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Agile Adaptive Radar Sampling of Fast‐Evolving Atmospheric Phenomena Guided by Satellite Imagery and Surface Cameras
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Plasmon coupling in topological insulator multilayers
Topological insulators (TIs) house two-dimensional Dirac plasmons on their surfaces. In TI thin films, plasmons on the top and bottom surfaces couple electrostatically, giving rise to an acoustic and an optical plasmon mode. By extension, a superlattice comprising TI layers and trivially-insulating layers could house multiple complex plasmon modes which could be used to create a new type of Dirac metamaterial. In this paper, we synthesize TI superlattices, fabricate them into stripe arrays, characterize their optical and plasmonic properties, and model the samples using transfer matrices. Furthermore, we excite plasmon modes that couple to the phonons in the superlattice, resulting in hybrid plasmon phonon polaritons. These modes are modeled using an analytical Fano resonance model and the extracted resonant positions are reproduced by transfer matrix modeling. We also excite an epsilon-near-zero mode in the top dielectric material (Bi 0.5 In 0.5 ) 2 Se 3 . Understanding the behavior of the polariton modes in this complex system will lend insight into the many-body interaction in low-dimensional systems.
Influence of polycarboxylate superplasticizer, citric acid and their combination on the hydration and workability of calcium sulfoaluminate cement
Highlights: • The dispersion efficiency of polycarboxylate superplasticizers drops quickly over time. • Citric acid maintains the dispersion efficiency of PCE over time. • Competitive adsorption between citric acid and PCE occurs. • The combination of citric acid with PCE decreases the initial dispersion efficiency of PCE. PCEs are well known to improve the initial fluidity of CSA. However, their dispersion efficiency drops quickly over time. This issue can be solved by incorporating retarders. In this context, this paper deals with the influence of citric acid, used as a retarder, PCE and their combination on the hydration and workability of CSA. Isothermal calorimetry, XRD and TG analysis were used to describe the hydration process, while workability was characterized with the mini-cone test. Adsorption behavior was investigated using total organic carbon analyzer coupled with ion chromatography. Results show that the introduction of citric acid retained the dispersion efficiency of PCE over time. However, the initial dispersion efficiency of PCE was decreased by citric acid as the latter tend to adsorb first on the surface of cement grains, inhibiting the adsorption of PCE. A dispersion model was proposed to describe the acting mechanism of these admixtures on CSA.
Grand-scale Atmospheric Imaging Apparatus (GAIA) and Wind LiDAR Multi-scale Measurements in the Atmospheric Surface Layer
Understanding the organization and dynamics of turbulence structures in the atmospheric surface layer (ASL) is important for fundamental and applied research in different fields, including weather prediction, snow settling, particle and pollutant transport, and wind energy. The main challenges associated with probing and modeling turbulence in the ASL are: i) the broad range of turbulent scales associated with the different eddies present in high Reynolds-number boundary layers ranging from the viscous scale ($\mathcal{O}$(mm)) up to large energy-containing structures ($\mathcal{O}$(km)); ii) the non-stationarity of the wind conditions and the variability associated with the daily cycle of the atmospheric stability; iii) the interactions among eddies of different sizes populating different layers of the ASL, which contribute to momentum, energy, and scalar turbulent fluxes. Creative and innovative measurement techniques are required to probe near-surface turbulence by generating spatio-temporally-resolved data in the proximity of the ground and, at the same time, covering the entire ASL height with large enough streamwise extent to characterize the dynamics of larger eddies evolving aloft. To this aim, the U.S. National Science Foundation sponsored the development of the Grand-scale Atmospheric Imaging Apparatus (GAIA) enabling super-large snow particle image velocimetry (SLPIV) in the near-surface region of the ASL. This inaugural version of GAIA provides a comprehensive measuring system by coupling SLPIV and two scanning Doppler LiDARs to probe the ASL at an unprecedented resolution. A field campaign performed in 2021–2022 and its preliminary results are presented herein elucidating new research opportunities enabled by the GAIA measuring system.
Interplay of surface energy and rheology in biopolymer soil enhancement
Biopolymers such as xanthan gum (XG) and locust bean gum (LBG) hold great potential as eco-friendly alternative soil binders. In this work, we investigated the impact of XG/LBG mixtures on the unconfined compressive strength (UCS) of sand. The high strength of dry biopolymer/sand arises from the cohesion between solid polymer films and sand particles which supported by work of adhesion calculation and soil mechanics measurement. LBG exhibits much lower sand reinforcement efficacy because polymers unevenly distributed within sand matrix. The formation of a core-shell structure in LBG/sand is an interplay of surface free energy and viscoelastic properties of polymer solutions. This structure is altered when LBG mixed with XG at varying ratios as those physical properties changed due to the complexity of polymer chains association. By probing these factors, we aim to elucidate the role of surface energies and polymer physics in governing the strength of the sand/polymer network, thereby contributing to a more comprehensive understanding polymer-sand interface. The low strength of gels (G’ ∼10Pa) cannot solely account for the increased UCS of wet sand over 10 kPa. Instead, the high strength of biopolymer/sand is more likely derived from the granular particles with biopolymers as solid glue.
