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At least 109 records · Page 6

Designing a Convection‐Cloud Chamber for Collision‐Coalescence Using Large‐Eddy Simulation With Bin Microphysics

Abstract Collisional growth of cloud droplets is an essential yet uncertain process for drizzle and precipitation formation. To improve the quantitative understanding of this key component of cloud‐aerosol‐turbulence interactions, observational studies of collision‐coalescence in a controlled laboratory environment are needed. In an existing convection‐cloud chamber (the Pi Chamber), collisional growth is limited by low liquid water content and short droplet residence times. In this work, we use numerical simulations to explore various configurations of a convection‐cloud chamber that may intensify collision‐coalescence. We employ a large‐eddy simulation (LES) model with a size‐resolved (bin) cloud microphysics scheme to explore how cloud properties and the intensity of collision‐coalescence are affected by the chamber size and aspect ratio, surface roughness, side‐wall wetness, side‐wall temperature arrangement, and aerosol injection rate. Simulations without condensation and evaporation within the domain are first performed to explore the turbulence dynamics and wall fluxes. The LES wall fluxes are used to modify the Scalar Flux‐budget Model, which is then applied to demonstrate the need for non‐uniform side‐wall temperature (two side walls as warm as the bottom and the two others as cold as the top) to maintain high supersaturation in a tall chamber. The results of LES with full cloud microphysics reveal that collision‐coalescence is greatly enhanced by employing a taller chamber with saturated side walls, non‐uniform side‐wall temperature, and rough surfaces. For the conditions explored, although lowering the aerosol injection rate broadens the droplet size distribution, favoring collision‐coalescence, the reduced droplet number concentration decreases the frequency of collisions.

54 ENVIRONMENTAL SCIENCES↗

Qualification of 3-D Printed Mortar With Electrical Conductivity Measurements

Additive manufacturing (AM) or 3D printing of concrete allows for construction of arbitrary shape structures without a mold. Since reproducibility of 3D printed concrete is lower than that of conventional fabrication, each 3D printed structure should be monitored for proper curing. Conventional qualification of concrete is based on several tests, including destructive compressive strength measurements. Because a structure is 3-D printed layer-by-layer, the surfaces of AM concrete structures have significant surface roughness. This limits the applicability of conventional nondestructive testing methods. We investigated qualification of 3D printed mortar by monitoring curing with nondestructive electrical conductivity measurements. Bulk resistance of concrete was extracted from electrochemical impedance spectroscopy (EIS measurements made using custom flexible self-adhesive electrodes, which contour to rough surfaces. We show that bulk resistivity of concrete increases linearly with time. This allows for developing a calibration curve for compressive strength lookup from nondestructive electrical conductivity measurements. Conductivity measurements also allow for estimation of formation factor, which is an indicator of mortar permeability.

36 MATERIALS SCIENCE↗

Revealing the Predominant Surface Facets of Rough Cu Electrodes under Electrochemical Conditions

