SEARCH · Search NASA

Results for “Derived”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2025

MXene-Derived Potassium-Preintercalated Bilayered Vanadium Oxide Nanostructures for Cathodes in Nonaqueous K-Ion Batteries

Bilayered vanadium oxides (BVOs) are promising cathode materials for beyond-Li-ion batteries due to their tunable chemistries and high theoretical capacities. However, the large size of beyond-Li + ions limits electrochemical cycling and rate capability of BVO electrodes. Recent reports of MXene-derived BVOs with nanoscale flower-like morphology have shown improved electrochemical stability at high rates up to 5C in nonaqueous lithium-ion batteries. Here, we report how morphological stabilization can lead to improved rate capability in potassium-ion batteries (PIBs) through the synthesis and electrochemical characterization of MXene-derived K-preintercalated BVOs (MD-KVOs), which were derived from two V 2 CT x precursor materials prepared using two different etching protocols. We show that the etching conditions affect the surface chemistry of the MXene, which plays a role in the MXene-to-oxide transformation process. MXene derived from a milder etchant transformed into a nanoflower MD-KVO with two-dimensional (2D) nanosheet petals (KVO-DMAE) while a more aggressive etchant produced a MXene that transformed into a MD-KVO with one-dimensional (1D) nanorod morphology (KVO-CMAE). Electrochemical cycling of the produced MD-KVOs after drying at 200 °C under vacuum (KVO-DMAE-200 and KVO-CMAE-200) in PIBs showed that electrochemical stability of MD-KVO at high rates improved through the morphological stabilization of 2D particles combined with the control of interlayer water and K + ion content. Structure refinement of KVO-DMAE-200 further corroborates the behavior observed during K + ion cycling, connecting structural and compositional characteristics to the improved rate capability. This work demonstrates how proper synthetic methodology can cause downstream effects in the control of structure, chemical composition, and morphology of nanostructured layered oxide materials, which is necessary for development of future materials for beyond-Li-ion battery technologies.

25 ENERGY STORAGE↗

DOE OSTI2025

Effect of toolpath in large-format additive manufacturing with bio-derived composites

There has been growing interest in integrating bio-derived composites into Large-format additive manufacturing (LFAM) feedstocks to reduce the use of petroleum-derived materials and reduce the overall carbon footprint of LFAM. However, these materials present unique challenges during manufacturing due to their variability, which can lead to unintended deformations and failures attributable to suboptimal process conditions. While numerical modelling has been extensively employed to simulate numerous manufacturing processes, its application in LFAM with bio-derived composites remains limited. This study addresses this gap by systematically developing a numerical model to simulate the LFAM process using bio-based materials, specifically wood fiber-reinforced polylactic acid (PLA/WF). Experimental investigations were conducted to characterise the thermal and mechanical properties of additively manufactured PLA/WF specimens. Numerical simulations were performed to predict temperature profiles and deformations during LFAM. The effect of varying infill patterns, internal structures, and tool paths on the temperature distribution and deformation of printed parts was explored using the developed model. This article aims to advance the utilisation of bio-derived composites in LFAM systems and provide a comprehensive understanding of the LFAM process. The findings offer valuable insights for optimising process parameters and enhancing the performance of LFAM with bio-based composites.

Large-format additive manufacturing↗

DOE OSTI2023

Sel1-like proteins and peptides are the major Oxalobacter formigenes -derived factors stimulating oxalate transport by human intestinal epithelial cells

