Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Local time stepping”

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.

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

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

A theory for the origin of a self-replicating chemical system. I - Natural selection of the autogen from short, random oligomers

A general theory is presented for the origin of a self-replicating chemical system, termed an autogen, which is capable of both crude replication and translation (protein synthesis). The theory requires the availability of free energy and monomers to the system, a significant background low-yield synthesis of kinetically stable oligopeptides and oligonucleotides, the localization of the oligomers, crude oligonucleotide selectivity of amino acids during oligopeptide synthesis, crude oligonucleotide replication, and two short peptide families which catalyze replication and translation, to produce a localized group of at least one copy each of two protogenes and two protoenzymes. The model posits a process of random oligomerization, followed by the random nucleation of functional components and the rapid autocatalytic growth of the functioning autogen to macroscopic amounts, to account for the origin of the first self-replicating system. Such a process contains steps of such high probability and short time periods that it is suggested that the emergence of an autogen in a laboratory experiment of reasonable time scale may be possible.

White, D. H.↗
NASA NTRS2002

Procedure for Tooth Contact Analysis of a Face Gear Meshing With a Spur Gear Using Finite Element Analysis

A procedure was developed to perform tooth contact analysis between a face gear meshing with a spur pinion using finite element analysis. The face gear surface points from a previous analysis were used to create a connected tooth solid model without gaps or overlaps. The face gear surface points were used to create a five tooth face gear Patran model (with rim) using Patran PCL commands. These commands were saved in a series of session files suitable for Patran input. A four tooth spur gear that meshes with the face gear was designed and constructed with Patran PCL commands. These commands were also saved in a session files suitable for Patran input. The orientation of the spur gear required for meshing with the face gear was determined. The required rotations and translations are described and built into the session file for the spur gear. The Abaqus commands for three-dimensional meshing were determined and verified for a simplified model containing one spur tooth and one face gear tooth. The boundary conditions, loads, and weak spring constraints were determined to make the simplified model work. The load steps and load increments to establish contact and obtain a realistic load was determined for the simplified two tooth model. Contact patterns give some insight into required mesh density. Building the two gears in two different local coordinate systems and rotating the local coordinate systems was verified as an easy way to roll the gearset through mesh. Due to limitation of swap space, disk space and time constraints of the summer period, the larger model was not completed.

Bibel, George↗
NASA NTRS2017

Low-Thrust Trajectory Optimization with Simplified SQP Algorithm

The problem of low-thrust trajectory optimization in highly perturbed dynamics is a stressing case for many optimization tools. Highly nonlinear dynamics and continuous thrust are each, separately, non-trivial problems in the field of optimal control, and when combined, the problem is even more difficult. This paper de-scribes a fast, robust method to design a trajectory in the CRTBP (circular restricted three body problem), beginning with no or very little knowledge of the system. The approach is inspired by the SQP (sequential quadratic programming) algorithm, in which a general nonlinear programming problem is solved via a sequence of quadratic problems. A few key simplifications make the algorithm presented fast and robust to initial guess: a quadratic cost function, neglecting the line search step when the solution is known to be far away, judicious use of end-point constraints, and mesh refinement on multiple shooting with fixed-step integration.In comparison to the traditional approach of plugging the problem into a “black-box” NLP solver, the methods shown converge even when given no knowledge of the solution at all. It was found that the only piece of information that the user needs to provide is a rough guess for the time of flight, as the transfer time guess will dictate which set of local solutions the algorithm could converge on. This robustness to initial guess is a compelling feature, as three-body orbit transfers are challenging to design with intuition alone. Of course, if a high-quality initial guess is available, the methods shown are still valid.We have shown that endpoints can be efficiently constrained to lie on 3-body repeating orbits, and that time of flight can be optimized as well. When optimizing the endpoints, we must make a trade between converging quickly on sub-optimal endpoints or converging more slowly on end-points that are arbitrarily close to optimal. It is easy for the mission design engineer to adjust this trade based on the problem at hand.The biggest limitation to the algorithm at this point is that multi-revolution transfers (greater than 2 revolutions) do not work nearly as well. This restriction comes in because the relationship between node 1 and node N becomes increasingly nonlinear as the angular distance grows. Trans-fers with more than about 1.5 complete revolutions generally require the line search to improve convergence. Future work includes: Comparison of this algorithm with other established tools; improvements to how multiple-revolution transfers are handled; parallelization of the Jacobian computation; in-creased efficiency for the line search; and optimization of many more trajectories between a variety of 3-body orbits.

