It is well-known that Ni alloy 600 exhibits lower susceptibility to SCC than stainless steel 304 in chloride-containing environments. To understand potentially relevant electrochemical differences, the kinetics of localized dissolution and the repassivation behavior of the two alloys were compared under pit/crack-like environments. Downward potential scans were conducted at isothermal conditions on 1D pit samples to assess the kinetics of metal dissolution. Downward temperature scans under potentiostatic conditions were performed to determine the conditions of potential, temperature and pit depth at which each alloy repassivates. Alloy 600 exhibits slower activation-controlled dissolution kinetics than SS304 in pit/crack-like environments. However, Ni600 stays active at conditions of lower aggressiveness, like lower temperature, whereas SS304 exhibits a higher tendency to repassivate. DFT calculations help explain these conflicting results and develop an understanding of the behavior of these different materials under SCC conditions.

Computational crystal structure prediction (CSP) is an increasingly powerful technique in materials discovery, due to its ability to reveal trends and permit insight across the possibility space of crystal structures of a candidate molecule, beyond simply the observed structure(s). In this work, we demonstrate the reliability and scalability of CSP methods for small, rigid organic molecules by performing in-depth CSP investigations for over 1000 such compounds, the largest survey of its kind to-date. We show that this highly-efficient force-field-based CSP approach is superbly predictive, locating 99.4% of observed experimental structures, and ranking a large majority of these (74%) as among the most stable possible structures (to within uncertainty due to thermal effects). We present two examples of insights such large predicted datasets can permit, examining the space group preferences of organic molecular crystals and rationalising empirical rules concerning the spontaneous resolution of chiral molecules. Finally, we exploit this large and diverse dataset for developing transferable machine-learned energy potentials for the organic solid state, training a neural network lattice energy correction to force field energies that offers substantial improvements to the already impressive energy rankings, and a MACE equivariant message-passing neural network for crystal structure re-optimisation. We conclude that the excellent performance and reliability of the CSP workflow enables the creation of very large datasets of broad utility and explanatory power in materials design.

We present an extensive exploration of the solid-form landscape of chlorpropamide (CPA) using a combined experimental-computational approach at the frontiers of both fields. We have obtained new conformational polymorphs of CPA, placing them into context with known forms using flexible-molecule crystal structure prediction. We highlight the formation of a new polymorph (ζ-CPA) via spray-drying experiments despite its notable metastability (14 kJ/mol) relative to the thermodynamic α-form, and we identify and resolve the ball-milled η-form isolated in 2019. Additionally, we employ impurity- and gel-assisted crystallization to control polymorphism and the formation of novel multicomponent forms. We, thus, demonstrate the power of this collaborative screening approach to observe, rationalize, and control the formation of new metastable forms.

The seventh blind test of crystal structure prediction (CSP) methods substantially increased the level of complexity of the target compounds relative to the previous tests organized by the Cambridge Crystallographic Data Centre. In this work, the performance of density-functional methods is assessed using numerical atomic orbitals and the exchange-hole dipole moment dispersion correction (XDM) for the energy-ranking phase of the seventh blind test. Overall, excellent performance was seen for the two rigid molecules (XXVII, XXVIII) and for the organic salt (XXXIII). However, for the agrochemical (XXXI) and pharmaceutical (XXXII) targets, the experimental polymorphs were ranked fairly high in energy amongst the provided candidate structures and inclusion of thermal free-energy corrections from the lattice vibrations was found to be essential for compound XXXI. Based on these results, it is proposed that the importance of vibrational free-energy corrections increases with the number of rotatable bonds.

Corrosion of buried, coated steel pipelines transporting natural gas is a significant source of methane emissions, from pipeline venting required for maintenance and repairs and from pipeline leaks and incidents. Corrosion of steel under field applied coatings is an important safety concern for the pipeline industry. This project investigates the application of a field applied alloy over girth welds to mitigate external corrosion of buried coated steel pipelines. Various metallic coating options were considered, which were required to meet several criteria: (1) it must resist corrosion under open-circuit or mild cathodic protection conditions, (2) it must protect the substrate steel, and (3) it must not negatively affect the adhesion of the field coating. Finite element models and lab testing were performed of alloy coating compositions to identify promising alloy types underneath disbonded coatings. Polarization curves of coating alloys were generated to provide the boundary conditions for the COMSOL model to compute potential and current distributions around coated areas. Sacrificial and corrosion-resistant metal alloy coatings were evaluated and optimized using corrosion modeling and laboratory electrochemical testing, where aluminum alloy 5356 (5% Mg) and steel alloy B9 (9% Cr) were selected. Corrosion test coupons were designed and fabricated using flame-sprayed aluminum 5356 and welded B9 steel overlays on API 5L grade X42 line pipe steel. The corrosion test coupons, with simulated pipe coating damage, were tested in a laboratory soil box and a field pipeline site in Texas for 3-months. Corrosion test coupons were then tested for 6-months at field pipeline sites in Texas and Tennessee to quantify corrosion rates and performance of the aluminum and steel alloys under polyethylene tape and 2-part epoxy coatings, various coating holidays, and with and without cathodic protection.

