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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24

DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure

Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. Here we present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and distributes the leaf litter from the trees in an elliptical shape based on tree species characteristics, wind data, and location-specific features. DUET then calculates grass growth between trees and around the litter patterns and sets moisture levels based on relative humidity. In this study, we use DUET to simulate spatial distributions of leaf litter and illustrate model sensitivity to several parameters, providing inputs for testing fuel spatial heterogeneity impacts on fire behavior using process-based models.

54 ENVIRONMENTAL SCIENCES↗

Surface Heater Fabrication Using Micro-Lithography for Transpiration Cooling Heat Transfer Coefficient Measurements

Abstract Transpiration cooling is able to provide more uniform coolant coverage than film cooling to effectively protect the component surface from contacting the hot gas. Due to numerous coolant ejection outlets within a small area at the target surface, the experimental thermo-fluid investigation on transpiration cooling becomes a significant challenge. Two classic methods to investigate film cooling, the steady-state foil heater method and the transient thermography technique, fail for transpiration cooling because the foil heater would block numerous coolant outlets, and the semi-infinite solid conduction model no longer holds for porous plates. In this study, a micro-lithography method to fabricate a silver coil pattern on top of the additively manufactured polymer porous media as the surface heater was proposed. The circuit was deliberately designed to cover the solid surface in a combination of series connection, and parallel connection to ensure the power in each unit cell area at the target surface was identical. With uniform heat flux generation, the steady-state tests were conducted to obtain distributions of a pair of parameters, adiabatic cooling effectiveness, and heat transfer coefficient (HTC). The results showed that the adiabatic cooling effectiveness could reach 0.65 with a blowing ratio lower than 0.5. Meanwhile, the heat transfer coefficient ratio (hf/h0) of transpiration cooling was close to 1 with a small blowing ratio at 0.125. A higher HTC ratio was observed for smaller pitch-to-diameter cases due to more turbulence intensity generated at the target surface.

Engineering↗

Assessing Decadal Predictability in an Earth-System Model Using Explainable Neural Networks

We show that explainable neural networks can identify regions of oceanic variability that contribute predictability on decadal timescales in a fully coupled Earth-system model. The neural networks learn to use sea-surface temperature anomalies to predict future continental surface temperature anomalies. We then use a neural-network explainability method called layerwise relevance propagation to infer which oceanic patterns lead to accurate predictions made by the neural networks. In particular, regions within the North Atlantic Ocean and North Pacific Ocean lend the most predictability for surface temperature across continental North America. We apply the proposed methodology to decadal variability, although the concept is generalizable to other timescales of predictability. Furthermore, while our approach focuses on predictable patterns of internal variability within climate models, it should be generalizable to observational data as well. Our study contributes to the growing evidence that explainable neural networks are important tools for advancing geoscientific knowledge.

58 GEOSCIENCES↗

Genotype–environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence

Abstract Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide‐ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype–environment associations in the hermit thrush ( Catharus guttatus ), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype–environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature‐associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature‐related barriers to gene flow and/or temperature‐driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype–environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population‐level sensitivity to climate change and other stressors.

59 BASIC BIOLOGICAL SCIENCES↗

Solution-Deposited and Patternable Conductive Polymer Thin-Film Electrodes for Microbial Bioelectronics

Microbial bioelectronic devices integrate naturally occurring or synthetically engineered electroactive microbes with microelectronics. These devices have a broad range of potential applications, but engineering the biotic–abiotic interface for biocompatibility, adhesion, electron transfer, and maximum surface area remains a challenge. Prior approaches to interface modification lack simple processability, the ability to pattern the materials, and/or a significant enhancement in currents. We report a novel conductive polymer coating that significantly enhances current densities relative to unmodified electrodes in microbial bioelectronics is reported. The coating is based on a blend of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) crosslinked with poly(2-hydroxyethylacrylate) (PHEA) along with a thin polydopamine (PDA) layer for adhesion to an underlying indium tin oxide (ITO) electrode. When used as an interface layer with the current-producing bacterium Shewanella oneidensis MR-1, this material produces a 178-fold increase in the current density compared to unmodified electrodes, a current gain that is higher than previously reported thin-film 2D coatings and 3D conductive polymer coatings. The chemistry, morphology, and electronic properties of the coatings are characterized and the implementation of these coated electrodes for use in microbial fuel cells, multiplexed bioelectronic devices, and organic electrochemical transistor based microbial sensors are demonstrated. It is envisioned that this simple coating will advance the development of microbial bioelectronic devices.