Parrish, Nathan L.↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

Laser-Assisted Synthesis of Monolayer 2D MoSe 2 Crystals with Tunable Vacancy Concentrations: Implications for Gas and Biosensing

We report tuning the structural and electronic properties of atomically thin two-dimensional (2D) materials via defect and vacancy engineering is the key to enabling their potential use in various applications, including electronics, energy, and sensing devices. Vacancies are, for instance, becoming highly promising for the enhanced interaction of gases and biomolecules with 2D materials in energy and sensing applications. However, the deterministic generation of desirable vacancies with tunable concentrations remains a challenge in 2D materials due to the limitations in the current growth methods, such as the complex reaction chemistries and gas flow dynamics. Therefore, engineering defects and vacancies in 2D materials have been mainly limited to destructive top-down processes such as heating, ion bombardments, and laser postprocessing. Here, we introduce a single-step bottom-up synthesis approach for the growth of monolayer MoSe 2 crystals with tunable vacancy concentrations. This method utilizes the spatiotemporal properties and adjustable power densities of the lasers to control the vaporization dynamics of the stoichiometric MoSe 2 powders. Such a mechanism in the vaporization allows us to grow tunable stoichiometry monolayer MoSe 2–x crystals on the substrates. The localized and time-controlled (250 ms to 2 s) vaporization of the MoSe 2 powder by a CO 2 laser enables the formation of monolayer crystals with controlled vacancy concentrations ranging from ~1 to 20%. The effects of laser power, laser irradiation time, and background pressure on the tuning range and subsequent properties of the crystals are investigated and quantified using Raman and photoluminescence spectroscopy, scanning transmission electron microscopy (STEM), and time-correlated single-photon counting (TCSPC). This bottom-up synthesis is a promising approach that allows the deterministic vacancy tuning for future electronics and, in particular, gas and biosensing applications without the need for further postprocessing and potential structural disruption of the crystals.

2D materials↗
NASA NTRS1974

The effect of yttrium and thorium on the oxidation behavior of Ni-Cr-Al alloys

The effect of quaternary additions of 0.5% Y, 0.5 and 1.0% Th to a base alloy of Ni-10CR-5Al on the oxidation behavior and mechanism was studied during oxidation in air over the range of 1000 to 1200 C. The presence of yttrium decreased the oxidation kinetics slightly, whereas, the addition of thorium caused a slight increase. Oxide scale adherence was markedly improved by the addition of the quaternary elements. Although a number of oxides formed on yttrium containing alloys, quantitative X-ray diffraction clearly showed that the rate-controlling step was the diffusion of aluminum through short circuit paths in a thin layer of alumina that formed parabolically with time. Although the scale adherence of the yttrium containing alloy was considerably better than the base alloys, spalling did occur that was attributed to the formation of the voluminous YAG particles which grew in a mushroom-like manner, lifting the protective scale off the subrate locally. The YAG particles formed primarily at grain boundaries in the substrate in which the yttrium originally existed as YNi9.

Kumar, A.↗
NASA NTRS1993

Monoclonal Antibody Testing for Cancer Metastasis

Malignant cells are characterized by the ability to invade surrounding normal tissues. Tumor invasion is abetted by proteolytic enzymes that have been correlated with recurrent disease and metastasis. These enzymes are involved in a cascade of proteolytic interactions with other enzymes and inhibitors which allow cancer cells to dissolve surrounding extracellular matrix, thereby enabling the cells to rapidly invade adjacent tissues and migrate to metastatic sites distant from the primary tumor. Among these proteases are the plasminogen activators (PA), collagenase IV, faminase, and in some cases cathepsin D, which together mediate key steps in the invasion process of metastasis. Cells which have the selective advantage for invasion and metastasis are those capable of regulating their proteolytic activity and proliferation. Cells in the process of invasion would be probably down-regulated for proliferation, but subsequent to attachment and adhesion at a distant site, would then be in a proliferative mode, up-regulating DNA replication. Urokinase (uPA) can be present in the tissues in several molecular forms. The inactive proenzyme is a single chain protein (scuPA) that is cleaved at Lys. 158 to form the double chain, high molecular weight active form (HMW-uPA) of 54 kD. A low molecular weight form (LMW-uPA) can also be produced by cleavage of the HMW-U PA at Lys. 135 - Lys. 136 giving a 35 kD active enzyme. Recently, it has been shown that the HMW active form of urokinase, bound to the tumor cell membrane, is responsible for the local lysis of the extracellular matrix, hence the tissue invasion mechanism for metastasis (Andreasen et al, 19861. Receptor- (membrane) bound uPA is twice as efficient (catalytically) as free fluid-phase uPA. Tho unbound uPA and the LMW form is not responsible for most of the local dissolution of extracellular matrix in the immediate vicinity of the metastatic tumor cell. High levels of urokinase (greater than 3.49 ng/mg of total protein) extracted from breast tumor tissues have recently been shown, together with plasminogen activator inhibitor 1 (PAI-1), to be a good prognostic indicator for high risk of recurrence and shorter patient survival times. In this project, we have attempted to develop immunocytochemical methodologies for the clinical assessment of the expression of urokinase plasminogen activator, which has been implicated to be important for initial steps in tumor invasion, and to relate it to cell proliferation and DNA replication at the single-cell level.