Metal electrodes with rough surfaces are frequently found to convert CO or CO 2 to hydrocarbons and oxygenates with high selectivity and at high reaction rates in comparison with their smooth counterparts. The atomic-level morphology of a rough electrode is likely one key factor responsible for its comparatively high catalytic selectivity and activity. However, few methods are capable of probing the atomic-level structure of rough metal electrodes under electrocatalytic conditions. As a result, the nuances in the atomic-level surface morphology that control the catalytic characteristics of these electrodes have remained largely unexplored. Because the C≡O stretching frequency of atop-bound CO (CO atop ) depends on the coordination of the underlying metal atom, the IR spectrum of this reaction intermediate on the copper electrode could, in principle, provide structural information about the catalytic surface during electrolysis. However, other effects, such as dynamic dipole coupling, easily obscure the dependence of the frequency on the surface morphology. Further, in the limit of low CO atop coverage, where coupling effects are small, the C≡O stretching frequencies of CO atop on Cu(111) and Cu(100) facets are virtually identical. Therefore, on the basis of the C≡O stretching frequency, it is not straightforward to distinguish between these two ubiquitous surface facets, which exhibit vastly different CO reduction activities. Herein, we show that key features of the atomic-level surface morphology of rough copper electrodes can be inferred from the potential dependence of the line shape of the C≡O stretching band of CO atop . Specifically, we compared two types of rough copper thin-film electrodes that are routinely employed in the context of surface-enhanced infrared absorption spectroscopy (SEIRAS). We found that copper films that are electrochemically deposited on Si-supported Au films (CuAu–Si) are poor catalysts for the reduction of CO to ethylene in comparison to copper films (Cu–Si) that are electrolessly deposited onto Si crystals. As quantified by differential electrochemical mass spectrometry (DEMS), the onset potential for ethylene is ~200 ± 65 mV more cathodic for CuAu–Si than that for Cu–Si. To reveal the origin of the disparate catalytic properties of Cu–Si and CuAu–Si, we probed the surfaces of the electrodes with cyclic voltammetry (CV) and SEIRAS. The CV characterization suggests that the (111) surface facet predominates on CuAu–Si, whereas the (100) facet is more common on Cu–Si. SEIRAS reveals that the line shape of the C≡O stretching of CO atop is composed of two bands that are attributable to CO atop on terrace and defect sites. The different surface structures manifest themselves in the form of starkly different potential dependences of the line shape of the C≡O stretching mode of CO atop on the two types of electrodes. With a simple Boltzmann model that considers the different adsorption energies of CO atop on terrace and defect sites, and the resulting CO atop populations on terrace and defect sites, we deduced that the observed electrode-specific potential dependence of the line shape is consistent with the presence of different predominant terrace sites on the two types of films. This strategy for assessing the atomic-level morphology is not restricted to SEIRAS but could also be applied to the C≡O stretching bands recorded with surface-enhanced Raman spectroscopy (SERS), which is suitable for probing a wide range of rough copper electrodes. Therefore, with this work, we establish the potential dependence of the C≡O stretching band of CO atop as a probe of the atomic-level surface structure of rough metal electrodes under electrochemical conditions. When it is coupled with complementary techniques, this methodology provides essential structural information for further improvement in the reaction selectivity of rough metal electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flow in additively manufactured super-rough channels

Metal additive manufacturing has enabled geometrically complex internal cooling channels for turbine and heat exchanger applications, but the process gives rise to large-scale roughness whose size is comparable to the channel height (which is 500 $\mathrm {\mu }$ m). These super-rough channels pose previously unseen challenges for experimental measurements, data interpretation and roughness modelling. First, it is not clear if measurements at a particular streamwise and spanwise location still provide accurate representation of the mean (time- and plane-averaged) flow. Second, we do not know if the logarithmic layer survives. Third, it is unknown how well previously developed rough-wall models work for these large-scale roughnesses. To answer the above practical questions, we conduct direct numerical simulations of flow in additively manufactured super-rough channels. Three rough surfaces are considered, all of which are obtained from computed tomography scans of additively manufactured surfaces. The roughness’ trough to peak sizes are 0.1 $h$ , 0.3 $h$ and 0.8 $h$ , respectively, where $h$ is the intended half-channel height. Each rough surface is placed opposite a smooth wall and the other two rough surfaces, leading to six rough-wall channel configurations. Two Reynolds numbers are considered, namely $Re_\tau =180$ and $Re_\tau =395$ . We show first that measurements at one streamwise and spanwise location are insufficient due to strong mean flow inhomogeneity across the entire channel, second that the logarithmic law of the wall survives despite the mean flow inhomogeneity and third that the established roughness sheltering model remains accurate.

