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HDG-2 and VIC Design updates. Including background, HDG-1 challenges, HDG-2 Mitigation efforts, Effect of updated ring model, Pressure boundary surface finish, and conclusions. Vendor Irradiation Capsule (VIC) to include, background, design overview, testing and neutronics results, and models.
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In a Computer Numerical Controlled (CNC) finishing process, the target material removal from an optical surface is guided by the convolution between the influence function of a machine tool and its dwell time at certain points over the surface. To reduce dynamics stressing and increase machining efficiency, the dwell time must be converted to varying velocities, which are the actual inputs to the machine tool controller. Conventionally, the conversion assumed constant acceleration and relied on linear motion interpolation, which caused discontinuities in velocities. This unsmooth motion affects the material removal distribution, and, thus, the accuracy of the finished surface shape. Many modern CNC machines support the smoother, cubic-polynomial interpolated Position-Velocity-Time (PVT) motion mode; however, the conventional scheduler may fail to provide suitable velocities for the PVT. Here in this study answers this challenge by proposing a novel PVT-based velocity scheduler that achieves smooth motion while considering CNC dynamic limits. Firstly, the principle of the PVT is explained, and the PVT-based velocity scheduler is formulated. Secondly, a quadratic programming is used to optimize the velocities by imposing the CNC dynamic constraints and the C 1 continuities (zeroth and first derivatives are continuous) simultaneously. Thirdly, the smoothness and accuracy of the scheduled velocities are studied on different kinds of tool paths via simulation. Finally, a sub-0.3 nm level surface finishing experiment using ion beam figuring is demonstrated to verify the feasibility of the proposed method. The PVT-based scheduler and simulator code is open-sourced.
Since 2001, 3D microfabrication based on two‐photon polymerization (TPP) has drawn extensive attention and interest in biology, optics, photonics, material science, and high‐energy physics. The in‐volume fabrication capability due to the threshold behavior of two‐photon absorption enables TPP higher flexibility compared with other nanofabrication techniques. However, as determined by the in‐volume fabrication feature as well as various reaction dynamics, the writing characteristics of TPP, such as throughput, accuracy, surface quality, and fabrication capability, are still limited. Herein, a comprehensive study is performed on the spatiotemporal behavior of reaction dynamics during TPP fabrication, mainly focusing on spatiotemporal characteristics of radical diffusion, photothermal effect, microscale mechanics, and voxel stacking process. Based on the study, a nonsequential fabrication method is established to simultaneously improve key writing characteristics of TPP and realize sharp features, high speeds, large overhang structure, and smooth surfaces. The method established in this work can be applied to improve the performance of functional devices for various fields.
Here, municipal solid waste (MSW)'s 40–60 % carbon content makes it a feedstock for biofuel production via pyrolysis. One challenge in the conversion process is MSW fouling due to thermal decomposition. The accumulated deposit on the injection screw often leads to plugging and constriction. This study examined the morphology and composition of the MSW fouling deposit and conducted a thermal simulation to understand the temperature gradience of the injection screw. Surface modifications including smoothening and anti-adhesion coating were proposed for the injection screw to address the deposit problem. For evaluating the candidate mitigations, a bench-scale fouling test was developed with the gas environment, temperature, and sliding speed relevant to the contact interface between the MSW particles and the screw. Results suggested that a smoother screw surface could reduce the grip and a non-metallic coating with a lower surface energy could decrease adhesion, consequently leading to less fouling. Specifically, reducing the roughness from 2 to 0.6 and then to 0.2 μm proportionally decreased the amount of deposit, and the diamond-like-carbon, CrN, and NiCr–CrC composite coatings effectively hindered the fouling process. This study provides fundamental insights into the MSW fouling and proof-of-concept of potential mitigations through the screw surface modification.
While machining processes are typically leveraged to establish geometric features, many functional characteristics of advanced materials are directly determined by their machining-induced surface integrity (SI). Current modeling approaches struggle to predict surface integrity, and typically neglect the effects of progressive tool-wear, resulting in inefficient ‘static’ process parameters. We present a novel integrated approach based on model-informed artificial intelligence (AI), which optimizes ‘dynamic’ process parameters in real-time. Here, by maximizing the useful life of a cutting tool over which a required set of SI parameters can be maintained, our paradigm will enable significantly more efficient processing of next-generation materials and components.