Source record↗
DOE OSTI2023

Computational diagnostics for flame acceleration and transition to detonation in a hydrogen/air mixture

A new computational diagnostic method for pressure-induced compressibility is proposed by projecting its local contribution to the chemical explosive mode (CEM) in the chemical explosive mode analysis (CEMA) framework. The new method is validated for the study of detonation development during the deflagration-to-detonation transition (DDT) process. The flame characteristics are identified through the quantification of individual CEM contributions of chemical reaction, diffusion, and pressure-induced compressibility. Numerical simulations are performed to investigate the DDT processes in a stoichiometric hydrogen-air mixture. A Godunov algorithm, fifth-order in space, and third-order in time are used to solve the fully compressible Navier-Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model (CDM) described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The new diagnostic method is first applied to onedimensional (1D) canonical flame configurations followed by two-dimensional (2D) simulations of DDT in an obstructed channel where different detonation initiation scenarios are examined using the new CEMA projection formulation. Detailed examinations of the idealized configuration of detonation initiation through shock focusing mechanism at a flame front are also studied using the new formulation. A comparison of the currently proposed CEMA projection and the original formulation by the authors suggests that including the pressure-induced compressibility is essential for the use of CEMA in DDT process. The results also show that the new formulation of CEMA projection can successively capture the detonation initiation through either a gradient mechanism or a direct initiation mechanism, and therefore can be used as an effective local analytical tool for the computational diagnostics of detonation initiation in a DDT process. It was found that detonation development is characterized by a strong contribution of chemistry role to the CEM which is pivotal to the initiation of detonation. The role of compressibility is found enhanced at the edge of the detonation front where diffusion was found to have minimal effects on detonation development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Context and mitigation of lost circulation during geothermal drilling in diverse geologic settings

Lost circulation is one of the most common and expensive problems facing geothermal energy development, representing up to 30% of drilling costs. We examined drilling records from four geothermal fields—McGinness Hills in central Nevada, Don A. Campbell and Steamboat Hills in western Nevada, and Puna Geothermal Venture on the Big Island of Hawai'i— to identify geologies most prone to lost circulation, as well as common mitigation strategies. Depths of lost circulation events varied, but their frequency often increased in the production interval. Lost circulation commonly occurred near fault intersections, and heavily faulted fields like McGinness Hills and Don A. Campbell showed secondary mineralization within approximately 100 m (328 ft) or less of where circulation was lost. Lost circulation mitigation strategies included using locally available materials (e.g., cotton seed hulls) as well as more expensive proprietary lost circulation materials, cement plugs above the reservoir, and drilling blind with aerated, polymer-based mud in the production zone. Addressing lost circulation using a well thought out decision-making approach and materials above the reservoir will save time and cost, and provide needed well integrity. Mitigation often requires a series of steps, typically applied from perceived least expensive to most, and are dependent on the severity and location in the well where circulation was lost and availability of materials. Placing cement plugs can cure lost circulation events, however these plugs are often expensive, time-consuming, and may not be successful.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Bi-Level Linear Programming Model for Automatic Load Shedding: A Distributed Wide-Area Measurement System-based Solution

Load shedding is currently implemented as a two-step based approach. In the first step, manual load shedding is taken place, were system operators, using estimates, inform distribution utilities of predicted stressful conditions. Information provided include the potential use of energy reserves, as well as load shedding amount. In a second step, automatic load shedding is done. The latter is realized using protection relays. While considering frequency variation, pre-defined values of load to be shed and correspondent number of stages for such to be realized are transformed into relay settings. Under-frequency protection relays use only local measurements towards decision making, thus operate in a decentralized architecture. Decision making is done in milliseconds plus breaker time. While this approach has provided much system reliability, considering the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions it will generate sub-optimal solutions, such as islanding. Phasor measurement units provide a source of information which can be useful for this problem. Centralized architecture-based solutions for automatic load shedding, as present in the state-of-the-art, require though total processing times which are not acceptable for real-life implementation. In this work, considering the above, a bi-level linear programming model is presented. The model is implemented considering a distributed architecture while leveraging phasor measurement units data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model, which decision variables are the location and load value to be shed. Easy-to-implement model, built-on the classic weighted least squares solution, highlight potential aspects towards real-life applications.