Formation of Nano- and Micro-Scale Surface Features Induced by Long-Range Femtosecond Filament Laser Ablation
In this work, we study the characteristics of femtosecond-filament-laser–matter interactions and laser-induced periodic surface structures (LIPSS) at a beam-propagation distance up to 55 m. The quantification of the periodicity of filament-induced self-organized surface structures was accomplished by SEM and AFM measurements combined with the use of discrete two-dimensional fast Fourier transform (2D-FFT) analysis, at different filament propagation distances. The results show that the size of the nano-scale surface features increased with ongoing laser filament processing and, further, periodic ripples started to form in the ablation-spot center after irradiation with five spatially overlapping pulses. The effective number of irradiating filament pulses per spot area affected the developing surface texture, with the period of the low spatial frequency LIPSS reducing notably at a high pulse number. The high regularity of the filament-induced ripples was verified by the demonstration of the angle-of-incidence-dependent diffraction of sunlight. This work underlines the potential of long-range femtosecond filamentation for energy delivery at remote distances, with suppressed diffraction and long depth focus, which can be used in biomimetic laser surface engineering and remote-sensing applications.
Registration and fusion of large-scale melt pool temperature and morphology monitoring data demonstrated for surface topography prediction in LPBF
In-situ monitoring technologies for laser powder bed fusion (LPBF) additive manufacturing often face one key challenge, extracting the ultrafast melt pool (MP) signatures for understanding the localized part properties. Further, the spatial information of each monitored MP signature is essential for correlating the MP – part property. This spatial information is often unavailable especially from commercial LPBF printers. Many MP monitoring methods have been reported and utilized. However, very few of these have the MP’s spatial information. To overcome this challenge, in this work we report a method for spatially registering the key MP signatures (MP intensity, temperature, and area) to the monitored print parts. The MP signatures are obtained from our coaxial high-speed single-camera based two-wavelength imaging pyrometry (STWIP) system and the MP spatial information is obtained from an off-axis camera system. A machine learning aided image analysis method is employed to retrieve the spatial distribution of MPs within the corresponding part’s coordinates system. Then, the MP signature maps (MPSMs) are reconstructed by mapping the STWIP measured MP signatures to the registered MP coordinates. Further, a long short-term memory (LSTM) neural network is developed for estimating the layer surface topography from the registered MPSMs. The obtained results indicate that the layer surface topography can be more accurately estimated by using MP temperature signature rather than MP intensity and/or area signatures as in common practice. Finally, our developed methods for MP monitoring, registration, and MP-surface topography prediction offer advanced capabilities for the online detection of process anomalies and part defects.
Nuclear reactor radiation and temperature effects on piezoelectric surface acoustic wave devices
Surface acoustic wave (SAW) resonators were characterized in-situ in a nuclear reactor environment at high temperature. Devices based on lithium niobate (LiNbO 3 ), aluminum nitride (sc-AlN), and thin-film aluminum nitride on sapphire substrate (AlN/sapphire) were tested up to 400 °C temperature and 1.9 × 10 12 n/cm 2 s neutron flux. Shifts in device resonant frequency were detected in response to temperature and neutron flux. Devices undergo a frequency change when exposed to neutron flux. At 300 °C, AlN/sapphire produced the strongest neutron flux response about 1.02 ppm at 1.27 × 10 12 n/cm 2 s neutron flux (5.7 × 10 4 rad-Si/hr neutron dose rate), compared to 0.30 ppm for LiNbO 3 and 0.17 ppm for sc-AlN. While the transient kinetics in response to step change in neutron flux support the defect-accumulation mechanism, the concurrent measurement of device temperature using resistive temperature sensor suggests additional heating caused by absorption of gamma rays can also play a role. These results make SAW devices attractive candidates for sensor applications in extreme environments.
Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces
Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.
Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces
Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.
Spin-dependent charge transmission through chiral 2T3N self-assembled monolayer on Au
In this study, a gold surface is functionalized by chemisorption of the enantiopure N,N'-bis-[2,2';5',2"]tert-thiophene-5-yl methylcyclohexane-1,2-diamine (2T3N), a chiral oligothiophene derivative, via overnight incubation in a 2T3N ethanol solution. The Au|2T3N interface is characterized by x-ray photoelectron circular dichroism and comparing x-ray photoemission spectroscopy and electro-desorption results. Charge transmission at the Au|2T3N| solution interface is characterized by recording the cyclic voltammetry of the Fe(III)/Fe(II) reversible redox couple, finding a charge transfer rate constant, k°, variation from 1 × 10 -1 to 3.3 × 10 -2 cm s -1 , when comparing the bare Au and the Au|2T3N interfaces, respectively. The “anomalous” high value of k° found for the chiral Au|2T3N interface can be rationalized on the basis of the chiral-induced spin selectivity effect, as further proved by magnetic–conductive atomic force microscopy measurements at room temperature. A spin polarization of about 30% is found.
