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At least 199 records · Page 11

Modulation of the Electronic and Vibrational Landscape in Lead Organic Chalcogenides

Metal organic chalcogenides (MOCs) are an emerging class of two-dimensional (2D) materials featuring tunable band gaps and strong light-matter interactions with great potential for optical and polaritonic applications. Lead organic chalcogenides (LOCs) stand out among MOCs for sustaining long-lived coherent optical phonons despite their distorted lattices. However, the strong electron–phonon coupling also leads to rapid charge carrier self-trapping, hindering carrier transport. Herein, we demonstrate that charge carrier self-trapping is suppressed in Se- and Te-based LOCs. Specifically, the expansive Se and Te orbitals give rise to more dispersive conduction bands and reduced electron effective masses, thereby mitigating carrier self-trapping. As a result of reduced carrier self-trapping, the Se- and Te-based LOCs exhibit enhanced band-to-band photoluminescence and improved charge transport performance. Furthermore, our results provide a synthetic route to Se- and Te-based LOC single crystals and demonstrate the potential of orbital engineering to tune their electronic and phononic properties.

Chalcogenides↗

Phonon modes and electron–phonon coupling at the FeSe/SrTiO 3 interface

The remarkable increase in superconducting transition temperature (T c ) observed at the interface of one-unit-cell FeSe films on SrTiO3 substrates (1 uc FeSe/STO) has attracted considerable research into the interface effects. Although this high T c is thought to be associated with electron-phonon coupling (EPC), the microscopic coupling mechanism and its role in the superconductivity remain elusive. Here we use momentum-selective high-resolution electron energy loss spectroscopy to atomically resolve the phonons at the FeSe/STO interface. We uncover new optical phonon modes, coupling strongly with electrons, in the energy range of 75-99 meV. These modes are characterized by out-of-plane vibrations of oxygen atoms in the interfacial double-TiO x layer and the apical oxygens in STO. Our results also demonstrate that the EPC strength and superconducting gap of 1 uc FeSe/STO are closely related to the interlayer spacing between FeSe and the TiOx terminated STO. These findings shed light on the microscopic origin of the interfacial EPC and provide insights into achieving large and consistent T c enhancement in FeSe/STO and potentially other superconducting systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Average hydrodynamic radius analysis reveals critical solvation thresholds in high-concentration lithium electrolytes

Understanding the solvation structures of lithium salts in carbonate- and ether-based electrolytes is central to explaining the exceptional stability of high-concentration electrolytes (HCEs) and localized high-concentration electrolytes (LHCEs). Conventional techniques such as vibrational spectroscopy and one-dimensional NMR provide only limited information, typically restricted to coordination ratios and ion-pair distributions, without revealing the actual size and mass of solution complexes. Here, in this study, we introduce an average hydrodynamic radius (AHR) analysis based on internally referenced DOSY NMR, which enables direct estimation of the average volume and molecular weight of lithium–solvent complexes in solution. Using LiFSI–EMC and LiFSI–EMC–TTE electrolytes, we demonstrate that the onset of effective lithium metal stabilization and aluminum corrosion suppression coincides with the formation of very large complexes, whose average volume exceeds 300 times that of free EMC molecules. This finding supports a new “blocking mechanism,” wherein bulky solvated complexes impede direct solvent access to reactive surfaces. The AHR analysis thus not only clarifies the fundamental origin of HCE and LHCE effectiveness, but also provides a broadly applicable experimental framework for probing complex solvation structures and guiding rational electrolyte design.

Concentrated electrolytes↗

Leveraging design of experiments to build chemometric models for the quantification of uranium (VI) and HNO3 by Raman spectroscopy