Kidney stones (KSs) are very common, excruciating, and associated with tremendous healthcare cost, chronic kidney disease (CKD), and kidney failure (KF). Most KSs are composed of calcium oxalate and small increases in urinary oxalate concentration significantly enhance the stone risk. Oxalate also potentially contributes to CKD progression, kidney disease-associated cardiovascular diseases, and poor renal allograft survival. This emphasizes the urgent need for plasma and urinary oxalate lowering therapies, which can be achieved by enhancing enteric oxalate secretion. We previously identified Oxalobacter formigenes (O. formigenes)-derived factors secreted in its culture-conditioned medium (CM), which stimulate oxalate transport by human intestinal Caco2-BBE (C2) cells and reduce urinary oxalate excretion in hyperoxaluric mice by enhancing colonic oxalate secretion. Given their remarkable therapeutic potential, we now identified Sel1-like proteins as the major O. formigenes-derived secreted factors using mass spectrometry and functional assays. Crystal structures for six proteins were determined to confirm structures and better understand functions. OxBSel1-14-derived small peptides P8 and P9 were identified as the major factors, with P8 + 9 closely recapitulating the CM’s effects, acting through the oxalate transporters SLC26A2 and SLC26A6 and PKA activation. Besides C2 cells, P8 + 9 also stimulate oxalate transport by human ileal and colonic organoids, confirming that they work in human tissues. Finally, P8 and P9 peptides are identified as the major O. formigenes-derived secreted factors and they have significant therapeutic potential for hyperoxalemia, hyperoxaluria, and related disorders, impacting the outcomes of patients suffering from KSs, enteric hyperoxaluria, primary hyperoxaluria, CKD, KF, and renal transplant recipients.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Utilizing coal-derived solid carbon materials towards next-generation smart and multifunction pavements

This project focused on developing an eco-friendly, multifunctional pavement system, called Coal-Derived Carbon Enabled Smart Pavement (CDC-SP), using coal-derived materials. The system utilizes coal-derived pyrolyzed char as a key component to create electrically conductive asphalt concrete for smart pavements that offer self-heating, self-sensing, and self-healing capabilities. These functions are made possible by the conductive properties of coal-char, which enable Ohmic heating for snow and ice deicing, piezoresistivity for self-sensing, and induction heating for self-healing of cracks caused by stress or aging. The team successfully created CDC-SP samples with over 50% coal char composition, demonstrating desirable mechanical properties such as rutting resistance, moisture susceptibility, and cracking resistance. These samples also exhibited strong electrical and thermal conductivity, making them ideal for heating applications. Extensive tests confirmed the pavement’s effectiveness in melting ice and snow and maintaining durability under environmental conditions. The CDC-SP presents a promising approach to integrating U.S. domestic coal resources into infrastructure projects, providing environmental and economic benefits by enhancing pavement performance while utilizing low-cost coal-derived materials. Further research and compliance with industry standards are recommended before commercial scaling.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Quantifying Leaf Chlorophyll Concentration of Sorghum from Hyperspectral Data Using Derivative Calculus and Machine Learning

Leaf chlorophyll concentration (LCC) is an important indicator of plant health, vigor, physiological status, productivity, and nutrient deficiencies. Hyperspectral spectroscopy at leaf level has been widely used to estimate LCC accurately and non-destructively. This study utilized leaf-level hyperspectral data with derivative calculus and machine learning to estimate LCC of sorghum. We calculated fractional derivative (FD) orders starting from 0.2 to 2.0 with 0.2 order increments. Additionally, 43 common vegetation indices (VIs) were calculated from leaf spectral reflectance factor to make comparisons with reflectance-based data. Within the modeling pipeline, three feature selection methods were assessed: Pearson’s correlation coefficient (PCC), partial least squares based variable importance in the projection (VIP), and random forest-based mean decrease impurity (MDI). Finally, we used partial least squares regression (PLSR), random forest regression (RFR), support vector regression (SVR), and extreme learning regression (ELR) to estimate the LCC of sorghum. Results showed that: (1) increasing derivative order can show improved model performance until certain order for reflectance-based analysis; however, it is inconclusive to state that a particular order is optimal for estimating LCC of sorghum; (2) VI-based modeling outperformed derivative augmented reflectance factor-based modeling; (3) mean decrease impurity was found effective in selecting sensitive features from large feature space (reflectance-based analysis), whereas simple Pearson’s correlation coefficient worked better with smaller feature space (VI-based analysis); and (4) SVR outperformed all other models within reflectance-based analysis; alternatively, ELR with VIs from original reflectance yielded slightly better results compared to all other models.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Nonlinear Dynamic Control Derivative Analysis for Aircraft with Application to Transonic Truss-Braced Wing

This paper presents the development of a nonlinear dynamic control derivative estimation method. A nonlinear aerodynamic model is developed to account for the effects of large control surface deflections on aircraft aerodynamic forces and moments. A series of unsteady RANS CFD simulations is performed to simulate the control surface oscillations at various reduced frequencies. The time-domain data are transformed into the frequency-domain data by a Fourier series analysis. Transfer functions of the dynamic control derivatives are then estimated by a frequency-domain regression. The method is applied to the Transonic Truss-Braced Wing (TTBW) to estimate the dynamic control derivatives for the elevator, aileron, and rudder.

