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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data mining and computational screening of Rashba-Dresselhaus splitting and optoelectronic properties in two-dimensional perovskite materials

Recent developments highlighting the promise of two-dimensional perovskites have vastly increased the compositional search space in the perovskite family. This presents a great opportunity for the realization of highly performant devices and practical challenges associated with the identification of candidate materials. High-fidelity computational screening offers great value in this regard. In this study, we carry out a multiscale computational workflow, generating a dataset of two-dimensional perovskites in the Dion-Jacobson and Ruddlesden-Popper phases. Our dataset comprises ten B-site cations, four halogens, and over 20 organic cations across over 2000 materials. We compute electronic properties, thermoelectric performance, and numerous geometric characteristics. Furthermore, we introduce a framework for the high-throughput computation of Rashba-Dresselhaus splitting. Finally, we use this dataset to train machine learning models for the accurate prediction of band gaps, candidate Rashba-Dresselhaus materials, and partial charges. The work presented herein can aid future investigations of two-dimensional perovskites with targeted applications in mind.

14 SOLAR ENERGY↗
DOE OSTI2025

Meaningful Household Savings: Best Practices for Achieving Equitable Solar Development

The Meaningful Household Savings Community of Practice—and this report—focuses on electricity bill savings, other household savings, wealth-building opportunities, and other benefits such as tenant services provided to residents in master-metered buildings. For this report, the project team collected information about ways meaningful household savings have been defined; researched best practices to define, achieve, and quantify meaningful household savings; and identified strategies to scale the adoption and implementation of successful methods.

14 SOLAR ENERGY↗
DOE OSTI2022

Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks

Tabulated chemistry models are widely used to simulate large-scale turbulent fires in applications including energy generation and fire safety. Tabulation via piecewise Cartesian interpolation suffers from the curse-of-dimensionality, leading to a prohibitive exponential growth in parameters and memory usage as more dimensions are considered. Artificial neural networks (ANNs) have attracted attention for constructing surrogates for chemistry models due to their ability to perform high-dimensional approximation. However, due to well-known pathologies regarding the realization of suboptimal local minima during training, in practice they do not converge and provide unreliable accuracy. Partition of unity networks (POUnets) are a recently introduced family of ANNs which preserve notions of convergence while performing high-dimensional approximation, discovering a mesh-free partition of space which may be used to perform optimal polynomial approximation. In this work, we assess their performance with respect to accuracy and model complexity in reconstructing unstructured flamelet data representative of nonadiabatic pool fire models. Our results show that POUnets can provide the desirable accuracy of classical spline-based interpolants with the low memory footprint of traditional ANNs while converging faster to significantly lower errors than ANNs. For example, we observe POUnets obtaining target accuracies in two dimensions with 40 to 50 times less memory and roughly double the compression in three dimensions. We also address the practical matter of efficiently training accurate POUnets by studying convergence over key hyperparameters, the impact of partition/basis formulation, and the sensitivity to initialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Efficient and Flexible Hierarchical Data Layouts for a Unified Encoding of Scalar Field Precision and Resolution

To address the problem of ever-growing scientific data sizes making data movement a major hindrance to analysis, we introduce a novel encoding for scalar fields: a unified tree of resolution and precision, specifically constructed so that valid cuts correspond to sensible approximations of the original field in the precision-resolution space. Furthermore, we introduce a highly flexible encoding of such trees that forms a parameterized family of data hierarchies. We discuss how different parameter choices lead to different trade-offs in practice, and show how specific choices result in known data representation schemes such as zfp[52], idx[58], and jpeg2000 [76]. Lastly, we provide system-level details and empirical evidence on how such hierarchies facilitate common approximate queries with minimal data movement and time, using real-world data sets ranging from a few gigabytes to nearly a terabyte in size. Experiments suggest that our new strategy of combining reductions in resolution and precision is competitive with state-of-the-art compression techniques with respect to data quality, while being significantly more flexible and orders of magnitude faster, and requiring significantly reduced resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Integrating Health and Energy Efficiency in Multi-Family Buildings

The intersection between health and the built environment has long been known. Since the 18 th century, public health officials have been targeting building issues, such as crowding, poor sanitation, and inadequate ventilation in efforts to reduce infectious diseases and fire hazards. More recently, federal agencies, such as the U.S. Environmental Protection Agency (EPA), the Centers for Disease Control and Prevention, HUD, and the DOE have been working to reduce or eliminate indoor building factors that are known to have adverse health impacts on Americans, including reducing lead in housing and indoor air pollution that causes respiratory disease, and ensuring access to adequate heating, cooling, and moisture control. PNNL, in support of FEMP’s HBI, undertook a review of literature and existing best practices to identify current activities and research on the intersection between traditional energy-efficiency measures and occupant health within multi-family buildings. While the HBI methodology has focused on traditional office building spaces, it is now expanding into additional building use types. This overview explores some of the most impactful resources to help property owners and managers understand more about multi-family residential buildings that are both healthy and energy efficient. The federal government provides direct oversight and operation across several types of multi-family residential housing, including dormitories, barracks, and senior community living centers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Demonstration of μCHP in Light Commercial Hot Water Applications