Natural gas pipeline operators often rely on gas and liquid sample analysis as well as bacteria serial dilution to determine if corrosive conditions exist within the pipeline. When corrosive conditions are suspected, additional monitoring methods such as corrosion coupons or probes are employed. One of the challenges faced by operators is determining what constitutes “corrosive conditions” because existing regulations do not define gas or liquid compositions that are corrosive. In this study, over a decade’s worth of sampling and corrosion monitoring data collected by a natural gas pipeline operator are assessed using machine learning in order to determine the parameters with the greatest influence on corrosion rate. This work combines over 2,300 gas tests, liquid samples, solid samples, and bacteria tests in an attempt to determine if the thresholds the company is using are reflective of where corrosion is actually occurring based on over 1,700 coupon analysis results within an operator’s unique system. The results from this study can be used to guide future sampling practices so that effort is spent collecting the most meaningful data and improving the ability to identify corrosive conditions.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

3D printing of metals, such as laser powder bed fusion (LPBF) printing of stainless steels, often leads to elevated oxygen content in the alloy substrate relative to conventional processing routes. Here we show that the extremely rapid cooling rate (106-107 K/s) during LPBF processing of austenitic stainless steel can trap a considerable fraction of oxygen and other elements in the interstitial sites of the metal lattice, at concentrations far exceeding the room temperature solubilities. High resolution character-ization and atomistic simulations with density functional theory reveal that oxygen and other elements exist in octahedral interstitial sites of the metal lattice and bond with their neighboring metal atoms. Our findings suggest that additive manufacturing can be a potential strategy of incorporating beneficial interstitial elements into a metal substrate. Given the well-known effect of interstitial elements in conventional alloys, significant improvement of the physicochemical properties of printed alloys is possible.

The DOE Office of Environmental Management is responsible for high level nuclear waste that must be safely isolated from humans and the environment for extremely long periods. The waste forms and containers are made of glass, ceramics, and metals. Verified safe disposal requires understanding the fundamental mechanisms of waste form degradation and the design of new waste forms with improved performance, which comprise the goals of the Energy Frontier Research Center known as the Center for the Performance and Design of Nuclear Waste Forms and Containers, WastePD. WastePD was constructed to develop innovative approaches and solutions to those goals through the synergistic interactions of individuals who are experts in the degradation behavior, modeling, and design of glasses, ceramics and metal alloys. WastePD is the first center ever created to address this diverse group of materials in a comprehensive and coordinated manner. The science goals are grouped into three common topics: corrosion mechanisms via advanced characterization, environmental impacts, and materials design. Synergistic interactions in these areas were a key component of WastePD. The fundamental understanding of the degradation mechanisms of the waste forms and containers as well as the development of new materials with improved properties will allow DOE to prevent environmental contamination and to explore totally new repository concepts. WastePD was operational from August 2016 through July 2022, but the DOE support was drastically reduced for the last two years. This final technical report covers the full period of performance. However, much of what was accomplished in the first four years is nicely summarized in a review paper published in 2021, which is appended to this report. Therefore, this final report focuses on the technical findings from the last two years of WastePD activities. Considerable progress was made in the areas of a) the environmental and compositional impacts on the corrosion of borosilicate and aluminosilicate glasses, b) the mechanism of glass corrosion and the structure and evolution of the surface alteration layer, c) the effects of environment and composition on the corrosion of pyrochlore, perovskite, hollandite, and other oxide ceramics, d) the corrosion mechanism of multi-principal element metallic alloys, and e) a new framework for understanding the pitting corrosion of metals.

