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At least 307 records · Page 17

Vibronic Effects in the Ultrafast Interfacial Electron Transfer of Perylene-Sensitized TiO 2 Surfaces

We combine ultrafast transient absorption (TA) spectroscopy and nonadiabatic quantum dynamics simulations to describe the real-time unfold of vibronic effects on the photoabsorption of TiO 2 anatase sensitized with the (perylen-9-yl)carboxylate dye (Pe-COOH/TiO2). The excited state is mapped in time and frequency by ultrafast broadband spectroscopy while atomistic quantum dynamics is used to simulate the self-consistent vibronic effects. The TA map shows the lifetime of the electronic population generated in the S 1 state of the dye and the rise of the absorption D 0 –D 1 of the cation. The theoretical analysis reveals that the electron transfer from perylene into TiO2 is complete within 20 fs, in agreement with the 12 fs experimental measurement. Because of the structural relaxation produced by the photoinduced electron transfer, the optical gap decreases by 390 meV, in agreement with the D 0 –D 1 transition band. Furthermore, the reorganization energy estimated to be around 220 meV is mostly due to the energy shift of the HOMO level, since the electron transfer occurs in the wide-band limit with little dependence on reorganization energy modes. By assuming the Condon approximation and by making use of the mixed quantum/classical trajectories of the Pe-COOH/TiO 2 system, the absorption spectrum is calculated, and the broad features of the transient absorption spectrum are correlated to excited-state nuclear reorganization effects of the adsorbate dye. The reorganization energy modes are identified by the power spectrum of the velocity autocorrelation function, which shows the occurrence of nonequilibrium modes within the range 1000–1800 cm –1 as in-plane asymmetric C–C vibrations in the perylene dye. The vibrational modes with the strongest influence on the optical gap contribute to shifting the absorption spectrum up in energy by ~2000 cm –1 . Finally, the overall agreement between theory and experiment reveals the capabilities of both methods to study vibronic effects in molecular and extended systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Rotational Dynamics in Mixed CH 4 –CO 2 Hydrates: Insights from Molecular Dynamics Simulations

The impact of guest molecule composition on the rotational dynamics in CH 4 , CO 2 , and mixed CH 4 –CO 2 gas hydrates is investigated with classical molecular dynamics simulations. Rotational autocorrelation functions are calculated for the guest and host molecules in each hydrate composition from simulation trajectories at 10, 40, 190, and 270 K. Analysis of these functions for each molecule is further decomposed into cage type for each CH 4 and CO 2 guest and cage face for the H 2 O host. CH 4 becomes more constrained, and CO 2 gains freedom in the mixed guest systems. Mixing guest species in gas hydrates alters the intermolecular interaction environment, impacting the rotational motion of the guest molecules. This effect is also seen in the host lattice H 2 O molecules, as evidence of molecular rotations is seen in the CO 2 hydrate at 270 K during longer simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion Behavior of Differently Charged Molecules in Self-Assembled Organic Nanotubes Studied Using Imaging Fluorescence Correlation Spectroscopy

The diffusion behavior of fluorescent molecules within bolaamphiphile-based organic nanotubes (ONTs) was systematically explored using imaging fluorescence correlation spectroscopy (imaging FCS). Anionic sulforhodamine B (SRB), zwitterionic/cationic rhodamine B (RB) or cationic rhodamine 123 (R123) was loaded into ONTs having cylindrical hollow structures (ca. 10 nm in inner diameter) with amine and glucose groups on the inner and outer surfaces, respectively. Wide-field fluorescence video microscopy was used to acquire imaging FCS data for dye-doped ONTs in aqueous solutions of different ionic strengths (1 – 500 mM) at different pH (3.4 – 8.4). The diffusion behavior of these dyes was discussed on the basis of their apparent diffusion coefficients (D) that were determined by autocorrelating the time transient of fluorescence intensity at each pixel on an ONT. Molecular diffusion in the ONTs was significantly slowed by molecule-nanotube interactions, as shown by the very small D (10-1 – 10-2 µm2/s). The pH-dependence of D revealed that dye diffusion was basically controlled by electrostatic interactions associated with the protonation of the amine groups on the ONT inner surface. The pH-dependent change in D was observed over a wide pH range, possibly due to electrostatically induced variations in the pKa of the densely packed ammonium ions on the ONT inner surface. On the other hand, the influence of ionic strength on D was relatively unclear, suggesting the involvement of non-coulombic interactions with the ONTs in molecular diffusion. Notably, individual ONTs of different lengths (1 – 5 µm) afforded similar diffusion coefficients for each type of dye at each solution condition, implying that the properties of ONTs were uniform in terms of solute loading and release. These conclusions highlight the characteristics of molecular diffusion behavior within the ONTs, and will help in the design of organic nanotubes better suited for use as drug vehicles and contaminant adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Untangleing the effects of chain rigidity on the structure and dynamics of strongly adsorbed polymer melts