Internal combustion engine driven combined heat and power (CHP) systems produce power while the waste heat is recovered and used for another purpose. For µCHP systems (less than 50kWe output) overall efficiencies can reach over 90% for products currently on the market throughout the world. On a fuel basis this offers an advantage over using grid-based power and another fuel for heat. Additionally, the cost of natural gas on an energy unit basis is significantly less expensive than electric power. This difference can lead to substantial savings for the end user of a CHP system. In some parts of the world, particularly Germany and Japan, µCHP has become a common part of the heat and distributed generation equipment mix. Market analysis conducted in 2012 showed that in North America there is potential of a 5,300 units per year market for µCHP, resulting in an annual energy savings of approximately 13.5 TBtu and more than $84 million in annual customer savings. However, µCHP still has not seen much market penetration in North America. This study helps to identify some of the reasons why, address roadblocks that still need to be overcome and provide experience to established best practices. Nine commercial sites were initially identified (fitness club, surgical center, senior community, resort and spa, commercial laundry, two multi-family housing, restaurant and manufacturing facility). Systems from two different manufacturers were installed at five sites total, but due to unforeseen circumstances, only three of those sites were finally commissioned: test data were collected by Oak Ridge National Laboratory. While not all systems were installed as intended, the project resulted in the following key findings: Micro combined heat and power is an unfamiliar technology for building owners and plumbing and electrical contractors that serve the buildings most suited for µCHP. Manufacturers will need to be aggressive in providing training and providing broad support to successfully bring the technology to market.; The proper integration of µCHP into other building systems is the most critical part of a successful installation. Manufacturers will need to be able to provide the expertise to train, advise and support the mechanical contractors during the design and installation of the heat integration system.; Regulations governing µCHP varies across the country. There are a few UL standards (UL 2200 and UL 1741) that apply nationally. Emissions are governed by EPA except in California where the California Air Resources Board (CARB) has established their own standard. Requirements that dictate installation and interconnection are dependent on local building codes and local utility processes and requirements. Some out of date building codes do not offer clear guidance for these requirements, leading to confusion. This makes developing training and determining broadly applicable best practices difficult.; Installation costs of µCHP are a key factor in making an installation successful. It is critical that these costs and all national, state and local regulations be understood and accounted for by all parties involved in the installation before a project is undertaken.; A robust customer service organization is important to meet the needs of the customers. These systems require annual maintenance and service and local capability is needed to keep costs inline.

03 NATURAL GAS↗
DOE OSTI2020

Target Detection via Cognitive Radars Using Change-Point Detection, Learning, and Adaptation

Many radar detection algorithms that assume a stationary environment (clutter) have been proposed and analyzed over the years. However, in practice, changes in the nonstationary environment can perturb the parameters of the clutter distribution, or even alter the clutter distribution family, which can greatly deteriorate the target detection capability. To avoid such potential performance degradation, cognitive radar systems are envisioned which are required to rapidly realize the nonstationarity, accurately learn the new characteristics of the environments, and adaptively update the detector. In this paper, aiming to develop a fully cognitive radar for target detection in nonstationary environments, we propose a unifying framework that integrates (i) change-point detection of clutter distributions by using a data-driven cumulative sum (CUSUM) algorithm and its extended version, (ii) learning/identification of clutter distribution by applying sparse theory and kernel density estimation methods, and (iii) adaptive target detection by automatically modifying the likelihood-ratio test and corresponding detection threshold. Further, with extensive numerical examples, we demonstrate the achieved improvements in detection performance due to the proposed framework in comparison to a nonadaptive case, an adaptive matched filter (AMF) method, and the clairvoyant case. Herein, we also use Wilcoxon rank-sum tests to evaluate the statistical significance of the performance improvements

42 ENGINEERING↗
DOE OSTI2025

Performance of wave function and Green's function methods for non-equilibrium many-body dynamics