Altland, Samuel↗

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗

SURFACE FINISHING AND ELECTROLESS NICKEL PLATING OF ADDITIVELY MANUFACTURED (AM) METAL COMPONENTS

This study investigates the application of electroless nickel deposition on additively manufactured stainless steel samples. Current additive manufacturing (AM) technologies produce metal components with a rough surface. Rough surfaces generally exhibit fatigue characteristics, increasing the probability of initiating a crack or fracture to the printed part. For this reason, the direct use of as-produced parts in a finished product cannot be actualized, which presents a challenge. Post-processing of the AM parts is therefore required to smoothen the surface. This study analyzes chempolish (CP) and electropolish (EP) surface finishing techniques for post-processing AM stainless steel components CP has a great advantage in creating uniform, smooth surfaces regardless of size or part geometry EP creates an extremely smooth surface, which reduces the surface roughness to the sub-micrometer level. In this study, we also investigate nickel deposition on EP, CP, and as-built AM components using electroless nickel solutions. Electroless nickel plating is a method of alloy treatment designed to increase manufactured component's hardness and surface resistance to the unrelenting environment. The electroless nickel plating process is more straightforward than its counterpart electroplating.. We use low-phosphorus (2-5% P), medium-phosphorus (6-9% P), and high-phosphorus (10-13% P). These Ni deposition experiments were optimized using the L9 Taguchi design of experiments (TDOE), which compromises the prosperous content in the solution, surface finish, plane of the geometry, and bath temperature. The pre-and post-processed surface of the AM parts was characterized by KEYENCE Digital MicroscopeVHX-7000 and Phenom XL Desktop SEM. The experimental results show that electroless nickel deposition produces uniform Ni coating on the additively manufactured components up to 20 μm per hour. Mechanical properties of as-built and Ni coated AM samples were analyzed by applying a standard 10 N scratch test. Nickel coated AM samples were up to two times scratch resistant compared to the as-built samples. This study suggests electroless nickel plating is a robust viable option for surface hardening and finishing AM components for various applications and operating conditions.

Keywords: additive manufacturing, fatigue, chempol↗

Processing aluminum alloy with hybrid wire arc additive manufacturing and ultrasonic nanocrystalline surface modification to improve porosity, surface finish, and hardness

Here, in this paper, a novel hybrid wire arc additive manufacturing (WAAM) and ultrasonic nanocrystal surface modification (UNSM) on porosity manipulation and surface properties of aluminum 5356 alloys was studied. The goal is to improve the quality of the WAAM-built part by eliminating bigger pores and reducing its size, reducing surface roughness, and increasing surface hardness. The as-built WAAM and WAAM-UNSM-treated samples were quantitatively studied for porosity using an X-ray micro-computed tomography (μ-CT). The surface roughness was measured on the surface profile of the same samples before and after UNSM treatment. Followed by the Vickers micro-hardness tests to evaluate the hardness modified by the influence of the UNSM treatment. It was found that the bigger pores in the as-built WAAM samples were eliminated and the medium-sized pores were shrunk to almost half the size after the UNSM treatment. Further, the UNSM treatment showed a significant improvement in both surface roughness and hardness on the WAAM Al5356 samples. This experimental work demonstrates the critical advantages of hybrid WAAM-UNSM in improving the qualities of the WAAM processed parts.

Hardness↗

Urban wash-off of tire wear particles

Tire wear particles (TWPs) are an important class of microplastics due to their toxicity and abundance. Because most TWPs are generated on impervious road surfaces, urban wash-off is the critical first phase of waterborne transport from their zone of production to stormwater drainage. However, little is known about the driving factors behind their mobilization. In this study, we use a rainfall simulator to investigate how surface roughness, rainfall intensity, and surface slope affect wash-off behaviors of TWPs. We also analyze how the size and shape of mobilized TWPs change over the course of simulated storm events. We found that low surface roughness, high rainfall intensity (most significant factor), and low slope result in the most rapid conveyance of TWP load. On average, large particles (>1000 µm) travelled faster than small particles (<125 µm). Particle shape explained a very small amount of variance in TWP wash-off velocity but was found to be more important under higher surface roughness conditions. In addition to wash-off velocity, we found similar conditions controlled the percent mobilization of TWPs. Low surface roughness and high rainfall intensity resulting in higher TWP wash-off rates is consistent with mineral sediment wash-off behavior. Conversely, low surface slope and large particle size leading to faster conveyance is directly opposed to mineral sediment wash-off. Our findings suggest drag-dominated flow and that sufficient runoff depth is the most important parameter governing TWP wash-off. These findings are important first steps to understanding wash-off behaviors of TWPs and informing future modeling efforts and mitigation strategies.