An intermittent pattern is observed in the modeling of interfacial cyclic-loading crack growth at high-angle grain boundaries in ternary Fe-Ni-Cr alloys. Different from conventional wisdom of stress-intensity factor, the abrupt crack advances are found driven by extreme value statistics-namely, the aggregation of atoms with most compressive residual stresses. In addition, inherently non-affine atomic stress fluctuations are discovered, and the fluctuations peak at intermediate level of chemical heterogeneity, causing the fastest crack growth. Implications of such nonmonotonic mechanism in regard to the origin of intermediate-temperature embrittlement phenomena are also discussed.

This study examines the effect of copper alloying on pitting resistance in a model solid solution FCC Ni-13%Cr-10%Fe alloy through potentiodynamic and potentiostatic polarization in 0.1 M NaCl in conjunction with an analysis using first-principles competitive electro-chemisorption modeling. The pitting potential increased with increasing Cu content in the alloy. Furthermore, the extent of metastable pit growth was suppressed and the incubation time for metastable to stable pit transition increased with Cu content. The first-principles competitive adsorption calculations suggested that Cu alloying suppresses chloride ion adsorption on the alloy surface in a simulated pit environment, which inhibits active dissolution at the pit bottom, enhances proton adsorption, and thereby increases the local pH at the pit bottom. We propose that these two effects of Cu in solid solution combine to reduce pit stability and may act in addition to the enrichment of Cu on the corroding pit surface.

The purpose of the Research Topical Symposia (RTS) is to bring together corrosion researchers and practitioners, through invited talks from leading experts in topical areas. The 2022 RTS was focused on corrosion life prediction methods used in diverse industries. Most of the talks have been assembled in this Special Issue. The underlying theme of the special issue is the integration of mechanistic insights, experimental data, and field performance into probabilistic methods. Although such approaches can be found in many articles published in CORROSION journal, the intent of the Special Issue is to highlight the topic and spur further research and application.The article by Srinivasan, et al., is an example of coupling microscopic study of the relationship between pit morphology and the type of aerosol salt deposition on stainless steels. The pit morphology can affect the pit to crack transition and has implications to life prediction of stainless steel components exposed to coastal atmospheres, such as spent nuclear fuel storage casks. Rebak provides a perspective on new developments in accident tolerant fuels to mitigate risks of catastrophic reactions of fuel/cladding under extreme scenarios and enable more sustainable operation of nuclear fission reactors.Wang and Chen discuss life prediction of buried oil and gas pipelines subject to stress corrosion cracking (SCC), specifically focusing on early-stage crack growth. They point to the role played by strain fluctuations and low-temperature creep in the early stages of crack extension. While most of the discussion is on deterministic modeling of crack growth process, they identify stochastic elements of crack coalescence. Ramgopal, et al., discuss the hydrogen embrittlement (HE) of precipitation hardenable Ni-based alloys in offshore oil and gas production systems. They describe the roles of crack-tip strain rate, deformation mode, and crack-tip chemistry on HE. An interesting aspect of their article is the possible connection between molecular level modeling of water adsorption at the crack tip and the effect of applied potential on HE in seawater. Harris, et al., examined the environmentally assisted cracking (EAC) of a high-strength martensitic steel coupled to Ti-6Al-4V bolting material and different metallic coatings to simulate a bearing/gear application in aerospace service. An important aspect of the article is the combination of finite element analysis of the potential distribution due to the galvanic coupling of steel to Ti alloy with fracture mechanics-based prediction of EAC. Such coupling can help simulate complex geometries of service components, while maintaining veracity to mechanisms of EAC.Sagues and Alexander introduce a new damage prediction model for reinforced concrete. This approach recognizes that the initiation and propagation stages of damage are coupled through the coupling of potential within the extended concrete structure. The coupling of potential can occur between different regions of a reinforced concrete system that are at different stages of damage. The coupled potential model predicts a slower progress of damage. The authors point to the need to further examine the sensitivity of the model prediction with assumptions of activation volume. Best and Gelling provide a historical review of life prediction of organic coatings and the uncertainties attendant upon field application of coatings. They describe the disconnect between life prediction based on controlled laboratory testing and performance in the field as well as identify probabilistic methods to address the various sources of uncertainty in field conditions. Sridhar describes a Bayesian network approach to integrating diverse sources of data and mechanistic models for predicting seawater corrosion of passive alloys. The challenges attending this approach are described.Corrosion life prediction is a vast area of study and each application has its own peculiar circumstances that influence performance of the materials, components, and system. A comprehensive coverage of the entire field is well beyond the scope any one publication. However, it is hoped that this special issue will provide the readers a snapshot of the diversity of approaches that have been used and inspire further research.