Aircraft Control Derivatives↗

DOE OSTI2021

Deterministic symbolic regression with derivative information: General methodology and application to equations of state

Symbolic regression methods simultaneously determine the model functional form and the regression parameter values by generating expression trees. Symbolic regression can capture the complexity of real–world phenomena but the use of deterministic optimization for symbolic regression has been limited due to the complexity of the search space of existing formulations. Herein we present a novel deterministic mixed–integer nonlinear programming formulation for symbolic regression that incorporates derivative constraints through auxiliary expression trees. By applying the chain rule to mathematical operations, binary expression trees are capable of representing the calculation of first and second derivatives. We apply this formulation to illustrative examples using derivative information to show increased model discrimination capability. In addition, we perform a case study of a thermodynamic equation of state to gain insight on valid functional forms with thermodynamics–based constraints on the first and second derivatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

The strip method for shape derivatives

Abstract A major challenge in shape optimization is the coupling of finite element method (FEM) codes in a way that facilitates efficient computation of shape derivatives. This is particularly difficult with multiphysics problems involving legacy codes, where the costs of implementing and maintaining shape derivative capabilities are prohibitive. The volume and boundary methods are two approaches to computing shape derivatives. Each has a major drawback: the boundary method is less accurate, while the volume method is more invasive to the FEM code. We introduce the strip method , which computes shape derivatives on a strip adjacent to the boundary. The strip method makes code coupling simple. Like the boundary method, it queries the state and adjoint solutions at quadrature nodes, but requires no knowledge of the FEM code implementations. At the same time, it exhibits the higher accuracy of the volume method. As an added benefit, its computational complexity is comparable to that of the boundary method, that is, it is faster than the volume method. We illustrate the benefits of the strip method with numerical examples.

Hardesty, Sean↗

DOE OSTI2022

Four-derivative corrections to minimal gauged supergravity in five dimensions

We study four-derivative corrections to pure N = 2, D = 5 gauged supergravity. In particular, we find that, up to field redefinitions, there is a single four-derivative superinvariant that one can add to the action, up to factors of the two-derivative action. Consequently, this selects out a unique set of coefficients for the four-derivative corrections. We confirm these coefficients (in the ungauged limit) on the BMPV solution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Derivation of K-matrix reaction theory in a discrete basis formalism

The usual derivations of the S and K matrices for two-particle reactions proceed through the Lippmann–Schwinger equation with formal definitions of the incoming and outgoing scattering states. Here we present a simpler alternative derivation that is carried out completely in the Hamiltonian representation, using a discrete basis of configurations for the scattering channels as well as the quasi-bound configurations of the combined fragments. We use matrix algebra to derive an explicit expression for the K matrix in terms of the Hamiltonian of the internal states of the compound system and the coupling between the channels and the internal states. The formula for the K matrix includes explicitly a real dispersive shift matrix to the internal Hamiltonian that is easily computed in the formalism. That expression is applied to derive the usual form of the S matrix as a sum over poles in the complex energy plane. Some extensions and limitations of the discrete-basis Hamiltonian formalism are discussed in the concluding remarks and in the Appendix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Subtle penetrant size effects on separation of carbon molecular sieve membranes derived from $\mathrm{6FDA:BPDA}$-$\mathrm{DAM}$ polyimide