Bretas, Arturo Suman↗
DOE OSTI2022

Robust Event Classification Using Imperfect Real-world PMU Data

Here, this paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1992

Divergence preserving discrete surface integral methods for Maxwell's curl equations using non-orthogonal unstructured grids

Several new discrete surface integral (DSI) methods for solving Maxwell's equations in the time-domain are presented. These methods, which allow the use of general nonorthogonal mixed-polyhedral unstructured grids, are direct generalizations of the canonical staggered-grid finite difference method. These methods are conservative in that they locally preserve divergence or charge. Employing mixed polyhedral cells, (hexahedral, tetrahedral, etc.) these methods allow more accurate modeling of non-rectangular structures and objects because the traditional stair-stepped boundary approximations associated with the orthogonal grid based finite difference methods can be avoided. Numerical results demonstrating the accuracy of these new methods are presented.

Madsen, Niel K.↗
DOE OSTI2022

Predictive Tools for Customizing Heat Treatment of Additively Manufactured Aerospace Components

Laser-bed powder fusion (LBPF) additive manufacturing is increasingly being used to produce components of complex geometries using the Ni-base superalloy Inconel 718. The composition and the microstructure of the alloy are currently well optimized for wrought components made using conventional manufacturing processes such as rolling, forging, extrusion, etc. The attractive mechanical properties of the alloy result from the underlying austenitic matrix with fine equiaxed grains, and a high density and uniform distribution of the precipitation hardening phase, γ". Heat treatment steps such as homogenization, solutioning and aging are well documented for the wrought alloy. However, when the same wrought alloy compositions are used for the additive manufacturing (AM) processes, the asprocessed microstructure is significantly different, because of the different thermal history associated with LBPF, including rapid solidification and multiple temperature excursions that lead to multiple re-melting and reheating in the solid state. Rapid solidification introduces potential non-equilibrium effects at the moving solid-liquid interfaces that impact the extent of solute segregation, as well as the morphology of the dendritic grains that form. In order to recover the target mechanical properties, AM components have to undergo post-process heat treatments. However, such heat treatments have to be custom designed for the AM process and the component geometry because of the expected vast differences in the microstructure at various locations of a component with complex geometry. The homogenization and precipitation steps should be optimized for the component so that target mechanical properties can be obtained throughout the part. The objective of this research is to utilize High Performance Computing in phase field simulations of microstructure evolution during post-processing of AM components. The physics-based modeling will be beneficial in reducing the experimental effort required for heat treatment process selection, optimization, and certification, thus leading to a significant reduction in energy consumption for AM and post-processing heat treatment. The optimization study will help identify heat treatments steps that are critical for development of a final desired microstructure with the minimum energy input. This combined with shortening of the production cycle (time-to-market) by reducing the number of failed parts (property targets), and reduction in the number of iterations for process optimization, will enable 30-40% savings in the energy costs. Phase field simulations of the degree of homogenization and the effect of local matrix composition on the nucleation and growth of competing precipitating phases were performed using the Microstructure Evolution Using Massively Parallel Phase Field Simulations code developed in-house at the Oak Ridge National Laboratory. The simulations were able to successfully capture the kinetics of nucleation and growth, and morphologies of various precipitating phases as a function of local matrix compositions and composition gradients characteristic of local microstructures arising from location-dependent variations in the thermal conditions. Future work will involve extending the simulations to a length scale consisting of multiple dendrites, so that the effect of homogenization on the coarsening of the dendrites can be simulated and used as an additional input to the optimization of the heat treatment process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Adaptive, problem-tailored variational quantum eigensolver mitigates rough parameter landscapes and barren plateaus

