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NASA NTRS1993

Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in large-scale atmospheric models.

Avissar, Roni↗

DOE OSTI2021

Modulating Interactions between Molten Polystyrene and Porous Solids Using Atomic Layer Deposition

Understanding and modulating the interactions between molten polymers and porous solids is important for numerous processes and phenomena including catalytic conversion of polymers and fabrication of nanocomposites and nanostructured materials. Although changing the surface composition of pores would enable modulation of interactions between polymer and nanoporous solids, it is challenging to achieve such a control without inducing significant changes to the size and structure of nanopores. In this work, we demonstrate that the interactions between molten polystyrene (PS) and disordered packings of SiO 2 nanoparticles (NPs) can be modulated by changing the surface composition of the NPs using atomic layer deposition (ALD). A disordered packing of silica NPs is modified with varying surface coverages of TiO 2 , WO 3 and CaCO 3 , with coverages estimated by the mass gain and the refractive index change of NP packings. Based on the time required to fully infiltrate these ALD-modified NP packings via capillarity, the contact angles for PS on different surfaces prepared via ALD are determined. The contact angle gradually changes from that of pure SiO 2 to that of the fully covered surfaces. The contact angles for PS on SiO 2 , TiO 2 , WO 3 and CaCO 3 are found to be 20°, 62°, 70° and 10°, respectively. Interestingly, the contact angles and interfacial energies between PS and the ALD-modified surfaces do not correlate strongly with the water contact angle of these surfaces; thus, caution must be exercised in predicting how a polymer would wet or interact with porous solids solely based on their hydrophilicity. Furthermore, the method presented in this work can be extended to study the interactions between a wide range of polymers and surfaces in porous media, which will have important implications for designing new catalytic materials for polymer upcycling reactions as well as novel NP-polymer composite films and membranes with enhanced mechanical and transport properties.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Feature extraction and classification algorithms for high dimensional data

Feature extraction and classification algorithms for high dimensional data are investigated. Developments with regard to sensors for Earth observation are moving in the direction of providing much higher dimensional multispectral imagery than is now possible. In analyzing such high dimensional data, processing time becomes an important factor. With large increases in dimensionality and the number of classes, processing time will increase significantly. To address this problem, a multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage. Several truncation criteria are developed and the relationship between thresholds and the error caused by the truncation is investigated. Next an approach to feature extraction for classification is proposed based directly on the decision boundaries. It is shown that all the features needed for classification can be extracted from decision boundaries. A characteristic of the proposed method arises by noting that only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is introduced. The proposed feature extraction algorithm has several desirable properties: it predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal means or equal covariances as some previous algorithms do. In addition, the decision boundary feature extraction algorithm can be used both for parametric and non-parametric classifiers. Finally, some problems encountered in analyzing high dimensional data are studied and possible solutions are proposed. First, the increased importance of the second order statistics in analyzing high dimensional data is recognized. By investigating the characteristics of high dimensional data, the reason why the second order statistics must be taken into account in high dimensional data is suggested. Recognizing the importance of the second order statistics, there is a need to represent the second order statistics. A method to visualize statistics using a color code is proposed. By representing statistics using color coding, one can easily extract and compare the first and the second statistics.

Lee, Chulhee↗

NASA NTRS2012

2D Radiative Processes Near Cloud Edges

Because of the importance and complexity of dynamical, microphysical, and radiative processes taking place near cloud edges, the transition zone between clouds and cloud free air has been the subject of intense research both in the ASR program and in the wider community. One challenge in this research is that the one-dimensional (1D) radiative models widely used in both remote sensing and dynamical simulations become less accurate near cloud edges: The large horizontal gradients in particle concentrations imply that accurate radiative calculations need to consider multi-dimensional radiative interactions among areas that have widely different optical properties. This study examines the way the importance of multidimensional shortwave radiative interactions changes as we approach cloud edges. For this, the study relies on radiative simulations performed for a multiyear dataset of clouds observed over the NSA, SGP, and TWP sites. This dataset is based on Microbase cloud profiles as well as wind measurements and ARM cloud classification products. The study analyzes the way the difference between 1D and 2D simulation results increases near cloud edges. It considers both monochromatic radiances and broadband radiative heating, and it also examines the influence of factors such as cloud type and height, and solar elevation. The results provide insights into the workings of radiative processes and may help better interpret radiance measurements and better estimate the radiative impacts of this critical region.