patterned bioelectronics↗

Modeling of ExB effects on tungsten re-deposition and transport in the DIII-D divertor

Mixed-material DIVIMP-WallDYN modelling, now incorporating ExB drifts, is presented that simultaneously reproduces tungsten (W) erosion and deposition patterns observed during the DIII-D Metal Rings Campaign, in which a toroidally symmetric set of W-coated tiles were installed in the carbon (C) DIII-D divertor. Since most reactor plasma facing component (PFC) designs call for mixed-material environments, including ITER’s W/Be enviroment, the divertor targets will quickly evolve into reconstitued surfaces of multiple elements. This work identifies controlling physics that affects material migration patterns in the divertor, which impact PFC lifetimes and impurity leakage from the divertor to the core. These simulations indicate that radial and poloidal ExB transport dominates over parallel force balance for high-Z impurities such as W in the divertor region of DIII-D. It is demonstrated that ExB drifts are required to reproduce the experimental observation of non-local W and C co-accumulation in a band ~7-9 cm outboard of the outer-strike-point (OSP) W source, for attached Lmode conditions in the unfavorable ion grad-B drift direction. In addition, W gross erosion is localized to the region outboard of the OSP, as the formation of C co-deposits suppresses W erosion at the strike point. Time-dependent simulations with scaled ExB impurity drifts (60% of the OEDGE-calculated drift velocity) and W re-erosion quantitatively reproduce these features, including depth-resolved W/C ratios, within a factor of 2 over ~115 seconds of accumulated plasma exposure. The location of co-deposition regions is shown to be well represented by an analytic leakage model, driven largely by poloidal ExB drifts. Qualitative agreement is also found between campaign-integrated W deposition measurements and simulations for the favorable ion grad-B drift direction, the standard mode of operation for most tokamaks. Furthermore, these results imply that a longterm inward radial migration of material from the outer divertor through the private flux region may occur in future devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Atomic Layer Deposition of Pt on the Surface Deactivated by Fluorocarbon Implantation: Investigation of the Growth Mechanism

Selective atomic layer deposition (ALD) using surface-controlled reactivity is attracting a great deal of attention as a simple bottom-up patterning process that can provide both continued dimensional scaling and accurate pattern placement for next-generation nanoelectronics. Previously, we reported topographically selective deposition through Pt ALD using a MeCpPtMe 3 precursor and an O 2 counter reactant on fluorocarbon (CF x )-modified surfaces; however, gradual loss of selectivity in the CF x -modified regions was observed during the Pt ALD process. This work develops a fundamental understanding of the microscopic growth mechanisms of Pt ALD on the CF x -modified surface using a combination of experimental analyses and theoretical methods. The Pt growth characteristics on the CF x surface are investigated within a temperature window from 225 to 350 °C, and the results show a sharp sensitivity to growth temperature, with significant Pt growth occurring at temperatures above 300 °C. Through density functional theory (DFT) calculations, the reaction energies for adsorption of oxygen and the MeCpPtMe 3 precursor as well as formation of reaction products of CF x degradation are determined. Based on experimental results in conjunction with the DFT calculations, we show that while lower temperature Pt ALD (<300 °C) on CF x -modified surfaces can be significantly retarded because of a lack of MeCpPtMe 3 chemisorption, the surface reaction pathways for Pt ALD on CF x -modified surfaces at temperatures above 300 °C can proceed through oxygen adsorption and CF 4 desorption followed by Pt nucleation in CF x -degraded regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Air quality impact of the Northern California Camp Fire of November 2018