Here, we present a detailed analysis of coarse-grained molecular dynamics simulations of semiflexible polymer melts in contact with a strongly adsorbing substrate. We have characterized the segments in the interfacial layer by counting the number of trains, loops, tails and unadsorbed segments. For more rigid chains, a tail and an adsorbed segment (a train) dominate while loops are more prevalent in more flexible chains. The tails exhibit a non-uniformly stretched conformation akin to the polydispersed pseudobrush envisioned by Guiselin. To probe the dynamics of the segments we computed the layer z-resolved intermediate coherent collective dynamics structure factor, S(q, t, z), mean-square displacement of segments, and the 2nd Legendre polynomial of the time-autocorrelation of unit bond vectors, 2 [n i (t,z)•n i (0,z)]>. Our results show that segmental dynamics is slower for stiffer chains and there is a strong correlation between the structure and dynamics in the interfacial layer. There is no glassy layer, and the slowing down in dynamics of stiffer chains in the adsorbed region can be attributed to the densification and the more persistent layering of segments.

36 MATERIALS SCIENCE↗

Visualization of Mesoscopic Conductivity Fluctuations in Amorphous Semiconductor Thin-Film Transistors

Charge transport in amorphous semiconductors is considerably more complicated than the process in crystalline materials due to abundant localized states. In addition to device-scale characterization, spatially resolved measurements are important to unveiling electronic properties. Here, we report gigahertz conductivity mapping in amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors by microwave impedance microscopy (MIM), which probes conductivity without Schottky barrier’s influence. The difference between the dc and microwave conductivities reflects the efficacy of the injection barrier in an accumulation-mode transistor. The conductivity exhibits significant nanoscale inhomogeneity in the subthreshold regime, presumably due to trapping and release from localized states. The characteristic length scale of local fluctuations, as determined by the autocorrelation analysis, is about 200 nm. Using a random-barrier model, we can simulate the spatial variation of the potential landscape, which underlies the mesoscopic conductivity distribution. Furthermore, our work provides an intuitive way to understand the charge transport mechanism in amorphous semiconductors at the microscopic level.

36 MATERIALS SCIENCE↗

Strong Localization of Surface Plasmon Polaritons with Engineered Disorder

Here in this work, we experimentally demonstrate for the first time strong localization of surface plasmon polaritons (SPPs) at visible regime in metallic nanogratings with short-range correlated disorder. By increasing the degree of disorder, the confinement of SPPs is significantly enhanced, and the effective SPP propagation length dramatically shrinks. Strong localization of SPPs eventually emerges at visible regime, which is verified by the exponentially decayed fields and the vanishing autocorrelation function of the SPPs. Physically, the short-range correlated disorder induces strong interference among multiple scattered SPPs and provides an adequate fluctuation to effective permittivity, which leads to the localization effect. Finally, our study demonstrates a unique opportunity for disorder engineering to manipulate light on nanoscale and may achieve various applications in random nanolasing, solar energy, and strong light-matter interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Structural Dynamics in UV Curable Resins Resolved by In Situ 3D Printing X-ray Photon Correlation Spectroscopy