Partial least squares regression (PLSR) and support vector regression (SVR) models were optimized for the quantification of U(VI) (10–320 g L −1 ) and HNO 3 (0.6–6 M) by Raman spectroscopy with optimized calibration sets chosen by optimal design of experiments. The designed approach effectively minimized the number of samples in the calibration set for PLSR and SVR by selecting sample concentrations with a quadratic process model, despite complex confounding and covarying spectral features in the spectra. The top PLS2 model resulted in percent root mean square errors of prediction for U(VI), HNO 3 , and NO 3 − of 3.7%, 3.6%, and 2.9%, respectively. PLS1 models performed similarly despite modeling an analyte with a majority linear response (i.e., uranyl symmetric stretch) and another with more covarying vibrational modes (i.e., HNO 3 ). Partial least squares (PLS) model loadings and regression coefficients were evaluated to better understand the relationship between weaker Raman bands and covarying spectral features. Support vector machine models outperformed PLS1 models, resulting in percent root mean square error of prediction values for U(VI) and HNO 3 of 1.5% and 3.1%, respectively. The optimal nonlinear SVR model was trained using a similar number of samples (11) compared with the PLSR model, even though PLS is a linear modeling approach. The generic D-optimal design presented in this work provides a robust statistical framework for selecting training set samples in disparate two-factor systems. This approach reinforces Raman spectroscopy for the quantification of species relevant to the nuclear fuel cycle and provides a robust chemometric modeling approach to bolster online monitoring in challenging process environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Knowledge Graph Approach to Analyze Systems and Assets Health

Nuclear power plants collect large amounts of equipment reliability data elements that contain information on the statuses of component, assets, and systems. All these data elements precisely record asset and system performance and health throughout the lifecycle of those assets and systems. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly focuses on the integration of numeric and textual data elements in order to assist plant system engineers in analyzing equipment reliability data. This task begins with preprocessing the data by extracting knowledge from textual data via natural language processing methods and quantifying system, asset, and component health based on numeric data. We then employed model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Data elements were then associated with a single MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 - MATHEMATICS AND COMPUTING↗

Environmental photosensitizers can exhibit enhanced actinic absorption in microhydrated clusters compared to solution

Brown carbon chromophores at environmental air-water interfaces often act as photosensitizers that absorb sunlight and subsequently transfer energy to nearby molecules, initiating a wide variety of chemical reactions. Despite their importance to understanding daytime chemistry at these airwater interfaces, little is known about the role of the solvation environment on the photophysical properties of these photosensitizers. In this work, we present a joint experimental-theoretical study of the vibrational and photophysical properties of microhydrated protonated and deprotonated 4-benzoylbenzoic acid (4-BBA), a key model system for environmental photosensitizers. We find that for protonated 4-BBAH + ∙(H 2 O) 0-1 , representing photosensitizers in very acidic conditions, a single bright state dominates the UV-Vis spectrum between 280 and 400 nm. Comparing the experimental UV-Vis spectra and quantum chemistry-predicted spectra of 4-BBA + ∙(H 2 O) 0-2 , we find that the degree of microhydration has little effect on the UV-Vis spectra or the orbitals of the dominant feature. For deprotonated 4-BBA ‒ , representing photosensitizers in basic conditions, quantum chemistry calculations predict that the UV-Vis spectra are ~3x weaker in intensity than the brightest 4-BBAH + ∙(H 2 O) 0-1 features and were not observed experimentally. Quantum chemistry calculations predict one dominant UV-Vis feature is present in the spectra of 4-BBA ‒ ∙(H 2 O) 0-2 , which exhibit minor shifts with degree of microhydration. While 4-BBA in bulk solution over a range of pH values has relatively weak absorption within the solar actinic region, we show that microhydrated 4-BBA has bright transitions within the actinic region. This indicates that the complex structure of environmental air-water interfaces can shift the absorption maximum of photosensitizers into the actinic region for enhanced absorption of sunlight and subsequent enhancement of photosensitizer-driven reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient simulation of open quantum systems coupled to a reservoir through multiple channels

It is challenging to simulate open quantum systems that are connected to a reservoir through multiple channels. For example, vibrations may induce fluctuations in both energy gaps and electronic couplings, which represent two independent channels of system–bath couplings. Systems of this kind are ubiquitous in the processes of excited state radiationless decay. Combined with density matrix renormalization group (DMRG) and matrix product states (MPS) methods, we develop an interaction-picture chain mapping strategy for vibrational reservoirs to simulate the dynamics of these open systems, resulting in time-dependent spatially local system–bath couplings in the chain-mapped Hamiltonian. This transformation causes the entanglement generated by the system–bath interactions to be restricted within a narrow frequency window of vibrational modes, enabling efficient DMRG/MPS dynamical simulations. We demonstrate the utility of this approach by simulating singlet fission dynamics using a generalized spin-boson Hamiltonian with both diagonal and off-diagonal system–bath couplings. This approach generalizes an earlier interaction-picture chain mapping scheme, allowing for efficient and exact simulation of systems with multi-channel system–bath couplings using matrix product states, which may further our understanding of nonlocal exciton–phonon couplings in exciton transport and the non-Condon effect in energy and electron transfer.