The Northern California Camp Fire that took place in November 2018 was one of the most damaging environmental events in California history. Here, we analyze ground-based station observations of airborne particulate matter that has a diameter <2.5 µm (PM 2.5 ) across Northern California and conduct numerical simulations of the Camp Fire using the Weather Research and Forecasting model online coupled with chemistry (WRF-Chem). Simulations are evaluated against ground-based observations of PM 2.5 , black carbon, and meteorology, as well as satellite measurements, such as Tropospheric Monitoring Instrument (TROPOMI) aerosol layer height and aerosol index. The Camp Fire led to an increase in Bay Area PM 2.5 to over 50 µg m –3 for nearly 2 weeks, with localized peaks exceeding 300 µg m –3 . Using the Visible Infrared Imaging Radiometer Suite (VIIRS) high-resolution fire detection products, the simulations reproduce the magnitude and evolution of surface PM 2.5 concentrations, especially downwind of the wildfire. The overall spatial patterns of simulated aerosol plumes and their heights are comparable with the latest satellite products from TROPOMI. WRF-Chem sensitivity simulations are carried out to analyze uncertainties that arise from fire emissions, meteorological conditions, feedback of aerosol radiative effects on meteorology, and various physical parameterizations, including the planetary boundary layer model and the plume rise model. Downwind PM 2.5 concentrations are sensitive to both flaming and smoldering emissions over the fire, so the uncertainty in the satellite-derived fire emission products can directly affect the air pollution simulations downwind. Our analysis also shows the importance of land surface and boundary layer parameterization in the fire simulation, which can result in large variations in magnitude and trend of surface PM 2.5 . Inclusion of aerosol radiative feedback moderately improves PM 2.5 simulations, especially over the most polluted days. Results of this study can assist in the development of data assimilation systems as well as air quality forecasting of health exposures and economic impact studies.

54 ENVIRONMENTAL SCIENCES↗

The Relative Importance of Forced and Unforced Temperature Patterns in Driving the Time Variation of Low-Cloud Feedback

Abstract Atmospheric models forced with observed sea surface temperatures (SSTs) suggest a trend toward a more-stabilizing cloud feedback in recent decades, partly due to the surface cooling trend in the eastern Pacific (EP) and the warming trend in the western Pacific (WP). Here, we show model evidence that the low-cloud feedback has contributions from both forced and unforced feedback components and that its time variation arises in large part through changes in the relative importance of the two over time, rather than through variations in forced or unforced feedbacks themselves. Initial-condition large ensembles (LEs) suggest that the SST patterns are dominated by unforced variations for 30-yr windows ending prior to the 1980s. In general, unforced SSTs are representative of an ENSO-like pattern, which corresponds to weak low-level stability in the tropics and less-stabilizing low-cloud feedback. Since the 1980s, the forced signals have become stronger, outweighing the unforced signals for the 30-yr windows ending after the 2010s. Forced SSTs are characterized by relatively uniform warming with an enhancement in the WP, corresponding to a more-stabilizing low-cloud feedback in most cases. The time-evolving SST pattern due to this increasing importance of forced signals is the dominant contributor to the recent stabilizing shift of low-cloud feedback in the LEs. Using single-forcing LEs, we further find that if only greenhouse gases evolve with time, the transition to the domination of forced signals occurs 10–20 years earlier compared to the LEs with full forcings, which can be understood through the compensating effect between aerosols and greenhouse gases.