Additive manufacturing (AM) is a promising technique to rapidly produce polymeric materials into complex 3-dimensional (3D) geometries. While AM is widespread and relevant for a range of applications, implementation in industry has outpaced our fundamental understanding of polymer dynamics and structure development during the printing process. Characterization and quantification of such dynamics is necessary to optimize final material properties and design future materials and processes for 3D printing. Here, we utilize X-ray photon correlation spectroscopy (XPCS) to measure spatial and time-resolved, out-of-equilibrium dynamics during direct ink write (DIW) 3D printing. Specifically, we investigate the progression of structural dynamics in a dual cure (UV/thermal) nanocomposite during and directly after printing. As the filament is printed and cured in situ, the relaxation processes of the cross-linking network are measured through the dynamics of inorganic filler particles. The characteristic relaxation time of the dynamics is calculated through the intensity–intensity autocorrelation function g 2 and directly correlated to the printing process parameters, such as printhead velocity and UV light intensity. The time-resolved evolution of nanoscale dynamics follows a power-law dependence as the filament is cured. Additionally, bulk rheological characterizations reveal the macroscopic solidification of the resin, providing correlation of material properties across a wide range of length and time scales. Overall, the measurement of multiscale, out-of-equilibrium dynamics provides insight into the development of structure in polymer nanocomposite filaments during 3D printing and is used to further understand the influence of such parameters on the AM process.

36 MATERIALS SCIENCE↗

Unraveling the Unconventional Order of a High-Mobility Indacenodithiophene-Benzothiadiazole Copolymer

We report a new class of donor–acceptor (D-A) copolymers found to produce high charge carrier mobilities competitive with amorphous silicon (>1 cm 2 V –1 s –1 ) exhibit the puzzling microstructure of substantial local order, however lacking long-range order and crystallinity previously deemed necessary for achieving high mobility. Here, we demonstrate the application of low-dose transmission electron microscopy to image and quantify the nanoscale and mesoscale organization of an archetypal D-A copolymer across areas comparable to electronic devices (≈9 μm 2 ). The local structure is spatially resolved by mapping the backbone (001) spacing reflection, revealing nanocrystallites of aligned polymer chains throughout nearly the entire film. Analysis of the nanoscale structure of its ordered domains suggests significant short- and medium-range order and preferential grain boundary orientations. Moreover, we provide insights into the rich, interconnected mesoscale organization of this new family of D-A copolymers by analysis of the local orientational spatial autocorrelations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-Level Insights into the NMR Relaxivity of Gadobutrol Using Quantum and Classical Molecular Simulations

MRI is an indispensable diagnostic tool in modern medicine; however, understanding the molecular-level processes governing NMR relaxation of water in the presence of MRI contrast agents remains a challenge, hindering the molecular-guided development of more effective contrast agents. By using quantum-based polarizable force fields, the first-of-its-kind molecular dynamics (MD) simulations of Gadobutrol are reported where the 1 H NMR longitudinal relaxivity r 1 of the aqueous phase is determined without any adjustable parameters. The MD simulations of r 1 dispersion (i.e., frequency dependence) show good agreement with measurements at frequencies of interest in clinical MRI. Importantly, the simulations reveal key insights into the molecular level processes leading to r 1 dispersion by decomposing the NMR dipole–dipole autocorrelation function G(t) into a discrete set of molecular modes, analogous to the eigenmodes of a quantum harmonic oscillator. The molecular modes reveal important aspects of the underlying mechanisms governing r 1 , such as its multiexponential nature and the importance of the second eigenmodal decay. By simply analyzing the MD trajectories on a parameter-free approach, the Gadobutrol simulations show that the outer-shell water contributes ∼50% of the total relaxivity r 1 compared to the inner-shell water, in contrast to simulations of (nonchelated) gadolinium-aqua where the outer shell contributes only ∼15% of r 1 . The deviation between simulations and measurements of r 1 below clinical MRI frequencies is used to determine the low-frequency electron-spin relaxation time for Gadobutrol, in good agreement with independent studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Studies of [Bmim][PF6]/n-Alcohol Interfaces with Many-Body Potentials