Converting natural gas pipelines to transport pure hydrogen or blends with natural is currently being implemented as part of the energy transition strategy to achieve net zero emissions. Addition of hydrogen to existing natural gas pipelines increases the risk of hydrogen embrittlement and poses potential integrity issues such as cracking to the pipelines. Prior work has demonstrated that the use of inhibitors such as oxygen, carbon monoxide, and others can inhibit a material's adsorption of atomic hydrogen and have been proposed to reduce the risk of hydrogen embrittlement. While these inhibitors may potentially reduce the risk of hydrogen embrittlement, there may be unintended consequences if the impact of these inhibitors on internal corrosion is not carefully evaluated. For example, the use of oxygen in the inhibitors can increase the potential for oxygen corrosion. This paper covers the methodology to evaluate the impact of internal corrosion on pipelines for any inhibitors used to prevent hydrogen embrittlement before they are applied. The recommendations for internal corrosion control when using oxygen-based inhibitors are discussed. Additionally, a comprehensive review of the proposed inhibitors for hydrogen embrittlement along with a discussion on their mode of action to prevent or mitigate hydrogen embrittlement is presented.

Fe-C alloys with free graphite in the microstructure are common industrial materials. Minor impurities can change the morphology of the graphite and the thermo-mechanical properties of the cast material; however, atomic mechanisms behind the impurity effects are unclear. We studied the interaction between solute elements found in cast iron materials and the interfaces that form in Fe-C alloys during solidification using density functional theory. Solute elements adsorb easily on graphite prismatic planes compared to the basal plane at the early solidification stage. When austenite phase envelops graphite, the migration energy indicates that O, C, S, Mg, Ti, and Cr migrate to the interface. At the same time, Si, Al, Mn, and Mo have no preference to migrate to the interface. The formation of carbon clusters on the undoped γ-Fe (111) and (Cr, O, Mg) doped surfaces was investigated. We demonstrate that linear carbon chains form initially, before hexagonal rings nucleate and are favored for undoped and Cr-doped surfaces. The configurations confirm the preferred growth direction of graphite in pure Fe-C alloy along the a-axis. Our findings shed light on the influence of solute elements on carbon phase morphology when precipitated directly from Fe-C melt at the atomic scale.

Insights into the roles of geometry, size, and composition on MnS inclusion dissolution to initiate pits in 304L SS were obtained by combining operando and ex-situ electron microscopy, EDS, and atomistic modeling. The majority of thirty MnS on SS surface did not undergo dissolution even after over a week of exposure, and only a small number caused an attack of SS. Operando TEM during potentiodynamic polarization confirmed that MnS attack was followed by corrosion of the nearby SS substrate. Atomistic modeling revealed that elemental variations in the surface composition may play a role in differentiating pitting initiation by sulfur species.

The design and corrosion resistance of five single-phase Ni-Fe-Cr-Mo-W-X (X = Mn, Al, and Cu) multi principal element alloys (MPEAs) has been recently reported. In this study, these alloys were heat treated at 800 degrees C for up to 160 h starting from the solutionized single-phase to allow precipitation of secondary phases that provide increased hardness and strength. During heat treatment at 800 degrees C, Sigma-phase rich in Cr, Ru, Mo and W precipitated at the grain boundaries in each alloy. Furthermore, copious in-grain precipitation was observed in the MPEAs containing Mn and Al. After aging, the hardness of the MPEA containing Al showed the most significant increase in hardness, about 90%, due to the precipitation. Multiple phases that were different from those predicted to exist at thermodynamic equilibrium were identified in the microstructure of the aged MPEAs using electron microscopy. During cyclic potentiodynamic polarization experiments in 0.6 M NaCl, all five aged MPEAs were found to be spontaneously passive. Only the MPEAs containing Mn, Cu or Al became susceptible to localized corrosion at higher potentials due to breakdown at the interface between the matrix and precipitate. (c) 2021 Elsevier B.V. All rights reserved.