58 GEOSCIENCES↗

Improvements in Reflected Target Non-intrusive Assessment (ReTNA)

Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. In 2022, NREL presented a new indoor optical measurement system to measure fully assembled heliostats during development and on the assembly line for quality assurance purposes, which has undergone significant development in the last year, including the installation of a new, larger laboratory setup. This system, called ReTNA (Reflected Target Non-intrusive Assessment), uses a printed pattern as a deflectometry target. Using printed pattern features as deflectometry targets instead of fringes allows the software to measure the surface slope in two dimensions, eliminating the need to for changing, projected targets. In the last year, NREL's ReTNA tool has been adapted to use a tall, thin target, that only spans one dimension of the mirror, and a camera moving on an automatic track system. We will present these new developments, including the new setup, target patterns, software methodology for fast, automatic optical analysis, and important lessons learned throughout the process. ReTNA results will be compared to established tools, to establish the uncertainty of this new method. ReTNA leverages recent improvements in computer vision and photogrammetry to remove as much careful calibration from the setup process as possible, making the tool low cost, simple, and portable. While it will not achieve the resolution of a fringe deflectometry system, its advantages make it well suited for CSP evaluation, and allow it to fill a different industry need.

concentrating solar power↗

Genesis and Propagation of Fractal Structures During Photoelectrochemical Etching of n-Silicon

The genesis, propagation, and dimensions of fractal-etch patterns that form anodically on front- or back-illuminated n-Si(100) photoelectrodes in contact with 11.9 M NH 4 F (aqueous) have been investigated during either a linear potential sweep or a constant potential hold ( E = +6.0 V versus Ag/AgCl). Optical images collected in situ during electrochemical experiments reflected the location and underlying mechanism of initiation and propagation of the structures on the surface. X-ray photoelectron spectroscopic (XPS) data collected for samples emersed from the electrolyte at varied times provided detailed information about the chemistry of the surface during fractal etching. The fractal structure was strongly influenced by the orientation of the crystalline Si sample. Furthermore, the etch patterns were initially generated at points along the circumference of bubbles that formed upon immersion of n-Si(100) samples in the electrolyte, most likely due to the electrochemical and electronic isolation of areas beneath bubbles. XPS data showed the presence of a tensile-stressed silicon surface throughout the etching process as well as the presence of SiO x F y on the surface. The two-dimensional fractal dimension, D f,2D , of the patterns increased with etching time to a maximum observed value of D f,2D = 1.82. Promotion of fractal etching near etch masks that electrochemically and electronically isolated areas of the photoelectrode surface enabled the selective placement of highly branched structures at desired locations on an electrode surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved Rate for the Oxygen Reduction Reaction in a Sulfuric Acid Electrolyte using a Pt(111) Surface Modified with Melamine

The feasible commercialization of alkaline, phosphoric acid and polymer electrolyte membrane fuel cells depends on the development of oxygen reduction reaction (ORR) electrocatalysts with improved activity, stability, and selectivity. The rational design of surfaces to ensure these improved ORR catalytic requirements relies on the so-called "descriptors" (e.g., the role of covalent and noncovalent interactions on platinum surface active sites for ORR). Here, we demonstrate that through the molecular adsorption of melamine onto the Pt(111) surface [Pt(111)-M ad ], the activity can be improved by a factor of 20 compared to bare Pt(111) for the ORR in a strongly adsorbing sulfuric acid solution. Additionally, the M ad moieties act as "surface-blocking bodies," selectively hindering the adsorption of (bi)sulfate anions (well-known poisoning spectator of the Pt(111) active sites) while the ORR is unhindered. This modified surface is further demonstrated to exhibit improved chemical stability relative to Pt(111) patterned with cyanide species (CN ad ), previously shown by our group to have a similar ORR activity increase compared to bare Pt(111) in a sulfuric acid electrolyte, with Pt(111)-M ad retaining a greater than ninefold higher ORR activity relative to bare Pt(111) after extensive potential cycling as compared to a greater than threefold higher activity retained on a CN ad -covered Pt(111) surface. We suggest that the higher stability of the Pt(111)-M ad interface stems from melamine's ability to form intermolecular hydrogen bonds, which effectively turns the melamine molecules into larger macromolecular entities with multiple anchoring sites and thus more difficult to remove.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Moisture availability mediates the relationship between terrestrial gross primary production and solar-induced chlorophyll fluorescence: Insights from global-scale variations