13 HYDRO ENERGY↗

Analytical modeling and simulation of electrical contact resistance for elastic rough electrode surface contact including frictional temperature rise

An improved electrical contact resistance (ECR) model for elastic rough electrode contact is proposed, incorporating the effects of asperity interactions and temperature rise by frictional and joule heating. The analytical simulation results show that the ECR decreases steeply at the beginning of the contact between Al and Cu. However, it becomes stabilized after reaching a specific contact force. It is also found that the longer elapsed sliding contact time, the higher ECR due to the increase in electrical resistivity of electrode materials by the frictional temperature rise at the interface. The effects of surface roughness parameters on ECR are studied through the 3 2 full-factorial design-of-experiment analysis. Based on the two representative roughness parameters, i.e., root-mean-square (rms) roughness and asperity radius, their individual and coupled effects on the saturated ECR are examined. The saturated ECR increases with the rms roughness for a rough machined surface condition, but it is hardly affected by the asperity radius. On the other hand, the saturated ECR increases with both the rms roughness and the asperity radius under a smooth thin film surface condition.

42 ENGINEERING↗

Electron beam surface remelting enhanced corrosion resistance of additively manufactured Ti-6Al-4V as a potential in-situ re-finishing technique

This study explores the effect of surface re-finishing on the corrosion behavior of electron beam manufactured (EBM) Ti-G5 (Ti-6Al-4V), including the novel application of an electron beam surface remelting (EBSR) technique. Specifically, the relationship between material surface roughness and corrosion resistance was examined. Surface roughness was tested in the as-printed (AP), mechanically polished (MP), and EBSR states and compared to wrought (WR) counterparts. Electrochemical measurements were performed in chloride-containing media. It was observed that surface roughness, rather than differences in the underlying microstructure, played a more significant role in the general corrosion resistance in the environment explored here. While both MP and EBSR methods reduced surface roughness and enhanced corrosion resistance, mechanical polishing has many known limitations. The EBSR process explored herein demonstrated positive preliminary results. The surface roughness (R a ) of the EBM-AP material was considerably reduced by 82%. Additionally, the measured corrosion current density in 0.6 M NaCl for the EBSR sample is 0.05 µA cm –2 , five times less than the value obtained for the EBM-AP specimen (0.26 µA cm –2 ).

42 ENGINEERING↗

Performance improvement of proton exchange membrane water electrolysis by surface modification of porous transport layers

Proton exchange membrane water electrolysis (PEMWE) is a promising option for hydrogen production from a variety of energy sources. Cost-effective production of hydrogen with PEMWE requires reduction of costly precious metals as well as optimization of the components and interfaces in the cell. The interface between the platinum-coated titanium porous transport layer (PTL) and catalyst layer (CL) significantly impacts the performance of the electrolyzer cell. Here, we report on two PTL modification methods, mechanical abrasion and chemical etching, which we find improve PEMWE performance by lowering the resistance of the PTL/CL interface. The PTL surface modifications enabled performance improvements up to 77 mV at 4 A cm −2 and reduction of the high frequency resistance, demonstrating that the resistance of the PTL/CL interface is a significant factor in the cell performance. The PTL surface roughness was varied using abrasive materials ranging from 0.1 to 140 μm in grain sizes and chemical etching was found to also increase the surface roughness. The surface roughness was quantified using confocal laser microscopy and the surface oxidation was measured using X-ray photoemission spectroscopy. These results demonstrate that both increasing surface roughness and oxide removal contribute to lowering the PTL/CL interfacial resistance and increasing cell performance.