Varnai, T.↗

DOE OSTI2024

Breaking Boundaries: Deformation Processing Techniques for the Next Generation of Lightweight and High-Strength Materials

This chapter emphasizes the importance of solid phase processing (SPP) techniques in developing advanced materials for lightweight and high-strength applications. SPP methods like friction stir welding, and shear-assisted processing can create new microstructures and process materials in novel ways. SPP can enhance mechanical performance via various strengthening mechanisms like solid solution supersaturation, Hall-Petch and Orowan effects, and misorientation angle grain boundaries. The potential for in situ alloying or joining of components with near-net shape and low energy inputs, even for immiscible systems with high enthalpies of mixing, is also discussed. The chapter explores the concept of metastability through microstructural manipulation and the role of advanced characterization for atomistic understanding. The formation of metastable grain, shear-driven chemical mixing, and transformation pathways are also discussed. Finally, the emerging trends for SPP and the challenges that need to be addressed before realizing the full potential of these techniques are presented.

Lastovich, Michael↗

DOE OSTI2023

The Sluggish Diffusion of Cations in CeO 2 Probed through Molecular Dynamics and Metadynamics Simulations

Cation diffusion in fluorite‐structured CeO 2 , though far slower than anion diffusion, is an important, high‐temperature process because it governs diverse fabrication and degradation phenomena. Herein, cation diffusion is studied by means of classical molecular dynamics and metadynamics simulations. Three different mechanisms are examined: migration involving an isolated cerium vacancy, migration involving a cerium vacancy in a defect associate with an oxygen vacancy, and migration involving a cation divacancy. For each mechanism, defect diffusion coefficients are calculated as a function of temperature, from which the respective activation enthalpy of defect migration is obtained. Through comparisons with experimental cation diffusion data (specifically, of the absolute magnitude of the cation diffusivity as well as its activation enthalpy), it is concluded that cation diffusion takes place predominantly neither by isolated vacancies nor by cation vacancy–oxygen vacancy associates but by cation divacancies.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Scale-fixed predictions for γ + η c production in electron-positron collisions at NNLO in perturbative QCD

In the paper, we present QCD predictions for γ + η c production at an electron-positron collider up to next-to-next-to-leading order (NNLO) accuracy without renormalization scale ambiguities. The NNLO total cross-section for e + + e – → γ + η c using the conventional scale-setting approach has large renormalization scale ambiguities, usually estimated by choosing the renormalization scale to be the e + e – center-of-mass collision energy $\sqrt{s}$. The Principle of Maximum Conformality (PMC) provides a systematic way to eliminate such renormalization scale ambiguities by summing the nonconformal β contributions into the QCD coupling α s ( Q 2 ). The renormalization group equation then sets the value of α s for the process. The PMC renormalization scale reflects the virtuality of the underlying process, and the resulting predictions satisfy all of the requirements of renormalization group invariance, including renormalization scheme invariance. After applying the PMC, we obtain a renormalization scale-and-scheme independent prediction, σ | NNLO,PMC ≃ 41.18 fb for $\sqrt{s}$=10.6 GeV. The resulting pQCD series matches the series for conformal theory and thus has no divergent renormalon contributions. The large K factor which contributes to this process reinforces the importance of uncalculated NNNLO and higher-order terms. Using the PMC scale-and-scheme independent conformal series and the Padé approximation approach, we predict σ | NNNLO,PMC+Pade ≃ 18.99 fb, which is consistent with the recent BELLE measurement ${\sigma}^{\mathrm{obs}}={16.58}_{-9.93}^{+10.51}$ fb at $\sqrt{s}$ ≃ 10.6 GeV. This procedure also provides a first estimate of the NNNLO contribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Measurement of electroweak $Z\left(\nu \overline{\nu}\right)\gamma jj$ production and limits on anomalous quartic gauge couplings in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

The electroweak production of $Z\left(\nu \overline{\nu}\right)\gamma jj$ in association with two jets is studied in a regime with a photon of high transverse momentum above 150 GeV using proton–proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider. The analysis uses a data sample with an integrated luminosity of 139 fb –1 collected by the ATLAS detector during the 2015–2018 LHC data-taking period. This process is an important probe of the electroweak symmetry breaking mechanism in the Standard Model and is sensitive to quartic gauge boson couplings via vector-boson scattering. The fiducial $Z\left(\nu \overline{\nu}\right)\gamma jj$ cross section for electroweak production is measured to be ${0.77}_{-0.30}^{+0.34}$ fb and is consistent with the Standard Model prediction. Evidence of electroweak $Z\left(\nu \overline{\nu}\right)\gamma jj$ production is found with an observed significance of 3.2σ for the background-only hypothesis, compared with an expected significance of 3.7σ. The combination of this result with the previously published ATLAS observation of electroweak $Z\left(\nu \overline{\nu}\right)\gamma jj$ production yields an observed (expected) signal significance of 6.3σ (6.6σ). Limits on anomalous quartic gauge boson couplings are obtained in the framework of effective field theory with dimension-8 operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Anticipating gelation and vitrification with medium amplitude parallel superposition (MAPS) rheology and artificial neural networks