Theoretical descriptions of the non-equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on the truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In this work, we select representative cases of each of the methods and address how these complementary approaches capture the dynamics driven by intense field perturbations to non-equilibrium states. Under strong driving, the systems are characterized by strong entanglement of the single-particle density matrix and natural populations approaching those of a strongly interacting equilibrium system. We generate a representative set of results that are numerically exact and form a basis for a critical comparison of the distinct families of methods. We demonstrate that the compressed formulation based on similarity-transformed Hamiltonians (coupled-cluster approach) is practically exact in weak fields and, hence, weakly or moderately correlated systems. Coupled cluster, however, struggles for strong driving fields, under which the system exhibits strongly correlated behavior, as measured by the von Neumann entropy of the single-particle density matrix. The dynamics predicted by Green's functions in the (widely popular) G W approximation are less accurate, but improve significantly upon the mean-field results in the strongly driven regime. Published by the American Physical Society 2025

Reeves, Cian C. (ORCID:0009000642581845)↗
DOE OSTI2022

tapir: A tool for topologies, amplitudes, partial fraction decomposition and input for reductions

The demand for precision predictions in the field of high energy physics has dramatically increased over recent years. Experiments conducted at the LHC, as well as precision measurements at the intensity frontier such as Belle II require equally precise theoretical predictions to make full use of the acquired data. To match the experimental precision, second-, third- and, for certain quantities, even higher-order calculations in perturbative quantum field theory are required. To facilitate such calculations, computer software automating as many steps as possible is required. Yet, each calculation poses different challenges and thus, a high level of configurability is required. In this context we present tapir: a tool for identification, manipulation and minimization of Feynman integral families. It is designed to integrate in toolchains based on the computer algebra system FORM, the use of which is common practice in the field. tapir can be used to reduce the complexity of multi-loop problems with cut-filters, topology mapping, partial fraction decomposition and alike. Program Title:tapir CPC Library link to program files:https://doi.org/10.17632/ptc9t46xyn.1 Developer's repository link:https://gitlab.com/tapir-devs/tapir Licensing provisions: GPLv3 Programming language:python 3, C++ Nature of problem: Multi-loop computations require the automatization of a large number of different tasks related to Feynman integral topologies. Among them are the identification and minimization of integral topologies, partial fraction decomposition of topologies in the case of linearly dependent propagators as well as mapping scalar products of loop momenta to scalar functions. Solution method: The minimization of topologies is performed by comparison of their respective Nickel indices [1], even further minimization utilizes Pak's algorithm [2]. To efficiently map scalar products of loop momenta to scalar functions FORM [3] code is generated. Additional comments including restrictions and unusual features: Minimization based on Pak's algorithm slows down for many lines and scales. A coarser minimization using the Nickel indices, however, is still possible. [1]B. Nickel, D. Meiron, G.A.J. Baker, Compilation of 2-pt and 4-pt graphs for continuous spin model, Report, University of Guelph, 1977.[2]A. Pak, J. Phys. Conf. Ser. 368 (2012) 012049, https://doi.org/10.1088/1742-6596/368/1/012049, arXiv:1111.0868.[3]B. Ruijl, T. Ueda, J. Vermaseren, FORM version 4.2, arXiv:1707.06453, 7 2017.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Multi-stage preconditioners for thermal–compositional–reactive flow in porous media

We present a family of multi-stage preconditioners for coupled thermal-compositional-reactive reservoir simulation problems. The most common preconditioner used in industrial practice, the Constrained Pressure Residual (CPR) method, was designed for isothermal models and does not offer a specific strategy for the energy equation. For thermal simulations, inadequate treatment of the temperature unknown can cause severe conver-gence degradation. When strong thermal diffusion is present, the energy equation exhibits significant elliptic behavior that cannot be accurately corrected by CPR's second stage. In this work, we use Schur-complement decompositions to extract a temperature subsystem and apply an Algebraic MultiGrid (AMG) approximation as an additional preconditioning stage to improve the treatment of the energy equation. We present results for several two-dimensional hot air injection problems using an extra heavy oil, including challenging reactive In-Situ Combustion (ISC) cases. We show improved performance and robustness across different thermal regimes, from advection dominated (high Péclet number) to diffusion dominated (low Péclet number). The number of linear iterations is reduced by 40–85% compared to standard CPR for both homogeneous and heterogeneous media, and the new methods exhibit almost no sensitivity to the thermal regime.