08 HYDROGEN↗

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗

High Carrier Lifetimes in Epitaxial Germanium-Tin/Al(In)As Heterostructures with Variable Tin Compositions

Group IV-based germanium-tin (Ge1-ySny) compositional materials have recently shown great promise for infrared detection, light emission and ultra-low power transistors. High carrier lifetimes are desirable for enhancing the detection limit and efficiency of photodetectors, low threshold current density in lasers, and low tunneling barrier height by lowering defects and dislocations at the heterointerface of a source and a channel. Here, carrier lifetimes in epitaxial germanium (Ge) and variable tin (Sn) compositional Ge1-ySny materials were experimentally determined on GaAs substrates using the contactless microwave photoconductive decay (u-PCD) technique at an excitation wavelength of 1500 nm. Sharp (2 x 2) reflection high energy electron diffraction patterns and low surface roughness were observed from the surface of the Ge0.97Sn0.03 epilayer. X-ray rocking curves from Ge0.97Sn0.03 and Ge0.94Sn0.06 layers demonstrated the pseudomorphic and lattice-matched growth on AlAs and In0.12Al0.88As buffers, respectively, further substantiated by reciprocal space maps and abrupt heterointerfaces evident from the presence of Pendellosung oscillations. High effective carrier lifetimes of 150 ns to 450 ns were measured for Ge1-ySny epilayers as a function of Sn composition, surface roughness, growth temperature, and layer thickness. The observed increase in the carrier lifetime with an increasing Ge layer thickness and a reducing surface roughness, by incorporating Sn, were explained. The enhancement of the carrier lifetime with an increasing Sn concentration was achieved by controlling the defects with lattice-matched Ge0.94Sn0.06/In0.12Al0.88As heterointerfaces or the pseudomorphic growth of Ge0.94Sn0.06 on GaAs. Therefore, our monolithic integration of variable Sn alloy compositional Ge1-ySny materials with high carrier lifetimes opens avenues to realize electronic and optoelectronic devices.

carrier lifetimes↗

Production of C 2 /C 3 Oxygenates from Planar Copper Nitride-Derived Mesoporous Copper via Electrochemical Reduction of CO 2

Electrochemical reduction of CO 2 provides an opportunity to produce fuels and chemicals in a carbon-neutral manner, assuming that CO 2 can be captured from the atmosphere. To do so requires efficient, selective, and stable catalysts. In this study, we report a highly mesoporous metallic Cu catalyst prepared by electrochemical reduction of thermally nitrided Cu foil. Under aqueous saturated CO 2 reduction conditions, the Cu 3 N-derived Cu electrocatalyst produces virtually no CH 4 , very little CO, and exhibits a faradaic efficiency of 68% in C 2+ products (C 2 H 4 , C 2 H 5 OH, and C 3 H 7 OH) at a current density of ~18.5 mA cm –2 and a cathode potential of -1.0 V versus the reversible hydrogen electrode. Under these conditions, the catalyst produces more oxygenated products than hydrocarbons. We show that surface roughness is a good descriptor of catalytic performance. The roughest surface reached 98% CO utilization efficiency for C 2+ product formation from CO 2 reduction and the ratio of oxygenated to hydrocarbon products correlates with the degree of surface roughness. These effects of surface roughness are attributed to the high population of undercoordinated sites as well as a high pH environment within the mesopores and adjacent to the surface of the catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface smoothing for laser powder-bed Ti-6Al-4V by a transient liquid phase

Surface roughness is the primary driver of fatigue for additively manufactured metals. To address surface roughness, this work introduces a new method to smooth features beyond line-of-sight without material removal. The method applies a coating that triggers local surface remelting by activating a eutectic reaction during heat treatment. The associated liquid phase then wets and isothermally solidifies into a smoother surface. For Ti-6Al-4V fabricated with laser powder bed fusion, samples with and without TLP smoothing (using a Cu coating) were characterized with a suite of techniques, including mechanical testing, electron backscatter diffraction, synchrotron X-ray tomography, and fractography. TLP smoothing reduced surface roughness by 80% and amplified compressive residual stress at the surface by about 50%. With statistically equivalent virtual microstructures, crystal plasticity scrutinized the roles of phases, porosity, and surface roughness. Although the tensile strain-to-failure was reduced to 1% strain, the TLP smoothing process increased high-cycle fatigue strength by about 20% compared to control samples, pointing to future opportunities to optimize the new process through various coating compositions and heat treatment schedules. Overall, this work establishes a new paradigm for treating surfaces of materials for smoothness and compressive residual stress.