Chemistry↗

Experimental electronic structures of the Fe IV =O bond in S=1 heme vs. nonheme sites: Effect of the porphyrin ligand

High-valent Fe IV =O species are common intermediates in biological and artificial catalysts. Heme and nonheme S=1 Fe IV =O sites have been synthesized and studied for decades but little quantitative experimental comparison of their electronic structures has been available, due to the lack of direct methods focused on the iron. This study allows a rigorous determination of the electronic structure of a nonheme Fe IV =O center and its comparison to an Fe IV =O heme site using 1s2p resonant inelastic X-ray scattering (RIXS) and Fe L-edge X-ray absorption spectroscopy (XAS). Further, variable temperature magnetic circular dichroism (VT-MCD) of the ligand field transitions, combined with nuclear resonance vibrational spectroscopy of the two S=1 Fe IV =O systems show that the equatorial ligand field decreases from a nonheme to a heme Fe IV =O site. Alternatively, RIXS and Fe L-edge XAS combined with MCD show that the Fe dπ orbitals are unperturbed in the Fe IV =O heme relative to the nonheme site because the strong axial Fe-O bond uncouples the Fe dπ orbitals from the porphyrin π-system. As a consequence, the thermodynamics and kinetics of the H-atom abstraction reactions are actually very similar for heme compound II and nonheme Fe IV =O active sites.

bioinorganic chemistry↗

SAP-X2C: Optimally-Simple Two-Component Relativistic Hamiltonian with Size-Intensive Picture Change

We present a simple relativistic exact 2-component (X2C) Hamiltonian that models two-electron picture-change effects using Lehtola’s superposition of atomic potentials (SAP) [S. Lehtola, J. Chem. Theory Comput. 15, 1593−1604 (2019)]. The SAP-X2C approach retains the low cost and technical simplicity of the popular 1-electron X2C (1eX2C) predecessor but is significantly more accurate and has a well-defined thermodynamic limit, making it applicable to extended systems (such as large molecules and periodic crystals). The assessment of the SAP-X2C-based Hartree−Fock total and spinor energies, spin−orbit splittings, equilibrium bond distances, and harmonic vibrational frequencies suggests that SAP-X2C is similar to the more complex atomic meanfield (AMF) X2C counterparts in its ability to approximate the 4-component Dirac−Hartree−Fock reference.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distinct Kinetic Signatures of Photodesorption from Metal Nanoparticles

Visible photon fluxes can influence the rate and selectivity of heterogeneously catalyzed reactions on metal nanoparticle surfaces. Models describing the influence of photon fluxes have typically introduced photon flux dependent apparent thermal kinetic parameters (reaction orders, activation energies, binding energies, etc.). This has relied on empirical fitting of reaction rate data, making mechanistic interpretations of how photon fluxes influence elementary step rates challenging and inconsistent with fundamental descriptions of photochemistry on metal surfaces developed from surface science studies. Using the CO adsorption–desorption quasi-equilibrium reaction on Pt/Al 2 O 3 catalysts as a model system, we measured steady state adsorbed CO (CO*) coverages under isothermal and isobaric (1 mbar CO) conditions as a function of temperature (473–573 K) and of 440 nm photon flux ((0.1–5.2) × 10 3 # hv Pt site –1 s –1 ) using in situ IR spectroscopy. Steady state CO* coverage on Pt was photon flux dependent with increasing photon flux causing decreasing coverage, consistent with photons driving CO* desorption rates faster than thermal CO* desorption rates. However, photon flux dependent CO* coverages were essentially temperature independent, inconsistent with models that describe photon effects using perturbations to apparent thermal kinetic parameters. Instead, 120 steady state CO* coverages as a function of temperature and photon flux are quantitatively described by a kinetic model in which the overall desorption rate is a summation of independent thermal and photon induced CO* desorption rates. Site-resolved analysis reveals distinct kinetic parameters for photon driven desorption of CO* from well-coordinated, under-coordinated, and highly under-coordinated Pt sites, with temperature-dependent apparent quantum efficiencies (AQE) consistent with temperature dependence of vibrational quanta distribution of adsorbed CO. The rigorous kinetic rate laws for independent photon and thermal driven pathways allow for predictive modeling of the influence of photon fluxes on the rates of CO* desorption under catalytic conditions. Further, the analysis provides evidence that steady state continuous wave photon fluxes can drive desorption/adsorption reactions on metal surfaces out of thermal equilibrium, reconciling surface science observations of molecular photodesorption with applied catalysis. The work establishes a general kinetic framework to be considered for photon driven processes on metals, and defines catalyst, reaction, and photon flux characteristic design principles for breaking Sabatier limitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Central Cut Width on the Dynamical Characteristics of Box Assembly Structure