In this paper, we present the results from molecular-dynamics simulations of the equilibrium properties of liquid/liquid interfaces of room temperature ionic liquid [bmim][PF6] and simple alcohols (i.e., methanol, 1-butanol, and 1-hexanol) at room temperature. Polarizable potential models are employed to describe the interactions among species. Results from our simulations show stable interfaces between the ionic liquid and n-alcohols, and we found that the interfacial widths decrease from methanol to 1-butanol systems, and then increase for 1-hexanol interfaces. Angular distribution analysis reveals that the interface induces a strong orientational order of [bmim] and n-alcohol molecules near the interface, with [bmim] extending its butyl group into the alcohol phase while the alcohol has the OH group pointing into the ion liquid region, which is consistent with the recent sum-frequency-generation experiments. We found the interface to have a significant influence on the dynamics of ionic liquids and n-alcohols. The orientational autocorrelation functions illustrate that [bmim] rotate more freely near the interface than in the bulk, while the rotation of n-alcohol is hindered at the interface. Additionally, the time scale associated with the diffusion along the interfacial direction is found to be faster for [bmim] but slowed down for n-alcohols approaching the interface. We also calculate the dipole moment of n-alcohols as a function of the distance normal to the interface. We found that, even though methanol and 1-butanol have different dipole moments in bulk phase, they reach a similar value at the interface. This work was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Pacific Northwest National Laboratory is a multiprogram national laboratory operated for the Department of Energy by Battelle. The calculations were carried out using computer resources provided by the Office of Basic Energy Sciences.

Chang, Tsun-Mei↗

Effects of Fault Roughness on Coseismic Slip and Earthquake Locations

We report that fault zone structure is well known to exert strong controls on earthquake properties including coseismic slip distribution, rupture propagation direction, and hypocenter location. It has also been well established that the principal slip surface, which accommodates the majority of earthquake displacement, exhibits roughness at all scales following self-affine fractal distributions. Here we explore the relationship between fault roughness and specific earthquake properties including coseismic slip distribution and hypocenter location based on long-term simulations of earthquake catalogs on fractally rough faults. We begin by using the von Kármán autocorrelation function to procedurally generate single faults with different fractal roughness properties, which we place in a homogeneous elastic solid and apply pure right-lateral shear at a constant back slip rate with the earthquake simulator RSQSim. Running the simulations for 10,000 years each, we generate millions of earthquakes including thousands of events with Mw > 6.0, which rupture the surface. We show that the patterns of surface rupture in these large events follow self-affine fractal distributions with consistent fractal dimension related distinctly to the fractal dimension of the fault. In addition, the hypocenters of these large events occur in very specific predictable locations where the longest wavelength structure produces a stress asperity (i.e., restraining bend). The resulting patterns can explain many features observed on real fault systems, including clustered hypocenter locations, spatially variable coseismic slip distributions, and characteristic slip recurrence behavior. Lastly, these results demonstrate a quantitative link between a directly measurable fault property—roughness—and the properties of future earthquakes.

58 GEOSCIENCES↗

Improved Spatiotemporal Representativeness and Bias Reduction of Satellite-Based Evapotranspiration Retrievals via Use of In Situ Meteorology and Constrained Canopy Surface Resistance

Evapotranspiration (ET) is a key component of the atmospheric and terrestrial water and energy budgets. Satellite-based vegetation index approaches have used remotely-sensed vegetation and reanalysis meteorological properties with surface energy balance models to estimate global ET (MOD16 ET). We reconstructed satellite retrievals using in situ meteorology (Argonne-ET) and evaluated them using a dense network of surface turbulent heat flux measurements. Argonne-ET resolves spatial heterogeneity of ET across the U.S. Southern Great Plains that is not well characterized by MOD16; MOD16 ET exhibits spatial autocorrelation (Moran's I (MI) significantly > 0 in May – Aug.), whereas in situ and Argonne-ET exhibit characteristics of a random spatial process (MI not significantly different from 0). The skill in resolving ET temporal variability is not significantly different between MOD16 and Argonne-ET (correlation coefficient = 0.75 and 0.72, respectively). However, the root mean square errors were significantly lower for Argonne-ET (36 W m -2 ) than MOD16 (43 W m -2 ), and MOD16 exhibits substantial bias in annual ET relative to in situ measurements (-38%). This is attributed to overestimation in the dry canopy surface resistance (rs) parameterization. Using rs constrained to the range of typical measured values, Argonne-ET substantially reduces the bias in the annual ET (+1%). The improved ET estimates are critical for regional water budget analyses. The methodology presented herein also demonstrates the ability to retrieve high temporally resolved (30-min; cf. 8-day MOD16) ET that can be used for development of processed-based diagnostics of model biases, and to elucidate avenues to improve ET model parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Soil Respiration Variability and Correlation Across a Wide Range of Temporal Scales