Abstract Anticipating qualitative changes in the rheological response of complex fluids (e.g., a gelation or vitrification transition) is an important capability for processing operations that utilize such materials in real-world environments. One class of complex fluids that exhibits distinct rheological states are soft glassy materials such as colloidal gels and clay dispersions, which can be well characterized by the soft glassy rheology (SGR) model. We first solve the model equations for the time-dependent, weakly nonlinear response of the SGR model. With this analytical solution, we show that the weak nonlinearities measured via medium amplitude parallel superposition (MAPS) rheology can be used to anticipate the rheological aging transitions in the linear response of soft glassy materials. This is a rheological version of a technique called structural health monitoring used widely in civil and aerospace engineering. We design and train artificial neural networks (ANNs) that are capable of quickly inferring the parameters of the SGR model from the results of sequential MAPS experiments. The combination of these data-rich experiments and machine learning tools to provide a surrogate for computationally expensive viscoelastic constitutive equations allows for rapid experimental characterization of the rheological state of soft glassy materials. We apply this technique to an aging dispersion of Laponite ® clay particles approaching the gel point and demonstrate that a trained ANN can provide real-time detection of transitions in the nonlinear response well in advance of incipient changes in the linear viscoelastic response of the system.

Lennon, Kyle R. (ORCID:0000000212515461)↗

DOE OSTI2022

Microscale THMC Modeling of Pressure Solution in Salt Rock: Impacts of Geometry and Temperature

Abstract Pressure solution, a mechanism that involves tight coupling between the geometry and thermal-hydro-mechanical-chemical (THMC) processes, plays an important role in diagenesis. In this study, we make the first attempt to conduct microscale THMC modeling to understand and quantify the impacts of geometry and temperature on pressure solution, taking natural salt rock as an example. This modeling capability is achieved by expanding a novel MC code that we developed previously (Hu et al. J Geophys Res: Solid Earth 126:e2021JB023112, 2021) to include temperature effects. We first conduct a simulation of an example that involves a single brine inclusion within a single halite grain and find that the temperature impact is limited for that case. We then extract geometry from an image of a natural salt rock and conduct simulations with different cases: (A) only temperature and no stress, (B) only stress and no temperature, and (C) with both stress and temperature. These different cases result in quite different phenomena. In case A, dissolution and precipitation occur across the entire system due to isolated pore space reaching a localized mass balance between dissolution, precipitation, and diffusion. In case B, intense geometric features (e.g., major asperities, inclusions) in one area undergo stress concentration, thus dominating pressure solution in that area. In case C, pressure solution is spread out at contacting highly stressed geometric features close to the hotter side. We conclude that geometric features dominate stress distribution, thus dominating pressure solution in a natural salt rock that may be affected by the temperature if a sufficient temperature gradient is applied.

58 GEOSCIENCES↗

DOE OSTI2025

Variation in Biomass Yield and Cell Wall Composition in Switchgrass Natural Variants Under Two Nitrogen Regimes

Switchgrass (Panicum virgatum) is a promising lignocellulosic biofuel crop for which biomass and processing quality are important. Inherent plant variability across genotypes and environments challenges uniformity and product quality. In this study, the impact of nitrogen (N) application on switchgrass yield and quality was examined under field conditions using a highly diverse switchgrass panel over a 4-year period at Knoxville, TN. Overall, biomass production was correlated between low (0 kg of added N/ha) and moderate (135 kg of added N/ha) nitrogen treatments, suggesting that the N impact is largely uniform across the genotypes. Nonetheless, high biomass genotypes were identified with high nitrogen-use efficiency ; biomass was congruent or even higher (up to 9-fold) in the low N treatment. Genotypes were also identified with up to 94% nitrogen-remobilization efficiency. Furthermore, nitrogen application appeared to impact lignin content in whole tillers but was neutral to lignin monomer syringyl-to-guaiacyl (S/G) ratio. The same panel grown under natural conditions in Watkinsville, GA, produced significantly more biomass than the Tennessee panel in the first 3 years, but biomass was similar across both sites and treatments in year 4. Top performing genotypes overlapped between sites by 20-37%. There were low correlations in lignin content in whole tillers across the two field sites, but moderate correlations were observed for S/G ratios. The high yielding genotypes from the low N plot identified in this study can be used in breeding programs and management strategies in switchgrass to evade adverse environmental and economic effects.

