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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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At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

NASA NTRS2015

Modulated Sine Waves for Differential Absorption Measurements Using a CW Laser System

A continuous wave Light Detection and Ranging (CW LiDAR) system utilizes two or more laser frequencies and time or range shifted pseudorandom noise (PN) codes to discriminate between the laser frequencies. The performance of these codes can be improved by subtracting out the bias before processing. The CW LiDAR system may be mounted to an artificial satellite orbiting the earth, and the relative strength of the return signal for each frequency can be utilized to determine the concentration of selected gases or other substances in the atmosphere.

Campbell, Joel F.↗

NASA NTRS1992

Canadian Space Agency Space Station Freedom utilization plans

Under the terms of the NASA/CSA Memorandum of Understanding, Canada will contribute the Mobile Servicing System and be entitled to use 3 percent of all Space Station utilization resources and user accommodations over the 30 year life of the Station. Equally importantly Canada, like NASA, can begin to exploit these benefits as soon as the Man-Tended Capability (MTC) phase begins, in early 1997. Canada has been preparing its scientific community to fully utilize the Space Station for the past five years; most specifically by encouraging, and providing funding, in the area of Materials Science and Applications, and in the area of Space Life Sciences. The goal has been to develop potential applications and an experienced and proficient Canadian community able to effectively utilize microgravity environment facilities such as Space Station Freedom. In addition, CSA is currently supporting four facilities; a Laser Test System, a Large Motion Isolation Mount, a Canadian Float Zone Furnace, and a Canadian Protein Crystallization Apparatus. In late April of this year CSA sent out a Solicitation of Interest (SOI) to potential Canadian user from universities, industry, and government. The intent of the SOI was to determine who was interested, and the type of payloads which the community at large intended to propose. The SOI will be followed by the release of an Announcement of Opportunity (AO) following governmental approval of the Long Term Space plan later this year, or early next year. Responses to the AO will be evaluated and prioritized in a fair and impartial payload selection process, within the guidelines set by our international partners and the Canadian Government. Payload selection is relatively simple compared to the development and qualification process. An end-to-end user support program is therefore also being defined. Much of this support will be provided at the new headquarters currently being built in St. Hubert, Quebec. It is recognized that utilizing the Space Station could be expensive for users; costing in many cases millions of dollars to get a payload from conception to retrieval. It is also recognized that some of the potential users cannot or will not invest a lot of money or effort into Space Station utilization, unless there is a perceived significant commercial potential. How best to fund Space Station payloads is under study. Space Station Freedom will provide the first opportunity for Canada to conduct experiments in a long-duration microgravity environment. CSA have been developing and funding potential users for some time, and considerable interest has been shown by the response to our SOI earlier this year. Canada can be one of the two earliest users for the Space Station, along with NASA. We hope to take full advantage of this opportunity.

Faulkner, James↗

DOE OSTI2024

Finite Element Analysis and Machine Learning Guided Design of Carbon Fiber Organosheet-Based Battery Enclosures for Crashworthiness

Carbon fiber composite can be a potential candidate for replacing metal-based battery enclosures of current electric vehicles (E.V.s) owing to its better strength-to-weight ratio and corrosion resistance. However, the strength of carbon fiber-based structures depends on several parameters that should be carefully chosen. Here, in this work, we implemented high throughput finite element analysis (FEA) based thermoforming simulation to virtually manufacture the battery enclosure using different design and processing parameters. Subsequently, we performed virtual crash simulations to mimic a side pole crash to evaluate the crashworthiness of the battery enclosures. This high throughput crash simulation dataset was utilized to build predictive models to understand the crashworthiness of an unknown set. Our machine learning (ML) models showed excellent performance (R 2 > 0.97) in predicting the crashworthiness metrics, i.e., crush load efficiency, absorbed energy, intrusion, and maximum deceleration during a crash. We believe that this FEA-ML work framework will be helpful in down select process parameters for carbon fiber-based component design and can be transferrable to other manufacturing technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development of Remote Cutting Tools for use at ATR - 20438

As a result of years of operations of the Advanced Test Reactor (ATR) at the Idaho National Lab (INL), the ATR canal has become congested due to the storage of materials including waste consisting of highly irradiated remote handled (RH) metals. In order to support its continuing nuclear mission the ATR requires canal space to support fuel storage and future core internal change out (CIC) components. INL staff determined that the canal must be cleaned out and waste removed to efficiently utilize the valuable canal floor space. It was determined that a methodology for processing, packaging, characterizing, and removing current and future irradiated hardware from the ATR canal is needed. Orano Federal Services (OFS) and its subcontractor Babcock Services Inc. (BSI) were selected to provide remote tooling in order to safely and efficiently size reduce the material currently stored in the ATR canal. INL developed detailed requirements that established the design and performance requirements for the tooling. Orano TN and BSI had recently successfully completed similar tasks in clearing highly activated materials from spent fuel pools and canals at commercial nuclear plants. That experience directly translated into a proven approach that could be used at the ATR thereby saving time and money and lowering risks. Based on BSI's demonstrated proficiency in the design and deployment of remote size reduction specialty tooling at comparable commercial facilities, Orano Federal Services was confident that a solution to INL's requirements could be delivered. The tooling had to be designed to be compatible with the operational requirements of the ATR canal as well as the functionality needed by the facility operators that will use the equipment. Some of the major design requirements and functions of the equipment included remote operations, capability to shear highly irradiated sections of aluminum and steel tubing, pipe, and components ranging in size from 0.6 cm to 16.5 cm diameter into 1.5 m -1.8 m lengths, utilizing buoyancy compensation to assist with underwater operations, and use commercially available existing technology and components as much as practical. The design team evaluated and selected commercially available equipment that could be modified to meet the design and performance specifications. In addition, a waste sizing table (WST) was designed and fabricated to further ensure the size reduction equipment would perform as expected and give the facility operators a stable and usable remote, underwater work platform. After successful development of the tooling, a mock up test and operator training was conducted to ensure the tooling performed as expected and met the requirements of INL. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2016