Abstract The high temporal variability of the soil‐to‐atmosphere CO 2 flux (soil respiration, R S ) has been studied at hourly to multiannual time scales but remains less well understood than R S spatial variability. How R S fluxes vary and are autocorrelated at various time lags has practical implications for sampling and more fundamentally for our understanding of its abiotic and biotic underlying mechanisms. We examined the variability, correlation, and sampling requirements of R S over a wide range of temporal scales in a temperate deciduous forest in eastern Maryland, USA, using both automated (temporally continuous, N = 30,036 over 10 months) and survey (spatially diverse, temporally sparse, N = 1,912 over 17 months) data. Data from a global R S database were also used to examine interannual variability in comparable forests. The coefficient of variability of successive measurements generally varied from the minute (median coefficient of variation 16%) to hourly and daily (11–12%) time scales. Successive R S values measured at a given collar exhibited a strong hour‐to‐hour correlation ( r = 0.931) and a moderate correlation at a 2‐hr lag (0.289); day‐to‐day (i.e., 24 hr lag) hourly observations were uncorrelated. Daily R S means were well correlated at a 1‐day lag ( r = 0.856) but not at any further time lag. In a linear mixed‐effects model predicting R S , soil temperature and moisture exerted consistently strong effects regardless of time scale, and model coefficient of variability was generally high (>80%). These results provide new opportunities to explore the drivers and variability of R S fluxes, quantify sampling requirements, and improve error propagation.

Bond‐Lamberty, Ben↗

Enhancing Streamflow Forecast and Extracting Insights Using Long-Short Term Memory Networks With Data Integration at Continental Scales

Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short-term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data integration (DI) to leverage recent discharge measurements to improve forecasts. DI accepts lagged inputs either directly or through a convolutional neural network unit. DI ubiquitously elevated streamflow forecast performance to unseen levels, reaching a record continental-scale median Nash-Sutcliffe Efficiency coefficient value of 0.86. Integrating moving-average discharge, discharge from the last few days, or even average discharge from the previous calendar month could all improve daily forecasts. Directly using lagged observations as inputs was comparable in performance to using the convolutional neural network unit. Importantly, we obtained valuable insights regarding hydrologic processes impacting LSTM and DI performance. Before applying DI, the base LSTM model worked well in mountainous or snow-dominated regions, but less well in regions with low discharge volumes (due to either low precipitation or high precipitation-energy synchronicity) and large interannual storage variability. DI was most beneficial in regions with high flow autocorrelation: it greatly reduced baseflow bias in groundwater-dominated western basins and also improved peak prediction for basins with dynamical surface water storage, such as the Prairie Potholes or Great Lakes regions. However, even DI cannot elevate performance in high-aridity basins with 1-day flash peaks. Despite this limitation, there is much promise for a deep-learning-based forecast paradigm due to its performance, automation, efficiency, and flexibility.