42 ENGINEERING↗
DOE OSTI2023

Practical Multi-Cycle Refueling Simulation of Stable Salt Reactors Based on REBUS Depletion Calculation

A Python software tool ReloadPy has been developed to assistant in formulating online refueling strategies for a family of stable salt reactors. ReloadPy wraps over the legacy fast reactor analysis codes REBUS, DIF3D, and PERSENT. These codes are used to perform single cycle depletion analysis and calculate reactivity worth and power density. ReloadPy determines a refueling assembly position to achieve the user-specified primary objective while satisfying constraints on various performance parameters such as the maximum power density, the maximum reactivity worth of reloaded assembly, and the minimum cycle length. Various capabilities of prescribing refueling sequence or a range of candidate refueling positions and restarting a previous simulation with altered options are implemented to reduce the required user’s efforts to investigate different refueling strategies. This report presents the computational models and methods and also serves as a user guide. Long-term simulation capabilities with different refueling strategies are demonstrated by a series of sample SSR refueling calculations with two-dimensional surrogate core models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗
DOE OSTI2023

A publicly available PyTorch-$\mathrm{ABAQUS}$ $\mathrm{UMAT}$ deep-learning framework for level-set plasticity

Here this paper introduces a publicly available PyTorch-ABAQUS deep-learning framework of a family of plasticity models where the yield surface is implicitly represented by a scalar-valued function. In particular, our focus is to introduce a practical framework that can be deployed for engineering analysis that employs a user-defined material subroutine (UMAT/VUMAT) for ABAQUS, which is written in FORTRAN. To accomplish this task while leveraging the back-propagation learning algorithm to speed up the neural-network training, we introduce an interface code where the weights and biases of the trained neural networks obtained via the PyTorch library can be automatically converted into a generic FORTRAN code that can be a part of the UMAT/VUMAT algorithm. To enable third-party validation, we purposely make all the data sets, source code used to train the neural-network-based constitutive models, and the trained models available in a public repository. Furthermore, the practicality of the workflow is then further tested on a dataset for anisotropic yield function to showcase the extensibility of the proposed framework. A number of representative numerical experiments are used to examine the accuracy, robustness and reproducibility of the results generated by the neural network models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Orthogonal luminescence lifetime encoding by intermetallic energy transfer in heterometallic rare-earth MOFs

Lifetime-encoded materials are particularly attractive as optical tags, however examples are rare and hindered in practical application by complex interrogation methods. Here, we demonstrate a design strategy towards multiplexed, lifetime-encoded tags via engineering intermetallic energy transfer in a family of heterometallic rare-earth metal-organic frameworks (MOFs). The MOFs are derived from a combination of a high-energy donor (Eu), a low-energy acceptor (Yb) and an optically inactive ion (Gd) with the 1,2,4,5 tetrakis(4-carboxyphenyl) benzene (TCPB) organic linker. Precise manipulation of the luminescence decay dynamics over a wide microsecond regime is achieved via control over metal distribution in these systems. Demonstration of this platform’s relevance as a tag is attained via a dynamic double encoding method that uses the braille alphabet, and by incorporation into photocurable inks patterned on glass and interrogated via digital high-speed imaging. This study reveals true orthogonality in encoding using independently variable lifetime and composition, and highlights the utility of this design strategy, combining facile synthesis and interrogation with complex optical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Recent Progress on Dominant Sulfide‐Type Solid‐State Na Superionic Conductors for Solid‐State Sodium Batteries

Abstract Over the past decade, solid‐state batteries have garnered significant attentions due to their potentials to deliver high energy density and excellent safety. Considering the abundant sodium (Na) resources in contrast to lithium (Li), the development of sodium‐based batteries has become increasingly appealing. Sulfide‐based superionic conductors are widely considered as promising solid eletcrolytes (SEs) in solid‐state Na batteries due to the features of high ionic conductivity and cold‐press densification. In recent years, tremendous efforts have been made to investigate sulfide‐based Na‐ion conductors on their synthesis, compositions, conductivity, and the feasibility in batteries. However, there are still several challenges to overcome for their practical applications in high performance solid‐state Na batteries. This article provides a comprehensive update on the synthesis, structure, and properties of three dominant sulfide‐based Na‐ion conductors (Na 3 PS 4 , Na 3 SbS 4 , and Na 11 Sn 2 PS 12 ), and their families that have a variety of anion and cation doping. Additionally, the interface stability of these sulfide electrolytes toward the anode is reviewed, as well as the electrochemical performance of solid‐state Na batteries based on different types of cathode materials (metal sulfides, oxides, and organics). Finally, the perspective and outlook for the development and practical utilization of sulfide‐based SE in solid‐state batteries are discussed.