An investigation into the Box Assembly with Removable Component (BARC) structure is conducted by utilizing computational simulations and experimental structural testing in order to determine the complex dynamical responses instigated by the central cut of the system. Because the dynamics of the BARC system is complex, this study focuses primarily on analyzing the behavior of the box assembly (BA) system. The investigation explores the dynamics of the BA system by varying the central cut widths, ranging from a cut as wide as 0.5” cut to a 0.25” cut system, as well as a 0.1” cut and a system with no cut at all. Experimental testing is performed on each system including a free vibration test using an impact hammer to excite and identify the dominant frequencies of each structure. This testing is followed by pseudo-random vibration tests and swept sinusoidal excitation tests to determine the nonlinear aspects of these systems, such as the possible existence of nonlinear softening, hardening, and/or damping. The results show that nonlinear softening and nonlinear damping are present in each system. The no-cut system demonstrated the highest peak frequencies throughout all the tests, being the most rigid structure. The 0.25” cut system was shown to have the highest peak frequencies among all the cut systems in both the finite elemenet analysis (FEA) and impact testing. This trend did not continue, though, in the random and harmonic testing, possibly due to the added stiffness of the test setup with the slip table and stinger. The results show the importance of accurately measuring the central cut width and how possible geometric uncertainties change the overall dynamical behaviors of complex systems, such as natural characteristics, nonlinear responses, coupling of modes, and oscillating amplitudes.

Padilla, Christopher (ORCID:000900033446732X)↗

Comparison of Ce( iv )/Th( iv )-alkynyl complexes and observation of a trans -influence ligand series for Ce( iv )

Organometallic cerium(iv) complexes have been challenging to isolate and characterize due to the strongly oxidizing nature of the cerium(iv) cation. Herein, we report two cerium(iv) alkynyl complexes, [Ce(TriNOx)(C[triple bond, length as m-dash]C-SiMe3)] (1-CeTMS) and [Ce(TriNOx)(C[triple bond, length as m-dash]C-Ph)] (1-CePh) (TriNOx3- = tris(2-tert-butylhydroxylaminato)benzylamine), that include terminal alkyne moieties. The isostructural thorium analogue [Th(TriNOx)(C[triple bond, length as m-dash]C-SiMe3)] (1-ThTMS) was also synthesized and compared with 1-CeTMS in bond distance, 13C-NMR spectra, vibrational spectra and electronic structure. The Ce-C bond distances were 2.501(3) Å for 1-CePh and 2.513(5) Å for 1-CeTMS on the shorter end of the few reported CeIV-C single bonds (2.478(3)-2.705(2) Å), possibly indicating significant Ce 5d- and 4f-orbital involvement. 13C-NMR spectroscopy was also consistent with Ce-C covalency, with significantly deshielded resonances ranging from 185-213 ppm. Such 13C-NMR shifts demonstrate a strong influence from spin-orbit coupling (SOC) effects, corroborated by computational studies. Raman analysis showed ν C[triple bond, length as m-dash]C stretching frequencies of 2000 cm-1 (1-CeTMS) and 2052 cm-1 (1-CePh), indicating the cerium(iv)-alkynyl interaction, compared to the parent HC[triple bond, length as m-dash]CPh (IR = 2105 cm-1 and Raman = 2104 cm-1). L3-edge X-ray absorption measurements revealed a predominant Ce(iv) electronic configuration, and magnetic measurements revealed temperature-independent paramagnetism. Electrochemical studies similarly revealed the electron donating ability of the alkynyl ligands, stronger than either fluoride or imido ligands for the Ce(iv)(TriNOx)-framework, with a cerium(iv/iii) reduction potential of E pc = -1.58 to -1.66 V vs. Fc/Fc+. Evidence for a trans-influence has been observed by evaluating a series including previously reported [CeIV(TriNOx)X]+/0 complexes with axial ligands X = THF, I-, Br-, Cl-, F-, -C[triple bond, length as m-dash]C-Ph, -C[triple bond, length as m-dash]C-SiMe3, -NH(3,5-(CF3)2-Ar), -OSiPh3, -N(M(L))(3,5-(CF3)2-Ar) [M(L) = Li(TMEDA), K(DME)2 or Cs(2,2,2-crypt)]. These data stand in contrast with previous reports of an inverse trans-influence at cerium(iv) and point to differences in involvement of cerium 4f- versus 5d-orbitals in the electronic structures of the complexes.