Effective use of solar-induced chlorophyll fluorescence (SIF) to estimate and monitor gross primary production (GPP) in terrestrial ecosystems requires a comprehensive understanding and quantification of the relationship between SIF and GPP. To date, this understanding is incomplete and somewhat controversial in the literature. Here we derived the GPP/SIF ratio from multiple data sources as a diagnostic metric to explore its global-scale patterns of spatial variation and potential climatic dependence. We found that the growing season GPP/SIF ratio varied substantially across global land surfaces, with the highest ratios consistently found in boreal regions. Spatial variation in GPP/SIF was strongly modulated by climate variables. The most striking pattern was a consistent decrease in GPP/SIF from cold-and-wet climates to hot-and-dry climates. We propose that the reduction in GPP/SIF with decreasing moisture availability may be related to stomatal responses to aridity. Furthermore, we show that GPP/SIF can be empirically modeled from climate variables using a machine learning (random forest) framework, which can improve the modeling of ecosystem production and quantify its uncertainty in global terrestrial biosphere models. Finally, our results point to the need for targeted field and experimental studies to better understand the patterns observed and to improve the modeling of the relationship between SIF and GPP over broad scales.

59 BASIC BIOLOGICAL SCIENCES↗

Large-Scale Plasmonic Hybrid Framework with Built-In Nanohole Array as Multifunctional Optical Sensing Platforms

Light coupling with patterned subwavelength hole arrays induces enhanced transmission supported by the strong surface plasmon mode. In this work, a nanostructured plasmonic framework with vertically built-in nanohole arrays at deep-subwavelength scale (6 nm) is demonstrated using a two-step fabrication method. The nanohole arrays are formed first by the growth of a high-quality two-phase (i.e., Au–TiN) vertically aligned nanocomposite template, followed by selective wet-etching of the metal (Au). Such a plasmonic nanohole film owns high epitaxial quality with large surface coverage and the structure can be tailored as either fully etched or half-way etched nanoholes via careful control of the etching process. The chemically inert and plasmonic TiN plays a role in maintaining sharp hole boundary and preventing lattice distortion. Optical properties such as enhanced transmittance and anisotropic dielectric function in the visible regime are demonstrated. Numerical simulation suggests an extended surface plasmon mode and strong field enhancement at the hole edges. Furthermore, two demonstrations, including the enhanced and modulated photoluminescence by surface coupling with 2D perovskite nanoplates and the refractive index sensing by infiltrating immersion liquids, suggest the great potential of such plasmonic nanohole array for reusable surface plasmon-enhanced sensing applications.

42 ENGINEERING↗

Complex Dependence of Calcite Crack Kinetics on Salinity: The Role of DLVO and Hydration Forces