54 ENVIRONMENTAL SCIENCES↗

Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction

Floods and heavy precipitation have disruptive impacts worldwide, but their historical variability remains only partially understood at the global scale. This article aims at reducing this knowledge gap by jointly analyzing seasonal maxima of streamflow and precipitation at more than 3,000 stations over a 100‐year period. The analysis is based on Hidden Climate Indices (HCIs). Like standard climate indices (e.g., Nino 3.4, NAO), HCIs are used as covariates explaining the temporal variability of data, but unlike them, HCIs are estimated from the data. In this work, a distinction is made between common HCIs, that affect both heavy precipitation and floods, and specific HCIs, that exclusively affect one or the other. Overall, HCIs do not show noticeable autocorrelation, but some are affected by noticeable trends. In particular, strong and wide‐ranging trends are identified in precipitation‐specific HCIs, while trends affecting flood‐specific HCIs are weaker and have more localized effects. A probabilistic model is then derived to link HCIs and large‐scale atmospheric variables (pressure, wind, temperature) and to reconstruct HCIs since 1836 using the 20CRv3 reanalysis. In turn this allows estimating the probability of occurrence of floods and heavy precipitation at the global scale. This 180‐year reconstruction highlights flood hot‐spots and hot‐moments in the distant past, well before the establishment of perennial monitoring networks. Finally, the approach presented in this study is generic and paves the way for an improved characterization of historical variability by making a better use of long but highly irregular station data sets.

54 ENVIRONMENTAL SCIENCES↗

Controlling single rare earth ion emission in an electro-optical nanocavity

Abstract Rare earth emitters enable critical quantum resources including spin qubits, single photon sources, and quantum memories. Yet, probing of single ions remains challenging due to low emission rate of their intra-4 f optical transitions. One feasible approach is through Purcell-enhanced emission in optical cavities. The ability to modulate cavity-ion coupling in real-time will further elevate the capacity of such systems. Here, we demonstrate direct control of single ion emission by embedding erbium dopants in an electro-optically active photonic crystal cavity patterned from thin-film lithium niobate. Purcell factor over 170 enables single ion detection, which is verified by second-order autocorrelation measurement. Dynamic control of emission rate is realized by leveraging electro-optic tuning of resonance frequency. Using this feature, storage, and retrieval of single ion excitation is further demonstrated, without perturbing the emission characteristics. These results promise new opportunities for controllable single-photon sources and efficient spin-photon interfaces.

42 ENGINEERING↗

Dynamics of superconducting qubit relaxation times

Superconducting qubits are a leading candidate for quantum computing but display temporal fluctuations in their energy relaxation times T 1 . This introduces instabilities in multi-qubit device performance. Furthermore, autocorrelation in these time fluctuations introduces challenges for obtaining representative measures of T 1 for process optimization and device screening. These T 1 fluctuations are often attributed to time varying coupling of the qubit to defects, putative two level systems (TLSs). In this work, we develop a technique to probe the spectral and temporal dynamics of T 1 in single junction transmons by repeated T 1 measurements in the frequency vicinity of the bare qubit transition, via the AC-Stark effect. Across 10 qubits, we observe strong correlations between the mean T 1 averaged over approximately nine months and a snapshot of an equally weighted T 1 average over the Stark shifted frequency range. These observations are suggestive of an ergodic-like spectral diffusion of TLSs dominating T 1 , and offer a promising path to more rapid T 1 characterization for device screening and process optimization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generation and measurement of intense few-femtosecond superradiant extreme-ultraviolet free-electron laser pulses

Free-electron lasers producing ultrashort pulses with high peak power promise to extend ultrafast non-linear spectroscopic techniques into the extreme-ultraviolet–X-ray regime. Key aspects are the synchronization between pump and probe, and the control of the pulse properties (duration, intensity and coherence). Externally seeded free-electron lasers produce coherent pulses that can be synchronized with femtosecond accuracy. An important goal is to shorten the pulse duration, but the simple approach of shortening the seed is not sufficient because of the finite-gain bandwidth of the conversion process. An alternative is the amplification of a soliton in a multistage, superradiant cascade: here, we demonstrate the generation of few-femtosecond extreme-ultraviolet pulses, whose duration we measure by autocorrelation. Overall, we achieve pulses four times shorter, and with a higher peak power, than in the standard high-gain harmonic generation mode and we prove that the pulse duration matches the Fourier transform limit of the spectral intensity distribution.

36 MATERIALS SCIENCE↗