An electrochemical and surface analytical study of the formation of nanoporous oxides on niobium

In the present paper, the anodization of Nb in mixed sulphate + fluoride electrolytes resulting in the formation of a nanoporous oxide film has been studied. Chronoamperometry and electrochemical impedance spectroscopy have been employed to characterise in situ the kinetics of the oxidation process. In addition, the evolution of the layer structure and morphology has been followed by ex situ scanning electron microscopy. Particularly, local electrochemical impedance spectroscopy has been used to discern between the mesoscopic 2D and 3D distributions of time constants at the electrode surface. The similarity between local and global impedance spectra during anodic oxidation of Nb demonstrates the presence of an inherent 3D distribution of the high-frequency time constant, which is interpreted as in-depth variation of the steady state conductivity of the passive film. The experimental and calculational results are discussed in relation to the micro- and nanoscopic structure of the formed oxide

Design-Based Confidence Sequences for Anytime-valid Causal Inference

Many organizations run thousands of randomized experiments, or A/B tests, to statistically quantify and detect the impact of product changes. Analysts take these results to augment decision-making around deployment and investment opportunities, making the time it takes to detect an effect a key priority. Often, these experiments are conducted on customers arriving sequentially; however, the analysis is only performed at the end of the study. This is undesirable because strong effects can be detected before the end of the study, which is especially relevant for risk mitigation when the treatment effect is negative. Alternatively, analysts could perform hypotheses tests more frequently and stop the experiment when the estimated causal effect is statistically significant; this practice is often called "peeking." Unfortunately, peeking invalidates the statistical guarantees and quickly leads to a substantial uncontrolled type-1 error. Our paper provides valid confidence sequences from the design-based perspective, where we condition on the full set of potential outcomes and perform inference on the obtained sample. Our design-based confidence sequence accommodates a wide variety of sequential experiments in an assumption-light manner. In particular, we build confidence sequences for 1) the average treatment effect for different individuals arriving sequentially, 2) the reward mean difference in multi-arm bandit settings with adaptive treatment assignments, 3) the contemporaneous treatment effect for single time series experiment with potential carryover effects in the potential outcome, and 4) the average contemporaneous treatment effect in panel experiments. We further provide a variance reduction technique that incorporates modeling assumptions and covariates to reduce the confidence sequence width proportional to how well the analyst can predict the next outcome

Anytime-Valid Linear Models and Regression Adjusted Causal Inference in Randomized Experiments

Linear regression adjustment is commonly used to analyse randomised controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to provide Type-I error and coverage guarantees that hold only at a single sample size. Here, we develop the theory for the anytime-valid analogues of such procedures, enabling linear regression adjustment in the sequential analysis of randomised experiments. We first provide sequential $F$-tests and confidence sequences for the parametric linear model, which provide time-uniform Type-I error and coverage guarantees that hold for all sample sizes. We then relax all linear model parametric assumptions in randomised designs and provide nonparametric model-free sequential tests and confidence sequences for treatment effects. This formally allows experiments to be continuously monitored for significance, stopped early, and safeguards against statistical malpractices in data collection. A particular feature of our results is their simplicity. Our test statistics and confidence sequences all emit closed-form expressions, which are functions of statistics directly available from a standard linear regression table. We illustrate our methodology with the sequential analysis of software A/B experiments at Netflix, performing regression adjustment with pre-treatment outcomes

Effect of hydrogen on electrochemical behavior of additively manufactured 316L in pressurized water reactor primary water

The electrochemical behavior of laser powder bed fusion (LPBF) 316 L stainless steel subject to different heat-treatments (solution annealing and hot isostatic pressing) is compared to nuclear-grade wrought 316 L in pressurized water reactor primary water at 288 °C (with and without dissolved hydrogen) using current-time transients, cyclic voltammetry and electrochemical impedance spectroscopy (EIS). Analysis of spectra by the Mixed-Conduction Model revealed slower corrosion rates of LPBF 316 L than wrought 316 L, the effect being more pronounced in the presence of dissolved hydrogen. The characteristics of the barrier layer and the oxide film/coolant interface were irreversibly altered upon removal of dissolved hydrogen

Mechanistic understanding of the localized corrosion behavior of laser powder bed fused 316L stainless steel in pressurized water reactor primary water

The laser powder bed fused (LPBFed) stainless steels showed anomalous and localized corrosion behavior in the nuclear reactor high-temperature water compared to their wrought counterparts, which affects their performance during plant operation. In this study, advanced microstructural characterization was performed on LPBFed 316 L sample along with wrought 316 L sample after corrosion tests to understand the underlying mechanisms. The results showed that an inhomogeneous/discontinuous inner oxide layer formed on LPBFed 316 L, in contrast to the continuous inner oxide layer on the wrought 316 L specimen. This discontinuous inner oxide layer was identified to consist of Cr-enriched nano-sized spinel oxide and the barrier layer features a Ni-enriched hexagonal close-packed Laves phase. Localized/preferential oxidation was found to occur along the cellular walls which were tangled with high density dislocations and decorated with Mn and Si-enriched nano-sized precipitates, and the nano-precipitates were observed in the core of dispersed Cr-enriched inner oxide crystals

Effect of hydrogen on electrochemical behavior of additively manufactured 316L in pressurized water reactor primary water

The electrochemical behavior of laser powder bed fusion (LPBF) 316 L stainless steel subject to different heat-treatments (solution annealing and hot isostatic pressing) is compared to nuclear-grade wrought 316 L in pressurized water reactor primary water at 288 °C (with and without dissolved hydrogen) using current-time transients, cyclic voltammetry and electrochemical impedance spectroscopy (EIS). Analysis of spectra by the Mixed-Conduction Model revealed slower corrosion rates of LPBF 316 L than wrought 316 L, the effect being more pronounced in the presence of dissolved hydrogen. The characteristics of the barrier layer and the oxide film/coolant interface were irreversibly altered upon removal of dissolved hydrogen