Economically scalable carbon molecular sieve (CMS) hollow fiber membranes rely upon a tunable bimodal pore morphology to separate gas pairs using angstrom-level size discrimination. Freshly formed CMS membranes experience self-retarding physical aging, reflected by permeance losses and selectivity gains that stabilize over short times compared to the lifetime of the membrane. Self-retarding morphology rearrangements are of special interest here due to tightening of the largest size range of ultramicropores, thereby causing aging for polyimide-derived CMS. We report effects of such aging for two A/B penetrant pairs, C 3 H 6 /C 3 H 8 and CO 2 /CH 4 . These two pairs not only have different average sizes, $\overline{d}_{A/B}$, but also different size differences,Δd A/B , between the members in each pair. We focus primarily on the C 3 H 6 /C 3 H 8 pair, which is the most difficult of the two pairs to separate, and use some CO 2 /CH 4 results as a comparison case. We study CMS derived from 6FDA:BPDA-DAM (1:1) polyimide by pyrolysis at 550 °C, 600 °C and 650 °C. Here we suggest conditions and physical causes that expedite, retard or even suppress the aging process within CMS membranes. Finally, we suggest how analysis of CMS derived from other precursors and other penetrant pairs can be generalized by understanding the results for the 6FDA:BPDA-DAM (1:1) polyimide derived CMS.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems using state measurements. One approach, known as Sparse Identification of Nonlinear Dynamics (SINDy), assumes the dynamics are sparse within a predetermined basis in the states and finds the expansion coefficients through linear regression with sparsity constraints. This approach requires an accurate estimation of the state time derivatives, which is not necessarily possible in the high-noise regime without additional constraints. We present an approach called Derivative-based SINDy (DSINDy) that combines two novel methods to improve ODE recovery at high-noise levels. First, we denoise the state variables by applying a projection operator that leverages the assumed basis for the system dynamics. Second, we use a second order cone program (SOCP) to find the derivative and governing equations simultaneously. We derive theoretical results for the projection-based denoising step, which allow us to estimate the values of hyperparameters used in the SOCP formulation. This underlying theory helps limit the number of required user-specified parameters. Finally, we present results demonstrating that our approach leads to improved system recovery for the Van der Pol oscillator, the Duffing oscillator, the Rössler attractor, and the Lorenz 96 model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Life-cycle energy use and greenhouse gas emissions of palm fatty acid distillate derived renewable diesel

This study aims to quantify life-cycle fossil energy use and greenhouse gas (GHG) emissions for palm fatty acid distillate (PFAD) derived renewable diesel (RD) taking into consideration different feedstock classifications that are applicable to PFAD (residue, byproduct, or coproduct), and incorporating updated data for key processes. Under the three classifications, the PFAD to RD pathway was modeled using the Greenhouse gases, Regulated Emissions, and Energy Use in Technologies (GREET®) model. PFAD-derived RD could reduce fossil energy consumption by 77%–88%, relative to petroleum diesel. GHG emissions are very sensitive to PFAD classification and coproduct handling methods. Considering the production of palm oil and PFAD and economic value, we maintain that PFAD should be treated as a byproduct in palm oil refineries. With this treatment, PFAD-derived RD could achieve 84% GHG emissions reductions, compared to the emissions of petroleum diesel. We also employed a substitution method to address the substitution of PFAD by other materials in the marketplace. Compared to coproduct allocation results, we found substituting PFAD by tallow, soy oil, barley, and canola oil results in lower GHG emissions. Due to high induced land-use change emissions associated with palm farming, if PFAD is treated as a coproduct with refined palm oil, PFAD-derived RD may not deliver GHG reductions. A sensitivity analysis identified key parameters such as palm fruit yield, oil extraction efficiency in oil mills, and energy use intensity for RD production affects LCA results significantly; future efforts to improve these parameters could result in further GHG reductions.

09 BIOMASS FUELS↗

DOE OSTI2021

Sorafenib derivatives-functionalized gold nanoparticles confer protection against tumor angiogenesis and proliferation via suppression of EGFR and VEGFR-2