Guo, Xiaolin↗
DOE OSTI2020

Green synthesis of reduced Ti 3 C 2 T x MXene nanosheets with enhanced conductivity, oxidation stability, and SERS activity

Transition metal carbides (MXenes) are an emerging family of highly conductive two-dimensional materials with additional functional properties introduced by surface terminations. Further modification of the surface terminations makes MXenes even more appealing for practical applications. Herein, we report a facile and environmentally benign synthesis of reduced Ti 3 C 2 T x MXene (r-Ti 3 C 2 T x ) via a simple treatment with L-ascorbic acid at room temperature. r-Ti 3 C 2 T x shows a six-fold increase in electrical conductivity, from 471 ± 49 for regular Ti 3 C 2 T x to 2819 ± 306 S m -1 for the reduced version. Additionally, we show an enhanced oxidation stability of r-Ti 3 C 2 T x as compared to regular Ti 3 C 2 T x . An examination of the surface-enhanced Raman scattering (SERS) activity reveals that the SERS enhancement factor of r-Ti 3 C 2 T x is an order of magnitude higher than that of regular Ti 3 C 2 T x . The improved SERS activity of r-Ti 3 C 2 T x is attributed to the charge transfer interaction between the MXene surface and probe molecules, re-enforced by an increased electronic density of states (DOS) at the Fermi level of r-Ti 3 C 2 T x . The findings of this study suggest that reduced MXene could be a superior choice over regular MXene, especially for the applications that employ high electronic conductivity, such as electrode materials for batteries and supercapacitors, photodetectors, and SERS-based sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Controlling Molecular Structure and Spin with Multiconfigurational Quantum Chemistry (Final Technical Report)

For many first-row transition metal complexes, structure-property relationships can be obtained from high-level molecular geometry optimizations and subsequent electronic structure studies. The project funded under this award utilized newly implemented fully internally contracted (FIC) nuclear gradients for extended multi-state (XMS) complete active space second-order multireference perturbation theory (CASPT2) to explore geometry changes in first-row transition metal coordination complexes. At the start of the project, only one full geometry optimization using FIC-CASPT2 analytical gradients had been reported (J. Chem. Theory Comput., 2016, 12 (8), 3781), and many open-questions regarding the performance and achievable accuracy in applying such computations to larger complexes persisted. Key deliverables in the report include the implementation of the numerical Hessian and subsequent vibrational analysis in the BAGEL program package. This includes both full Hessian vibrational analysis (FHVA) and a partial Hessian vibrational analysis (PHVA). The latter of which allows us to reduce the significant cost of computing the vibrational frequencies in a large molecule by focusing on the modes of highest interest. The gradient code also proved useful in the development of an approach to improve the Hubbard-U correction by removing bias in predicting spin-splitting in Fe(II) complexes via plane-wave density functional theory (DFT). Finally, we showed for three families of complexes (spin-crossover (SCO) complexes, metallocorroles complexes, and those with metal-metal bonds) that CASPT2 can result in good molecular geometries and established best practices in undertaking this work. We are now using this approach in collaborative projects with experimental groups, which would not have been possible at the start of this project. A common theme also arose through this work that static and dynamic correlation must be recovered in a balanced way to yield quantitative results. By systematically varying how both effects were included, we were able to make key chemical insights. This work supported the training of two postdoctoral scholars, one graduate student, and one undergraduate student in applying high-level wavefunction based methods to challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Critical Roles of Chalcogenide Anion on Strengthening Stability of Ni 2 Mo 6 Te 8 for Almost Exclusive Electrocatalysts Nitrate to Ammonia Conversion

Electrochemical hydrogenation of nitrate to ammonia using renewable electricity is a promising route for sustainability but lacks catalysts that can deliver balanced selectivity, activity, and durability. For this work, a new family of noble metal-free and high-performing Chevrel phase Ni 2 Mo 6 T 8 (T = S, Se, and Te) catalysts that have similar structural and textural properties and differ presumably only in chalcogenide anion is systematically studied. The side-by-side comparisons allow the uncovering of the critical roles of chalcogenide anions in impacting kinetic activities and long-term durability. The incorporation of anions with larger size and smaller electronegativity from sulfide to selenide and telluride invokes stronger inhibition of the otherwise competing hydrogen evolution reaction (HER) and steers the hydrogenation toward the selective formation of ammonia, thus improving both Faradic selectivity and the turnover frequency to high levels of 99.4% and 21.5 s –1 , respectively, on the Ni 2 Mo 6 Te 8 catalyst. More significantly, the bulkier anion in the Ni 2 Mo 6 T 8 catalyst kinetically inhibited the intercalation of electrolyte cations, a major degradation mechanism in the catalyst family examined here and delivered several times improved durability. Therefore, this study introduces novel active motifs for selective nitrate reduction and provides insights into the catalyst degradation mechanism and practical ways to improve durability.

36 MATERIALS SCIENCE↗