Abstract Subcritical crack growth (SCG) plays an important role in many geological processes such as delayed earth rupture and rock weathering. The complex dependency of SCG on the in‐crack fluid chemistry, however, is still poorly understood. In this study, we utilize the newly developed surface force‐based fracture theory (SFFT) to elucidate the relative contributions of surface forces and solute transport to the crack growth kinetics of calcite in NaCl solutions. Expanding on Barenblatt's cohesive crack model, SFFT introduces an effective stress intensity at the crack tip that encompasses all the relevant intermolecular forces across the crack in addition to the external far‐field stresses. The nonlinear system of equations portraying the crack opening profile, the solute distribution in a propagating crack, and the crack growth velocity are numerically solved via an implicit scheme. After carefully calibrating the model for calcite‐water systems, the SFFT is used to predict the SCG response of calcite at different NaCl concentrations, based on various hypotheses. These predictions are then compared to existing SCG data from the literature. We demonstrate that the experimentally observed variation of SCG rate with NaCl concentration cannot be explained solely by DLVO forces (electrostatic and Van der Waals interactions). This can be remediated by introducing an exponentially decaying hydration force with a nonlinear, nonmonotonic dependence on NaCl concentration. Furthermore, we demonstrate that accounting for both diffusive and advective transport of ions is important in explaining the absence of a stage‐II SCG response for calcite in electrolyte solutions. Plain Language Summary Subcritical crack growth (SCG) refers to the slow propagation of cracks in materials under a stress below the threshold for catastrophic failure. SCG is a key process in many geological events, for example, delayed earth ruptures and rock weathering. New initiatives such as underground CO 2 and H 2 storage in carbonate reservoirs further call for better understanding of SCG in carbonate minerals subjected to varying fluid chemistry. This study examines the SCG of calcite, a key mineral found in carbonate rocks, intergranular cement in sandstones, and filling material in mineral veins and faults, determining their deformation and strength. A mathematical model is developed to describe how the crack opens and propagates, how solutes (like salts) distribute within the crack, and how the crack surfaces interact with each other. We used the model to predict calcite SCG in water at different salt concentrations and compared it with experimental data. Our results revealed that the hydration force is the dominating factor in determining the complex, non‐linear dependency of SCG on salinity. We also found that both the movement of ions by diffusion and by bulk water flow are crucial for explaining the SCG rates, especially when the cracks grow quickly. Key Points Surface Force‐Based Fracture Theory predicts the complex subcritical crack growth patterns of calcite crystals immersed in NaCl solutions Results highlight the dominant role of hydration forces in altering the fracture behavior of calcite compared to VdW and electric double‐layer forces Advective solute transport explains the absence of stages‐II and ‐III subcritical crack growth responses in solid‐liquid systems

DLVO↗

A unified ensemble soil moisture dataset across the continental United States

Abstract A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies in temporal scales across datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions and making recommendations for drought response planning.

54 ENVIRONMENTAL SCIENCES↗

Self Assembled Monolayers for Passivated Contacts

Passivated contacts mitigate defects typically encountered due metallization of solar cells. We deposit amorphous silicon (a-Si:H) on an oxidized silicon wafer via PECVD and anneal at high temperature to crystallize into polysilicon passivated contact. One drawback is the absorption of the polysilicon between grid fingers, so removal of this material is desirable to maximize Jsc. Alternatively, interdigitated back contact cells rely on a gap between n- and p- fingers, which is commonly etched to ensure electronic isolation. We utilize a self assembled monolayer (SAM) using hexamethyldisilazane (HMDS) as a precursor to pattern and etch amorphous silicon (a-Si:H) and polysilicon without the need for photoresist. Ultraviolet light exposure oxidizes the HMDS by photocleaving the organic groups [1] of the SAM leaving a patterned SiO2. Directly soaking this in TMAH will eventually etch the SAM and the silicon, where the SiO2 serves as an etch mask. Inversely, a dilute HF dip selectively etches this SiO2 and the SAM remains. A subsequent soak in TMAH selectively etches the underlying silicon, where the SAM serves as an etch mask. Importantly, we find that the SAM can remain intact for metallization, where we measure 10 mO-cm2 specific contact resistivity on n-type polysilicon.

passivation↗

Artificial Intelligence for imaging Cherenkov detectors at the EIC

Abstract Imaging Cherenkov detectors form the backbone of particle identification (PID) at the future Electron Ion Collider (EIC). Currently all the designs for the first EIC detector proposal use a dual Ring Imaging CHerenkov (dRICH) detector in the hadron endcap, a Detector for Internally Reflected Cherenkov (DIRC) light in the barrel, and a modular RICH (mRICH) in the electron endcap. These detectors involve optical processes with many photons that need to be tracked through complex surfaces at the simulation level, while for reconstruction they rely on pattern recognition of ring images. This proceeding summarizes ongoing efforts and possible applications of AI for imaging Cherenkov detectors at EIC. In particular we will provide the example of the dRICH for the AI-assisted design and of the DIRC for simulation and particle identification from complex patterns and discuss possible advantages of using AI.

Instruments & Instrumentation↗