Sorafenib is a multi-kinase inhibitor that has been highlighted as a tumor suppressor due to its anti-proliferative and anti-angiogenic properties, whereas the clinical application of Sorafenib is restricted by the side effects it may cause. The past decade has witnessed the development of a series of sorafenib derivatives to improve the clinical performance of sorafenib. Gold nanoparticles (AuNPs) have been widely utilized in drug delivery systems due to their unique properties, including biocompatible nature, simple preparation, and easy surface modification. Herein, this study is aimed to investigate the anti-tumor effects of new sorafenib derivatives-capped gold nanoparticles (AuNPs-New Sor) in tumor formation and metastasis as well as the underlying mechanisms. Initially, new sorafenib derivatives were constructed and combined with AuNPs to form AuNPs-New Sor, and the properties of synthesized AuNPs-New Sor were identified in a mouse model of tumorigenesis. The effect of AuNPs-New Sor on tumor vascular normalization was investigated by assessing vascular permeability and perfusion rate. Next, we evaluated the effect of AuNPs-New Sor on migration and viability of tumor cells and human umbilical vein endothelial cells (HUVECs) as well as on HUVEC angiogenesis in vitro. A melanoma mouse model was further established for in vivo substantiation of the anti-tumor effect of AuNPs-New Sor. According to the results, AuNPs could deliver new sorafenib derivatives into tumor tissues and downregulate the expression of epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor-2 (VEGFR-2), thereby suppressing tumor migration, EMT, and angiogenesis in vitro. In addition, AuNPs-New Sor displayed competitive anti-tumor activities in vivo. Taken together, AuNPs-New Sor may attenuate tumor development and angiogenesis through downregulation of EGFR and VEGFR-2.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

MCL1 inhibition enhances the efficacy of docetaxel against airway-derived squamous cell carcinoma cells

Highlights: • Authentic squamous cell carcinoma (SqCC) cell lines of the lung are sparse. • HARA lung SqCC cells depend highly on MCL1 for survival in vitro and in vivo. • MCL1-silenced HARA cells decline in number upon docetaxel (DTX) exposure. • High MCL1 mRNA expression is linked with shorter survival in lung SqCC patients. • MCL1 depletion + DTX is highly effective against Detroit 562 pharyngeal SqCC cells. MCL1 is an anti-apoptotic BCL2 family member that is often overexpressed in various malignant tumors. However, few reports have described the role of MCL1 in squamous cell carcinoma (SqCC) derived from airways including the lung. In this study, we examined whether MCL1 could be a novel druggable target for airway-derived SqCC, for which effective molecular targeted drugs are unavailable. We searched the Kaplan–Meier Plotter database and found that high MCL1 mRNA expression was significantly associated with shorter survival in patients with lower airway (lung) or upper airway (head and neck) derived SqCC. We also explored the Expression Atlas database and learned that authentic lung SqCC cell lines expressing both TP63 and KRT5 mRNA were extremely sparse among the publicly available “lung SqCC cell lines”, with an exception being HARA cells. HARA cells were highly dependent on MCL1 for survival, and MCL1-depleted cells were not able to grow, and even declined in number, upon docetaxel (DTX) exposure in vitro and in vivo. Similar in vitro experimental findings, including those in a 3D culture model, were also obtained using Detroit 562 pharyngeal SqCC cells. These findings suggested that combined treatment with MCL1 silencing plus DTX appears highly effective against airway-derived SqCC.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Metabolism of Syringyl Lignin-Derived Compounds in Pseudomonas putida Enables Convergent Production of 2-Pyrone-4,6-Dicarboxylic Acid

Valorization of lignin, an abundant component of plant cell walls, is critical to enabling the lignocellulosic bioeconomy. Biological funneling using microbial biocatalysts has emerged as an attractive approach to convert complex mixtures of lignin depolymerization products to value-added compounds. Ideally, biocatalysts would convert aromatic compounds derived from the three canonical types of lignin: syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H). Pseudomonas putida KT2440 (hereafter KT2440) has been developed as a biocatalyst owing in part to its native catabolic capabilities but is not known to catabolize S-type lignin-derived compounds. Here, we demonstrate that syringate, a common S-type lignin-derived compound, is utilized by KT2440 only in the presence of another energy source or when vanAB was overexpressed, as syringate was found to be O-demethylated to gallate by VanAB, a two-component monooxygenase, and further catabolized via extradiol cleavage. Unexpectedly, the specificity (kcat/KM) of VanAB for syringate was within 25% that for vanillate and O-demethylation of both substrates was well-coupled to O2 consumption. However, the native KT2440 gallate-cleaving dioxygenase, GalA, was potently inactivated by 3-O-methylgallate. To engineer a biocatalyst to simultaneously convert S-, G-, and H-type monomers, we therefore employed VanAB from Pseudomonas sp. HR199, which has lower activity for 3MGA, and LigAB, an extradiol dioxygenase able to cleave protocatechuate and 3-O-methylgallate. This strain converted 93% of a mixture of lignin monomers to 2-pyrone-4,6-dicarboxylate, a promising bio-based chemical. Overall, this study elucidates a native pathway in KT2440 for catabolizing S-type lignin-derived compounds and demonstrates the potential of this robust chassis for lignin valorization.