How can we design short-term laboratory corrosion tests to adequately simulate long-term outdoor atmospheric corrosion? To achieve this objective, models need to be devised to rank and quantify critical environmental variables that influence atmospheric corrosion. This effort provides a data-driven analysis of environmental factors that can be used to quantitatively model atmospheric corrosion aluminum alloy 2024-T3 (AA2024-T3) samples placed at three unique coastal sites in the state of Florida, USA, for various time periods over an 18-month total period of exposure. Atmospheric corrosion proceeds via several processes that take place in sequence and/or in parallel across multiple classes of matter: the atmosphere, condensed aqueous solution, organic coatings, oxide scales, precipitated salts, and microstructurally heterogeneous metal alloys. Several physical and chemical phenomena contribute to the process of corrosion, including mass-transport, electrochemical effects, metal dissolution, grain-boundary transport, etc. For this reason it is difficult to directly predict, using fundamental physics or chemical principles, the corrosion rate of a metal in its environment. Likewise, it is difficult to directly extrapolate the results of short-term tests to long-term tests solely from physical principles. A modeling approach that pairs data analytics with scientific insight is required. To support this objective, data was collected for AA2024-T3 coupons based on exposure over an 18-month period at three coastal sites in Florida, USA. Methods to summarize the environmental exposure metrics for each time period were developed using standard statistical metrics (mean, standard deviation) as well as a more complete set of metrics, known as the Catch-22 algorithms, developed by The University of Oxford. The corrosion coupon data was aggregated into a data framework that included the metrics of mass loss per unit area, linear corrosion rate, and a parabolic corrosion constant, as well as generation of additional data by sample differencing that considers cumulative corrosion occurring between time periods. An automated approach was then developed that queries public and/or pay-to-access websites for environmental data to build an exposure profile for a sample placed at a known location (specified by latitude/longitude) and over a given range of dates. We evaluated 288 total variables in the exposure profile. Of these 288 variables, five key variables were determined to have a quantitative effect on the corrosion rate and mass loss per unit area, and these include mean precipitation, the range of temperatures, the minimum wind speed, the standard deviation of ozone exposure, and the maximum solar irradiance. This work serves to help with the selection of appropriate variables to be used in designs for a laboratory-simulation exposure chamber that would mimic service environment and accelerate the development of advanced materials degradation test protocols. The approach developed herein can be applied to other materials of interest, different locations, and adapted to other metrics of corrosion such as localized corrosion depth and volume, due to pitting.

Materials stewardship is an informed approach to materials management that addresses the maintenance of the material during product ownership and the “second life” of the material after its present use expires. Materials stewardship has been expressed as the four D’s strategies of dematerialization, durability, design for multiple lifecycles, and diversion of waste streams through industrial symbiosis. The framework of materials stewardship provides corporations, government organizations, and their stakeholders a model for preserving and extending the lifetime of materials, thus reducing the rate of materials throughput, cutting waste, and preventing the social, environmental and economic costs due to materials failure. Materials stewardship intersects with the concepts of cradle to cradle and the circular economy. Cradle to cradle is a biomimetic method for product (and system) design that intentionally seeks to harvest materials (and/or energy) at the end of life for future products. The circular economy is a broader view that patterns economic, agricultural and industrial systems around circular lifecycles, in which activities such as product reuse, maintenance, repair, refurbishment, etc. enhance value and reduce waste. In this paper we introduce these concepts, and highlight areas in which an awareness of corrosion management and materials integrity would enhance the viability of these sustainable models.

Laser powder bed fusion (PBF) has been used to create structures of many different alloys including stainless steels (SS). In contrast to SS prepared via conventional approaches, PBF-produced SS often contains a high concentration of oxygen. It is generally believed that the oxygen primarily exists as oxide inclusions with diameters ranging from tens of nanometers to several microns. Thermodynamic calculations also show that the solubility of the oxygen is extremely low in the liquid, face center cubic (FCC), or body center cubic phases that are relevant to the composition of the SS investigated in this study. Additionally, these calculations predict that majority of oxygen stays in the metastable MnSiO3 phase. In this study, we perform multi-scale, quantitative electron microscopic analysis on the as-printed SS 316L and find that a large amount of oxygen actually exists in the interstitial sites of the alloy lattice, suggesting that oxygen might have been trapped in the alloy substrate during the rapid cooling process of PBF. The observations from the atomic-scale-resolution characterization are supported by the first principles simulations through density functional theory calculations, which reveal that oxygen can stay energetically stable in the octahedral site of the FCC structure. Additionally, these interstitial oxygen atoms can form ionic bonds with the neighboring metal atoms, with a particularly high affinity towards Cr atoms. The presence of interstitial oxygen in the SS substrate appears to assist the surface passivation processes and lead to the exceptionally high pitting potential. The identification of a large amount of interstitial oxygen in the alloy may have a profound impact on the design of strong, tough, and corrosion resistant alloys.