Pit rim decomposition into multiple quantum dots on surfaces of epitaxial thin films grown on pit-patterned substrates
Here, we report results of dynamical simulations according to an experimentally validated surface morphological evolution model on the formation of regular arrays of quantum dot molecules (QDMs) consisting of 1D arrays of smaller interacting quantum dots (QDs). These QD arrays form along the sides of each pit rim on the surface of a coherently strained thin film epitaxially deposited on a semiconductor substrate, the surface of which consists of a periodic pattern of inverted prismatic pits with rectangular pit openings. We find that this complex QDM pattern results from the decomposition of the pit rim from a “quantum fortress” with four elongated QDs into four 1D arrays of multiple smaller QDs arranged along each side of the pit rim. Systematic parametric analysis indicates that varying the pit opening dimensions and the pit wall inclination directly impacts the number of QDs in the resulting QDM pattern, while varying the pit depth only affects the dimensions of the QDs in the nanostructure pattern. Therefore, the number, arrangement, and sizes of QDs in the resulting pattern of QDMs on the film surface can be engineered precisely by proper tuning of the pit design parameters. Our simulation results are supported by predictions of morphological stability analysis, which explains the pit rim decomposition into multiple QDs as the outcome of a tip-splitting instability and provides a fundamental characterization of the post-instability nanostructure pattern. Our theoretical findings can play a vital role in designing optimal semiconductor surface patterns toward enabling future nanofabrication technologies.
High-throughput surface characterization to identify porosity defects in additively manufactured 316L stainless steel
In the present study, a high throughput (HT) methodology is applied to rapidly assess the surface characteristics of 83 additively manufactured 316L stainless steel. The variation in surface roughness (S a ) showed a good correlation with a dimensionless number (π) and provided direct linkages to the internal porosity defects. Lack-of-fusion regime relates to high surface roughness (S a > 5 µm), low dimensionless number (π < 61), and the presence of cavities in between the melt pool tracks. Balling regime correlates to high surface roughness (S a > 5 µm), intermediate dimensionless number (61 < π < 146), and non-uniform melt pool track width. Keyhole regime shows low surface roughness (S a < 5 µm), high dimensionless number (π > 146), and a curved melt pool track. This approach accelerates the process parameter discovery and minimizes the porosity defects for the LPBF process. The impact of the defects on the as-processed tensile mechanical properties demonstrates that samples with porosity exhibit up to 10% less tensile strength and 30% less ductility than optimal samples.
Evaluation of temperature changes in a cell culture plate well with absorbing walls containing a 3D model of tumour spheroid under irradiation in the optical range
The temperature conditions for photodynamic therapy of the culture of tumour cells organised in 3D spheroids are studied. The spheroids are placed in the cell culture medium in the well of a special cell culture plate with absorbing walls. A mathematical model is presented that describes the temperature distribution in a well with a cell culture plate heated by optical radiation. It is shown that the temperature in the well volume is not uniformly distributed, and the temperature on the well surface can differ significantly from the temperature in its volume. (laser medicine)
Gridded Sub-daily Climate Forcings for North America Based on Daymet and GSWP3 (Daymet-GSWP3)
To support high spatial and temporal resolution land surface modeling, this dataset provides 3-hourly time step historic weather forcing at 1-km spatial resolution for the entire North America. The latest Daymet V4 data provides gridded historic daily weather observations at 1-km spatial resolution from 1980 to 2014. Using sub-daily temporal information from the Global Soil Wetness Project Phase 3 (GSWP3), Daymet was further temporally downscaled to 3-hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each sub-daily time step from GSWP3 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2014 Daymet-GSWP3 dataset. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.
Gridded Sub-daily Climate Forcings for North America Based on Daymet and GSWP3 (Daymet-GSWP3)
To support high spatial and temporal resolution land surface modeling, this dataset provides 3-hourly time step historic weather forcing at 1-km spatial resolution for the entire North America. The latest Daymet V4 data provides gridded historic daily weather observations at 1-km spatial resolution from 1980 to 2014. Using sub-daily temporal information from the Global Soil Wetness Project Phase 3 (GSWP3), Daymet was further temporally downscaled to 3-hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each sub-daily time step from GSWP3 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2014 Daymet-GSWP3 dataset. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.