2-pyrone-4,6-dicarboxylic acid↗

DOE OSTI2021

Controlling selectivity of modular microbial biosynthesis of butyryl-CoA-derived designer esters

Short-chain esters have broad utility as flavors, fragrances, solvents, and biofuels. Controlling selectivity of ester microbial biosynthesis has been an outstanding metabolic engineering problem. In this study, we enabled the de novo fermentative microbial biosynthesis of butyryl-CoA-derived designer esters (e.g., butyl acetate, ethyl butyrate, butyl butyrate) in Escherichia coli with controllable selectivity. Using the modular design principles, we generated the butyryl-CoA-derived ester pathways as exchangeable production modules compatible with an engineered chassis cell for anaerobic production of designer esters. We designed these modules derived from an acyl-CoA submodule (e.g., acetyl-CoA, butyryl-CoA), an alcohol submodule (e.g., ethanol, butanol), a cofactor regeneration submodule (e.g., NADH), and an alcohol acetyltransferase (AAT) submodule (e.g., ATF1, SAAT) for rapid module construction and optimization by manipulating replication (e.g., plasmid copy number), transcription (e.g., promoters), translation (e.g., codon optimization), pathway enzymes, and pathway induction conditions. To further enhance production of designer esters with high selectivity, we systematically screened various strategies of protein solubilization using protein fusion tags and chaperones to improve the soluble expression of multiple pathway enzymes. Finally, our engineered ester-producing strains could achieve 19-fold increase in butyl acetate production (0.64 g/L, 96% selectivity), 6-fold increase in ethyl butyrate production (0.41 g/L, 86% selectivity), and 13-fold increase in butyl butyrate production (0.45 g/L, 54% selectivity) as compared to the initial strains. Altogether, this study presented a generalizable framework to engineer modular microbial platforms for anaerobic production of butyryl-CoA-derived designer esters from renewable feedstocks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Synthesis and Properties of Bulk Mg 3 WN 4 in a Wurtzite-Derived Structure

Experimental synthesis of theoretically predicted materials with controlled elemental coordination environments can lead to the realization of useful properties, such as facile ion transport or ferroelectric switching. Among such materials are ternary nitrides in the Mg−W−N composition space, where several stable and metastable compounds have been predicted and synthesized recently in bulk and film forms. Here, we report for the first time on the bulk synthesis of Mg 3 WN 4 in a wurtzite-derived crystal structure via a solid-state metathesis reaction. In situ synchrotron powder X-ray diffraction shows how the ion exchange proceeds from Li 6 WN 4 + MgCl 2 precursors to Mg 3 WN 4 + LiCl products, with the reaction starting slowly near 380 °C and completing by 600 °C, including the presence of a competing disordered rocksalt-derived phase (Mg,W)N above 440 °C. The follow-up ex situ powder synthesis at 400 °C for 0.5 h with 10% excess MgCl 2 reveals the cation-ordered nature of the wurtzite-derived Mg 3 WN 4 structure with polar symmetry confirmed by second-harmonic generation measurements. Optical absorption spectra, chemical composition analysis, and electron microscopy imaging suggest that bulk Mg 3 WN 4 obtained via metathesis reaction is prone to defect formation. Overall, this study shows that selective ex situ synthesis of the phase-pure ternary nitrides, informed by in situ measurements, is possible by carefully controlling the thermal budget of the reaction and paves the way toward property characterization of the Mg 3 WN 4 wurtzite-derived material.

36 MATERIALS SCIENCE↗