Yang, Qiaomu↗

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

A new computational framework for spinor-based relativistic exact two-component calculations using contracted basis functions

Here, a new computational framework for spinor-based relativistic exact two-component (X2C) calculations is developed using contracted basis sets with a spin–orbit contraction scheme. Generally contracted, j-adapted basis sets of p-block elements using primitive functions in the correlation-consistent basis sets are constructed for the X2C Hamiltonian with atomic mean-field spin–orbit integrals (the X2CAMF scheme). The contraction coefficients are taken from atomic X2CAMF Hartree–Fock spinors, thereby following the simple concept of a linear combination of atomic orbitals. Benchmark calculations of spin–orbit splittings, equilibrium bond lengths, and harmonic vibrational frequencies demonstrate the accuracy and efficacy of the j-adapted spin–orbit contraction scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-dependent phenomena in correlated materials

Understanding time-dependent processes and light-matter interaction in strongly correlated materials, and the interplay between electronic, orbital, vibrational, and spin degrees of freedom, is a cornerstone of condensed matter. These mechanisms can be proven by measuring the response of the systems to time-dependent perturbations. The corresponding time scales are dictated by the way light couples to the different excitations, and how these excitations exchange energy and momentum. Our research advances our understanding of these processes, and the interpretation of different equilibrium and time-resolved spectroscopies. Our project encompasses two main themes: (i) developing and refining computational techniques to study non-equilibrium spectroscopies including non-perturbative effects and (ii) applications to non-equilibrium phenomena. We have developed a new computational approach that works directly in the time domain: by including all the degrees of freedom involved in the scattering process (e.g. electrons, photons, neutrons), we solve the time dependent problem: a faithful numerical simulation of the experiment. By measuring the energy and momentum of the outgoing particles, we can extract information about the energy and momentum absorbed by the system. Prior to our work, people attempting to model and calculate non-equilibrium spectral functions relied on a description of the scattering cross section based on a formulation in the frequency domain, a treatment that is extremely cumbersome and complex. Our technique works in and out of equilibrium and can reproduce spectra by several spectroscopic techniques, such as time-resolved photoemission, neutron scattering, Raman, X-ray spectroscopies (RIXS, Auger, XAS, XMCD), and, by not relying on analytical approximations, yields results that reveal novel overlooked transient mechanisms. These tools provide sorely needed intuition for understanding the phenomenology of strongly correlated materials and will help experimentalists in identifying signatures of relevant excitations in pump-probe experiments, such as those conducted in DOE supported facilities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Three-Dimensional Aerodynamics and Vortex-Shedding Characteristics of Wind Turbine Airfoils over 360-Degree Angles of Attack

In this work, we present the first three-dimensional (3D) computational investigation of wind turbine airfoils over 360° angles of attack to predict unsteady aerodynamic loads and vortex-shedding characteristics. To this end, static–airfoil simulations are performed for the FFA-W3 airfoil family at a Reynolds number of 107 with the Improved Delayed Detached Eddy Simulation turbulence model. Aerodynamic forces reveal that the onset of boundary-layer instabilities and flow separation does not necessarily coincide with the onset of stall. In addition, a comparison with two-dimensional simulation data and flat plate theory extension of airfoil polars, suggest that, in the deep stall regime, 3D effects remain critical for predicting both the unsteady loads and the vortex-shedding dynamics. For all airfoils, the vortex-shedding frequencies are found to be inversely proportional to the wake width. In the case of slender airfoils, the frequencies are nearly independent of the airfoil thickness, and their corresponding Strouhal number St is approximately 0.15. Based on the calculated St, the potential for shedding frequencies to coincide with the natural frequencies of the International Energy Agency 15 MW reference wind turbine blades is investigated. The analysis shows that vortex-induced vibrations occur primarily at angles of attack of around ±90° for all airfoils.

17 WIND ENERGY↗