Additive manufacturing↗

Revisiting heat treatment and surface activation of GaAs photocathodes: In situ studies using scanning tunneling microscopy and photoelectron spectroscopy

The lifetime of GaAs photocathodes in polarized electron guns is limited due to the delicate activation layer. An atomically clean and smooth GaAs surface is needed to deposit a robust activation layer, such as Cs 2 Te, with longer lifetime compared to traditional (Cs,O) activation. A previous experiment with Cs 2 Te activation on GaAs used heat cleaning temperatures around 400°C to avoid an increase in surface roughness [Bae et al., Appl. Phys. Lett. 112, 154101 (2018)]. Furthermore, high-temperature heat cleaning around 580°C, which results in a relatively contamination-free surface, could be one possible way to improve quantum efficiency. However, one should be cautious about surface roughness degradation during high-temperature heat cleaning. In this paper, we report results of surface roughness measurements on native, heat cleaned, and (Cs,O) activated GaAs photocathodes under vacuum. The results, measured by ultrahigh vacuum scanning tunneling microscopy, show that the surface roughness improves as the heat cleaning temperature is increased, by at least a factor of three for 580°C heat cleaning, compared to the native sample. Activation with (Cs,O) is shown to increase surface roughness by a factor of four compared to a 580°C heat cleaned sample. This confirms that high-temperature heat cleaning can be useful for depositing good quality robust activation layers on GaAs. Additionally, we also report chemical analysis for each step of preparation for p-doped GaAs photocathodes using X-ray photoelectron spectroscopy (XPS), angle-resolved XPS, and ultraviolet photoelectron spectroscopy. Our results indicate that the (Cs,O) activation layer forms a sandwich structure consists of Cs and oxygen. We found no formation of any specific compound such as Cs 2 O or Cs 11 O 3 .

43 PARTICLE ACCELERATORS↗

Computational Analysis of Water Film Thickness During Rain Events for Assessing Hydroplaning Risk Part 2: Rough Road Surfaces

Hydroplaning occurs when a water film forms on a road during a rain event and vehicles are traveling at a speed that does not provide sufficient time for the tires to push the water film out of the tire path. Under these conditions, the tire loses contact with the road and the driver may lose control over the vehicle. The present study is a part of a multiyear research effort aimed at gaining a better understanding of the factors that contribute to hydroplaning risk in order to minimize the occurrence of hydroplaning accidents. Three-dimensional computational fluid dynamics (CFD) analysis was used to investigate the water film thickness on multilane roads, one of the key parameters in evaluating hydroplaning risk. In the first part of the study, water films forming on wide roadways, i.e. multilane highways with 2, 4, and 6 lanes per side, were analyzed, with varying cross slope, longitudinal slope, and rainfall rate. Roadways with and without curbs and drainage were included in the analysis. The analysis in the first part was limited to nearly smooth asphalt or concrete surfaces because the maximum roughness height that can be specified in a CFD model using wall functions to determine shear stress at the road surface boundary is one half the thickness of computational cell layer adjacent to the boundary and the need to resolve the vertical velocity distribution in a thin water film requires cell layers that are a fraction of a millimeter thick. In this part of the study, the analysis was extended to consider the influence of pavement roughness over a range extending up 3.6 mm on the development of water film thickness. Various methods of modeling roughness were investigated and are presented: the roughness height model, a meshed-out geometry of the macrotexture of the pavement, and a porous region model. The computational results were analyzed and compared with experimental measurements performed by Gallaway et al.

42 ENGINEERING↗