09 BIOMASS FUELS↗

DOE OSTI2021

Exploring the Spatial Control of Topotactic Phase Transitions Using Vertically Oriented Epitaxial Interfaces

Engineering oxygen vacancy formation and distribution is a powerful route for controlling the oxygen sublattice evolution that affects diverse functional behavior. The controlling of the oxygen vacancy formation process is particularly important for inducing topotactic phase transitions that occur by transformation of the oxygen sublattice. Here we demonstrate an epitaxial nanocomposite approach for exploring the spatial control of topotactic phase transition from a pristine perovskite phase to an oxygen vacancy-ordered brownmillerite (BM) phase in a model oxide La 0.7 Sr 0.3 MnO 3 (LSMO). Incorporating a minority phase NiO in LSMO films creates ultrahigh density of vertically aligned epitaxial interfaces that strongly influence the oxygen vacancy formation and distribution in LSMO. Combined structural characterizations reveal strong interactions between NiO and LSMO across the epitaxial interfaces leading to a topotactic phase transition in LSMO accompanied by significant morphology evolution in NiO. Using the NiO nominal ratio as a single control parameter, we obtain intermediate topotactic nanostructures with distinct distribution of the transformed LSMO-BM phase, which enables systematic tuning of magnetic and electrical transport properties. The use of self-assembled heterostructure interfaces by the epitaxial nanocomposite platform enables more versatile design of topotactic phase structures and correlated functionalities that are sensitive to oxygen vacancies.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Light–Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

Abstract This review provides a comprehensive overview of the progress in light–material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Materials Science↗

DOE OSTI2024

An orphan gene BOOSTER enhances photosynthetic efficiency and plant productivity

Organelle-to-nucleus DNA transfer is an ongoing process playing an important role in the evolution of eukaryotic life. Here, genome-wide association studies (GWAS) of non-photochemical quenching parameters in 743 Populus trichocarpa accessions identified a nuclear-encoded genomic region associated with variation in photosynthesis under fluctuating light. The identified gene, BOOSTER (BSTR), comprises three exons, two with apparent endophytic origin and the third containing a large fragment of plastid-encoded Rubisco large subunit. Higher expression of BSTR facilitated anterograde signaling between nucleus and plastid, which corresponded to enhanced expression of Rubisco, increased photosynthesis, and up to 35% greater plant height and 88% biomass in poplar accessions under field conditions. Overexpression of BSTR in Populus tremula × P. alba achieved up to a 200% in plant height. Similarly, Arabidopsis plants heterologously expressing BSTR gained up to 200% in biomass and up to 50% increase in seed.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

A library of calcium mineral reference spectra recorded by parallel imaging using NEXAFS spectromicroscopy

Calcium minerals are ubiquitous in geology and life chemistry. Understanding the phase and chemical state of calcium minerals is important for numerous processes including materials chemistry, hard tissue biogenesis and geological processes. Photoemission spectroscopies such as near edge X-ray absorption fine structure (NEXAFS) and scanning transmission X-ray microscopy have been instrumental in identifying and characterizing calcium minerals in all these areas. In this work, we have recorded reference spectra for a range of different calcium minerals including a series of calcium carbonates, calcium oxalates and calcium phosphates. While collections of reference spectra for several calcium minerals can be found in the literature, these spectra have been reported in different contexts using a variety of instruments. We, here, report a comprehensive list of references recorded in parallel in a single experiment by imaging an array of calcium minerals using a NEXAFS microscope. We present reference NEXAFS spectra at the calcium L-, carbon K- and oxygen K-edges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Discrete stochastic model of point defect-dislocation interaction for simulating dislocation climb