Abstract Variational quantum eigensolvers (VQEs) represent a powerful class of hybrid quantum-classical algorithms for computing molecular energies. Various numerical issues exist for these methods, however, including barren plateaus and large numbers of local minima. In this work, we consider the Adaptive, Problem-Tailored Variational Quantum Eiegensolver (ADAPT-VQE) ansätze, and examine how they are impacted by these local minima. We find that while ADAPT-VQE does not remove local minima, the gradient-informed, one-operator-at-a-time circuit construction accomplishes two things: First, it provides an initialization strategy that can yield solutions with over an order of magnitude smaller error compared to random initialization, and which is applicable in situations where chemical intuition cannot help with initialization, i.e., when Hartree-Fock is a poor approximation to the ground state. Second, even if an ADAPT-VQE iteration converges to a local trap at one step, it can still “burrow” toward the exact solution by adding more operators, which preferentially deepens the occupied trap. This same mechanism helps highlight a surprising feature of ADAPT-VQE: It should not suffer optimization problems due to barren plateaus and random initialization. Even if such barren plateaus appear in the parameter landscape, our analysis suggests that ADAPT-VQE avoids such regions by design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Automated imaging of the annihilation of a transverse domain wall in patterned magnetic thin films

Imaging the magnetic domain wall behavior in patterned thin films under external stimuli can enable understanding the underlying energy landscape and the role of local microstructure and defects. We present an automated workflow for in situ Lorentz transmission electron microscopy to image magnetic domain walls at the nanometer length scale and at a time resolution in the sub-millisecond regime—the latter of which is limited by the speed of the available camera. Our workflow is modular and can be broadly applied to various types of in situ experiments, taking us a step closer to the future of autonomous imaging of nanomagnetic films with electron microscopy. Using our workflow, we show the transformation of a transverse domain wall with sub-millisecond time resolution under the application of an in situ transverse magnetic field, a study of whose dynamics are essential in the design of future domain wall mediated spintronic device applications.

Algebraic topology↗
DOE OSTI2020

Zero-deadtime processing in beta spectroscopy for measurement of the non-zero neutrino mass

The Project 8 collaboration seeks to measure, or more tightly bound, the mass of the electron antineutrino by applying a novel spectroscopy technique to precisely measure the tritium beta-decay spectrum. The current system produces a single analog signal, which is digitized and processed in several stages before being saved to local disk storage. Online processing includes two stages, an FPGA connected to the analog to digital converter reduces the data down to the region of interest before shipping over the local network for further processing and storage. A normal CPU-based processing stage applies triggering logic to only save data at times when a signal is present, further reducing the total volume of data which needs to be written to disk or transferred for long-term storage. The next stage of the project will need to process many input channels and will integrate a necessary aggregation and combination step prior to applying the event search and triggering logic. We present the online processing system which has successfully been deployed for the current, singlechannel, phase. We also present the status and design for a many-channel platform.

Project 8 Collaboration↗
NASA NTRS1989

Thickening oscillation of a delta wing using Navier-Stokes and Navier-displacement equations

The problem of unsteady, supersonic, locally conical, vortical flow around a delta wing undergoing thickening oscillation is solved using the unsteady, thin-layer Navier-Stokes equations and the unsteady linearized Navier-displacement equations. The unsteady, thin-layer Navier-Stokes equations are solved using the implicit approximate-factorization finite-volume scheme to compute the conservative components of the flow vector field. With the conservative components known at any time step, the linearized, Navier-displacement equations are solved using the alternating, direction-implicit scheme to obtain the grid points displacements due to known displacement boundary conditions. A grid-displacements limiter, in the form of a low mesh Reynolds number, is used to limit grid-folding in regions of highly reversed flow.

Chuang, Hsin-Kung A.↗
DOE OSTI2020

Local Modulation of Single-Atomic Mn Sites for Enhanced Ambient Ammonia Electrosynthesis

Rationally tuning the local structures of single-atomic active sites for the electrocatalytic N 2 reduction reaction (NRR) remains an urgent but worthwhile research topic. Herein, we accomplish the local modulation of single-atomic Mn sites and construct single Mn–O 3 N 1 sites anchored on porous carbon (Mn–O 3 N 1 /PC) by delicately controlling the Mn–O bonding conditions. Furthermore, the constructed structures are confirmed via the combination of atomic-scale imaging, Raman spectroscopy, synchrotron radiation-based soft and hard X-ray absorption spectroscopies, and X-ray photoelectron spectroscopy. The Mn–O 3 N 1 /PC catalyst yields an NH 3 yield rate of 66.41 μg h –1 mg cat. –1 (corresponding to 1.56 mg h –1 mg Mn –1 ) at -0.35 V versus reversible hydrogen electrode, which is about four times that on the control Mn–N 4 /PC catalyst. The enhanced NRR performance is ascribed to its unique geometry and electronic structures, which not only facilitate the adsorption and activation of the N 2 molecule but also lower the free energy change of the potential-determining step.

36 MATERIALS SCIENCE↗