD). The mechanism by which voltage turns on enzyme activity is unclear. Structural analysis and modeling suggest several sites of VSD-PD interaction that could couple voltage sensing to catalysis. Voltage clamp fluorometry reveals voltage-driven rearrangements in three sites implicated earlier in enzyme activation—the VSD-PD linker, gating loop and R loop—as well as the N-terminal domain, which has not yet been explored. N-terminus mutations perturb both rearrangements in the other segments and enzyme activity. Our results provide a model for a dynamic assembly by which S4 controls the catalytic site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advanced Structured Adsorbent Architectures for Transformative Carbon Dioxide Capture Performance (Final Report)

Svante is a world leader at using solid sorbents for low-cost Carbon Dioxide (CO 2 ) capture, a technology which is recognized as critical in meeting the dual mandates of energy security/reliability and the mitigation of man-made CO 2 emissions. Svante has been developing proprietary adsorbent material compositions, forming them into structured laminates, developing and optimizing process cycles, and system design for efficient capture of CO 2 from post-combustion flue gases of thermal power plants and industrial facilities. The deployment of first-generation CO 2 capture technology has been significantly hampered by high costs and energy penalties, among other barriers. Second generation CO 2 capture technologies (including the Mark I variant of Svante’s Veloxotherm™ adsorption-based technology), utilizing single adsorbent architecture, show promise for reducing the barriers to deploying CO 2 capture plants in commercially meaningful numbers. The objective of this project was to evaluate the Recipient’s transformational (Mark-II) VeloxoTherm™ Technology via the development and bench-scale testing of an advanced structured adsorbent, including novel Bi-layer, laminated adsorbent structures and segmented beds. Svante selected, synthesized, and characterized tailored solid adsorbents for computational modeling, advanced structured adsorbent development, process simulations, and dynamic bench scale (~1-10 kg/day CO 2 captured) testing using an existing single-bed VeloxoTherm™ Station (VTS) coupled with a natural gas-fired boiler. Segmented beds used the in-house, multi-bed Process Demonstration Unit (PDU) to demonstrate key performance indicators (KPIs), such as recovery, product purity, regeneration energy, and the integrated system's productivity in lifetime analysis. Segmented beds were used at a 1 tonne per day (TPD) unit at an industrial site to provide bench-scale validation of performance in an industrial setting. Svante was developing and optimizing the post-combustion CO 2 adsorption technology architectures, including the Bi-layer and segmented laminated adsorbent structure design, integrated rapid cycle temperature swing adsorption (RC-TSA) cycle, flow path architecture, and adsorbent bed construction and packaging (including gas porting) to progress towards achievement of DOE’s Transformational CO 2 Capture goals of 95% CO 2 purity and a cost of electricity at least 30% lower than a supercritical Pulverized Coal (PC) power plant with CO 2 capture, or approximately $30 per tonne of CO 2 captured ready for demonstration by 2030. The main requirements to reach the DOE target cost of carbon capture below $30/MT using Rapid-Cycling Temperature Swing Adsorption (RC-TSA) are as follows: (1) Increased capacity at different CO 2 concentrations, (2) Increased sorbents cycle life, (3) Increased O 2 resistance, and (4) Decreased steam requirement to extract 1 kg of CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗

Dynamics of poly[n]catenane melts

Inspired by advances in the chemical synthesis of interlocking polymer architectures, extensive molecular dynamics simulations have been conducted to study the dynamical properties of poly[n]catenanes-polymers composed entirely of interlocking rings-in the melt state. Both the degree of polymerization (number of links) and the number of beads per ring are systematically varied, and the results are compared to linear and ring polymers. Herein, a simple Rouse-like model is presented, and its analytical solution suggests a decomposition of the dynamics into "ring-like" and "linear-like" regimes at short and long times, respectively. In agreement with this picture, multiple sub-diffusive regimes are observed in the monomer mean-squared-displacements even though interchain entanglement is not prevalent in the system. However, the Rouse-type model does not account for the topological effects of the mechanical bonds, which significantly alter the dynamics at intermediate length scales both within the rings and at the chain segment scales. The stress relaxation in the system is extremely rapid and may be conveniently separated into ring-like and linear-like contributions, again in agreement with the Rouse picture. However, the viscosity has a non-monotonic dependence on the ring size for long chains, which disagrees strongly with theoretical predictions. This unexpected observation cannot be explained in terms of chain disentanglement and is inconsistent with other measures of polymer relaxation. Possible mechanisms for this behavior are proposed and implications for materials design are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-Domain Vortex Induced Vibration Modeling of Reference Dynamic Power Cable for the Gulf of Maine

Vortex-induced vibration (VIV) is a phenomenon known to decrease the fatigue life of dynamic power cables used in floating offshore wind systems through increased bending loading cycles. A variety of modeling solutions have been proposed to study this, but none enable fully-coupled simulations leveraging open-source tools. To address this, a time-domain VIV model has been successfully implemented into the open-source mooring dynamics model MoorDyn. The semi-empirical VIV model describes a lift force acting on segments of a flexible cylinder, making it well suited for implementation into MoorDyn. The new capability successfully predicted the frequencies and magnitudes of strain in both steady and oscillating flows when compared to the original validation results and matched peak spectral response when compared to experimental results, verifying successful implementation. MoorDyn with VIV was then leveraged to simulate a 15 MW floating turbine with a dynamic power cable in the Gulf of Maine using OpenFAST for six return periods of combined wind, wave, and current conditions. Increased curvature and tension fluctuations in higher flow speeds were observed when simulating VIV. Maximum tensions and curvatures also increased, with the 500 year conditions violating the curvature factor of safety of 2.0. These results highlight the importance of considering VIV when designing dynamic power cables for the Gulf of Maine, and indicate that cost effective mitigation strategies should be explored for the area. They also demonstrate the utility of this new modeling capability, which provides the first open-source tool for fully coupled time-domain floating offshore wind simulations with dynamic power cable VIV.

17 WIND ENERGY↗

Effects of Intra- and Interchain Interactions on Exciton Dynamics of PTB7 Revealed by Model Oligomers

Recent studies have shown that molecular aggregation structures in precursor solutions of organic photovoltaic (OPV) polymers have substantial influence on polymer film morphology, exciton and charge carrier transport dynamics, and hence, the resultant device performance. To distinguish photophysical impacts due to increasing π-conjugation from chain lengthening and π–π stacking from single/multi chain aggregation in solution and film, we used oligomers of a well-studied charge transfer polymer PTB7 with different lengths as models to reveal intrinsic photophysical properties of a conjugated segment in the absence of inter-segment aggregation. In comparison with previously studied photophysical properties in polymeric PTB7, we found that oligomer dynamics are dominated by a process of planarization of the conjugated backbone into a quinoidal structure that resembles the self-folded polymer and that, when its emission is isolated, this quinoidal excited state resembling the planar polymer chain exhibits substantial charge transfer character via solvent-dependent emission shifts. Furthermore, the oligomers distinctly lack the long-lived charge separated species characteristic of PTB7, suggesting that the progression from charge transfer character in isolated chains to exciton splitting in neat polymer solution is modulated by the interchain interactions enabled by self-folding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