Dislocation climb is an important high temperature process in metals plasticity, responsible for the phenomena such as creep, swelling, or hardening. Climb is defined by the ability of dislocations to leave their original glide plane by interacting with point defects. As such, dislocation climb is controlled by point defect diffusion/absorption/emission, all of which involve thermal activation. The existing thermodynamically consistent models for climb are generally formulated in a continuum framework, through the definition of effective defect fluxes and climb propensities in response to thermodynamic driving forces. However, the point-wise discrete nature of vacancies (and/or self-interstitials) confers a highly discrete nature to the climb dynamics, which is also strongly affected by elastic forces. The combination of discreteness, thermal activation, and elasticity makes this process too challenging for direct atomistic methods such as molecular dynamics. Here we develop a kinetic Monte Carlo model that captures vacancy generation and transport kinetics acting in conjuction with the evolving elastic fields provided by discrete dislocation dynamics simulations. The two models are coupled via the applied stresses and stress gradients generated by dislocation structures at vacancy locations. Our simulations reveal two surprising results. First that climb is dominated by vacancy emission even when the background vacancy concentration is much higher than the equilibrium one. And, second, that climb velocities might be much faster than otherwise believed when one uses the classical theories of climb. These effects are due to the locality of vacancy-dislocation processes, which are not captured in classical treatments that assume smooth vacancy fluxes and homogeneous concentrations. We apply the method to study elementary climb processes in body-centered cubic iron and furnish climb mobility functions to be used in parametric dislocation dynamics and/or crystal plasticity simulations. Here, we apply the technique to study non-conservative plastic bypass of spherical precipitates by edge dislocations and point out the differences between our discrete approach and existing continuum formulations.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A molecular dynamics study of collisional heat transfer to nanoclusters in the gas phase

Nanoclusters in the gas phase grow by condensation and coagulation, which heat up nanoclusters, creating thermal non-equilibrium with the surrounding gas. The extent of non-equilibrium for nanoclusters is dependent upon the rate of heating relative to the rate of cooling brought about by nanocluster-gas molecule collisions, hence the latter process plays an important role in nanocluster energy evolution during growth. We apply molecular dynamics simulations to investigate heat transfer between metal nanoclusters and gas molecules relevant to high temperature aerosol systems. In analysis, we first define a thermal reemission coefficient (TRC), which is a correction factor for the portion of energy possessed by reemitted gas molecules after collision. Here, the TRC differs from the thermal accommodation coefficient (TAC), which is a correction factor for the maximum possible energy transfer rate from nanoclusters to gas molecules based on the diffusive collision model. We find the TRC is insensitive to nanocluster size but is affected by the nanocluster to gas temperature ratio and the nanocluster to gas atomic mass ratio. Comparison to the traditionally-defined TAC shows that the TAC is insensitive to temperature, a phenomenon that has been widely indicated in literature but not quantitatively explained. We show how the temperature insensitivity of the TAC arises because of the manner in which TRCs vary with both nanocluster and gas temperature, i.e. the manner in which the reemitted gas molecule energy from a surface varies with the temperature of that surface relative to that of the gas. In addition, while calculations ultimately reveal temperature insensitive TACs and justify their continued use in modeling gas-phase heat transfer, we argue that the TRC is more appropriate to calculate a priori in analyzing simulations; it is physically more realistic to first introduce a correction factor solely for the energy of reemitted gas molecules after a collision (as TRCs) instead of a correction factor applying to both the reemission energy and the initial energy (as TACs), as the latter is exactly calculable and independent of nanocluster properties. In line with prior work, for monoatomic gases we find the TAC decreases as the nanocluster to gas atomic mass increases, approaching 0.08 for gold nanoclusters in helium.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

The impact of nickel concentration and stacking fault energy on deformation mechanisms in high-purity austenitic Fe-Cr-Ni alloys

Understanding how composition affects deformation mechanisms in austenitic stainless steels is essential for developing accurate predictive models of stress-induced failures and stress corrosion cracking. Nickel (Ni), an element classified as a critical element, plays a crucial role in these processes. It is important to examine how Ni concentration influences stacking fault energy (SFE) and, consequently, the deformation mechanisms of austenitic stainless steels. However, in commercial stainless steels, the effects of other alloying elements and impurities can obscure Ni's role, complicating efforts to isolate its impact. Here, in this study, we use two high-purity Fe-Cr-Ni alloys to investigate how Ni concentration and SFE interact to alter deformation mechanisms and induce martensitic transformation. By combining in situ synchrotron X-ray diffraction (XRD) tensile testing and post-mortem electron microscopy with density functional theory simulations, we gain precise insights into these phenomena. We find that the Fe18Cr10Ni (wt%) alloy, with its low SFE, exhibits higher stacking fault probability, deformation-induced martensitic transformation, and a lesser increase in dislocation density with plastic strain. In contrast, the Fe18Cr14Ni (wt%) alloy, with its higher SFE, shows enhanced deformation twinning and greater dislocation density with increasing strain. These findings from high-purity ternary alloys provide valuable insights that can guide the search for alternative elements to replace Ni while achieving similar effects on phase stability and deformation behavior.

36 MATERIALS SCIENCE↗