Deterministic finishing methods of optical components for high-peak-power laser applications that can meet the requirements for high laser damage resistance are not sufficiently developed to meet all needs. This is especially the case for ultraviolet (UV) laser applications. Fused silica is the material of choice for optics operating at UV wavelengths owing to its intrinsically large bandgap, high transparency, and excellent uniformity. Here we report on the laser damage behavior of fused silica surfaces finished by fluid jet polishing (FJP) as a function of removal depth. Fused silica test substrates were processed by FJP to depths ranging from 0.7 μm to 18 μm. Laser damage testing was conducted on these surfaces at 351 nm and 1-ns pulse lengths for both, 1-on-1 and R-on-1 testing protocols. The results for 1-on-1 testing showed no degradation in the laser-induced damage threshold (LIDT) of the substrates. Instead, a gradual improvement starting at a depth of 2.1 μm was observed and continued to the 18-μm surface. At 18-μm of removal, the LIDT was 16% higher than a surface that was not finished by FJP. For R-on-1 testing, all surfaces treated by FJP demonstrated an improvement in laser damage resistance. At depths greater than 5 μm, the improvements were significantly more pronounced and a 30% increase in the LIDT was realized.
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 ).
A method for the manufacture of a three-dimensional object using a refractory matrix material is provided. The method includes the additive manufacture of a green body from a powder-based refractory matrix material followed by densification via chemical vapor infiltration (CVI). The refractory matrix material can be a refractory ceramic (e.g., silicon carbide, zirconium carbide, or graphite) or a refractory metal (e.g., molybdenum or tungsten). In one embodiment, the matrix material is deposited according to a binder-jet printing process to produce a green body having a complex geometry. The CVI process increases its density, provides a hermetic seal, and yields an object with mechanical integrity. The residual binder content dissociates and is removed from the green body prior to the start of the CVI process as temperatures increase in the CVI reactor. The CVI process selective deposits a fully dense coating on all internal and external surfaces of the finished object.
A method for the manufacture of a three-dimensional object using a refractory matrix material is provided. The method includes the additive manufacture of a green body from a powder-based refractory matrix material followed by densification via chemical vapor infiltration (CVI). The refractory matrix material can be a refractory ceramic (e.g., silicon carbide, zirconium carbide, or graphite) or a refractory metal (e.g., molybdenum or tungsten). In one embodiment, the matrix material is deposited according to a binder-jet printing process to produce a green body having a complex geometry. The CVI process increases its density, provides a hermetic seal, and yields an object with mechanical integrity. The residual binder content dissociates and is removed from the green body prior to the start of the CVI process as temperatures increase in the CVI reactor. The CVI process selective deposits a fully dense coating on all internal and external surfaces of the finished object.
Niobium (Nb) superconducting radio frequency (SRF) cavities require electropolishing surface treatment to reach high acceleration gradient. EP performed in the plateau region of an I-V curve [1] leads to a smooth finish of the cavity surface including the equator surface. The equator surface is vital because a rough equator surface leads to premature quench and limit the cavity performance. Previous experimental work was performed to optimize EP parameters for low-beta (LB) 650 MHz Nb cavity [1]. It was found that different cathode surface areas vary the plateau onset voltage. A lower onset voltage was achieved for HB650 cavity with an enlarged cathode surface area. The aim of the study is to perform electrostatic and electrochemical simulation to understand the impact of both cavity geometry and cathodes. This report covers an initial result on electric field simulation performed with HB and LB 650 MHz cavities.
Numerous studies on the corrosion response of metal AM have been conducted. Nonetheless, the specimens being tested are commonly ground or polished to remove the outer as-built surface. If metal AM is truly going to be employed as a transformative technology that can produce complex shapes that do not require traditional machining, then the material needs to be evaluated in the as-built state. The reality is that AM alloys have shown significant inconsistencies regarding as-built surface texture, topology, and residual stress. One metric that has shown significant unpredictability in the literature is the susceptibility to localized corrosion of typically passive alloys, such as stainless steel (SS). There are a large number of studies that have attempted to understand the corrosion response of metal AM materials, but these studies are typically performed on materials that have been printed on a single machine and often mechanically polished to a smooth finish. This study compares the corrosion response of as-built AM, laser-beam powder bed fusion (LB-PBF), 316L SS parts that have been fabricated on five different machines. The majority of this work focused on understanding the susceptibility to localized corrosion of AM metals with respect to machine-dependent variables, namely surface roughness, and build angle. Surface roughness data was collected using scanning white light triangulation, laser scanning confocal microscopy, and coherence scanning interferometry. The results show that there is significant variability (p two-tail < 0.05) in the susceptibility to local corrosion initiation of LB-PBF 316L SS samples built on different machines. Surface oxides were probed with electron dispersive spectroscopy and revealed that variations in local corrosion susceptibility likely arise from differences in the stability of the passive film caused by chemical segregation, unique microstructure, and tortuous roughness features at the as-built surfaces. The variability of roughness and corrosion properties from test samples printed on different machines was corroborated by property measurements performed at five different testing sites, proving reproducibility of the data. Most importantly, this study shows that if the as-built surface layer is removed through grinding or electropolishing the machine-to-machine variation observed in the corrosion susceptibility is reduced.
Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.
We investigated and compared optoelectronic properties, crystallographic structures, and nanoscale surface morphologies of ex-situ phosphorus-doped polycrystalline silicon (poly-Si)/SiO x passivating contacts, formed by different deposition methods (sputtering, plasma-enhanced chemical vapour deposition (PECVD), and low-pressure chemical vapour deposition (LPCVD)). Across all these deposition technologies, a similar trend is observed: higher diffusion temperatures yield films that are more crystalline but have rougher surface morphologies due to bigger surface crystal grains. Also, the recrystallization process of the as-deposited Si films starts from the SiO x interface, rather than from the film surface and bulk. However, there are some distinct differences among these technologies. Firstly, the LPCVD method yields the roughest surface and smallest degree of crystallinity on finished poly-Si films. In contrast, the PECVD method has the smoothest surface for both as-deposited Si and annealed poly-Si films. Secondly, as-deposited sputtered and PECVD Si films contain only an amorphous phase whereas as-deposited LPCVD films has already had some crystalline phase. Thirdly, the LPCVD phosphorus in-diffusion into the substrate depends strongly on the initial film thickness, whereas for the other two methods it is weakly dependent on thickness.
In this work, we study how crystallographic structures, optoelectronic properties, and nanoscale surface morphologies of ex situ phosphorus-doped polycrystalline silicon (poly-Si)/SiO x passivating contacts, formed by different deposition methods (sputtering, plasma-enhanced chemical vapour deposition [PECVD], and low-pressure chemical vapour deposition [LPCVD]), are investigated and compared. Across all these deposition technologies, we noted the same trend: higher diffusion temperatures yield films that are more crystalline but that have rougher surface morphologies due to bigger surface crystal grains. Also, the recrystallization process of the as-deposited Si films starts from the SiO x interface, rather than from the film surface and bulk. However, there are some distinct differences among these technologies. First, the LPCVD method yields the lowest deposition rate, roughest surfaces, and smallest degree of crystallinity on finished poly-Si films. In contrast, the PECVD method has the highest deposition rate and smoothest surfaces for both as-deposited Si and annealed poly-Si films. Second, as-deposited sputtered and PECVD Si films contain only an amorphous phase, whereas as-deposited LPCVD films already has some crystalline phase. Third, the LPCVD phosphorus in-diffusion into the substrate depends strongly on the initial film thickness, whereas for the other two methods, it is weakly dependent on thickness. Finally, the passivation quality of every poly-Si film type has different responses to the film thickness and diffusion temperature, suggesting that the ex situ doping optimization should be performed independently.
The best performance of niobium SRF accelerating cavities is obtained with surfaces smoothed with electropolishing chemical finishing. Jefferson Lab has recently specified, procured, installed, and commissioned a new versatile production electropolishing (EP) tool. Experience with EP research and operations at JLab as well as vendor interactions and experience guided development of the system specification. Detailed design and fabrication was awarded by contract to Semiconductor Process Equipment Corporation (SPEC). The delivered system was integrated into the JLab chemroom infrastructure and commissioned in 2020. The new EP tool provides much improved heat exchange from the circulating H₂SO₄/HF electrolyte and also the cavity via variable temperature external cooling water flow, resulting in quite uniform cavity wall temperature control and thus improved removal uniformity. With the JLab infrastructure, stabilized process temperature as low as 5 C is available. We describe the system and illustrate operational modes in this contribution.
This repository contains datasets, training scripts, and finished models, and test simulations used in the development of DeepREBO— a machine-learned interatomic potential trained to emulate the REBO2 empirical potential. The data was generated to study deep potential development for simulations of plasma-surface interactions. It uses an active learning framework, starting from a minimal dataset and iteratively expanding it. Included are those generated datasets, the trained models, and simulations used to evaluate the performance of the training process. This resource supports reproducibility and provides a reference framework for training deep potentials in plasma-surface interaction studies.
Dwell time plays a vital role in determining the accuracy and convergence of the computer-controlled optical surfacing process. However, optimizing dwell time presents a challenge due to its ill-posed nature, resulting in non-unique solutions. To address this issue, several well-known methods have emerged, including the iterative, Bayesian, Fourier transform, and matrix-form methods. Despite their independent development, these methods share common objectives, such as minimizing residual errors, ensuring dwell time's positivity and smoothness, minimizing total processing time, and enabling flexible dwell positions. This paper aims to comprehensively review the existing dwell time optimization methods, explore their interrelationships, provide insights for their effective implementations, evaluate their performances, and ultimately propose a unified dwell time optimization methodology.