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases.1 Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission.2 Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an Advanced Design Methods (ADM) based approach. This approach applies the concepts of Design of Experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development e ort. In order to t a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of Ground Rules and Assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated \what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are t to the outputs of each environment and are integrated via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any \what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will have the potential to lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗

NASA NTRS2016

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are fit to the outputs of each environment and are "integrated" via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any ''what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will help ensure lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗

DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗

DOE OSTI2021

Reinforcement Learning Configuration Interaction

Selected configuration interaction (sCI) methods exploit the sparsity of the full configuration interaction (FCI) wave function, yielding significant computational savings and wave function compression without sacrificing the accuracy. Despite recent advances in sCI methods, the selection of important determinants remains an open problem. Furthermore, we explore the possibility of utilizing reinforcement learning approaches to solve the sCI problem. By mapping the configuration interaction problem onto a sequential decision-making process, the agent learns on-the-fly which determinants to include and which to ignore, yielding a compressed wave function at near-FCI accuracy. This method, which we call reinforcement-learned configuration interaction, adds another weapon to the sCI arsenal and highlights how reinforcement learning approaches can potentially help solve challenging problems in electronic structure theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Integration of phage and yeast display platforms: A reliable and cost effective approach for binning of peptides as displayed on-phage

Hundreds of target specific peptides are routinely discovered by peptide display platforms. However, due to the high cost of peptide synthesis only a limited number of peptides are chemically made for further analysis. Here we describe an accurate and cost effective method to bin peptides on-phage based on binding region(s), without any requirement for peptide or protein synthesis. This approach, which integrates phage and yeast display platforms, requires display of target and its alanine variants on yeast. Flow cytometry was used to detect binding of peptides on-phage to the target on yeast. Once hits were identified, they were synthesized to confirm their binding region(s) by HDX (Hydrogen deuterium exchange) and crystallography. Moreover, we have successfully shown that this approach can be implemented as part of a panning process to deplete non-functional peptides. This technique can be applied to any target that can be successfully displayed on yeast; it narrows down the number of peptides requiring synthesis; and its utilization during selection results in enrichment of peptide population against defined binding regions on the target.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

NASA NTRS1973

Development of a computer-aided procedure for the national program of inspection of dams

An effort was undertaken to determine the utility of ERTS-1 MSS data, together with automatic data processing (ADP) techniques, to detect and locate surface water, and transfer the related technology to the Texas Water Rights Commission (TWRC). A test site was selected, ERTS-1 MSS and ancillary data obtained, and existent ADP classification programs applied. During the course of this effort a linear discriminant function was developed. The results were evaluated for potential candidates for a transferable procedure. A computer-aided technique using a linear discriminant function was selected and recommended, for inclusion in an operational system, which met detection and location criteria. Specifically, evaluation of the selected computer-aided procedure for the test site resulted in the detection of 100 percent of areas of surface water 10 acres or greater in areal extent and the geographic location of areas classified as water to a positional accuracy of 1000 feet or closer. The procedure was recommended for inclusion in an operational computer-aided procedure for transfer to TWRC.

Source record↗

NASA NTRS1978

The Ten-Ecosystem Study - Landsat ADP mapping of forest and rangeland in the United States

The Ten-Ecosystem Study was designed to assess the maximum information content of Landsat data and its utility for large area classification using a uniform technical approach on the 10 generalized forest and rangeland ecosystems of the United States. Conclusions on the feasibility of using Landsat remote sensing automatic data processing methods, selecting the best seasons, analyzing costs and the effects of site complexity, miscellaneous analysis, problems, and recommendations were derived from 2 years of study, the project being three-fourths completed.

Kan, E. P.↗

NASA NTRS1988

Technology advances for Space Shuttle processing

One of the major initial tasks of the Space Systems Integration and Operations Research Applications (SIORA) Program was the application of automation and robotics technology to all aspects of the Shuttle tile processing and inspection system. The SIORA Program selected a nonlinear systems engineering methodology which emphasizes a team approach for defining, developing, and evaluating new concepts and technologies for the operational system. This is achieved by utilizing rapid prototyping testbeds whereby the concepts and technologies can be iteratively tested and evaluated by the team. The present methodology has clear advantages for the design of large complex systems as well as for the upgrading and evolution of existing systems.

Wiskerchen, M. J.↗

NASA NTRSDate not supplied

New Capabilities and Improvements to the High-Order Glenn Flux Reconstruction Code

The Glenn Flux Reconstruction (GFR) code is a computational fluid dynamics (CFD) code under development at NASA Glenn Research Center. GFR is based on the high-order flux reconstruction (FR) method and provides a large-eddy simulation (LES) capability that is both accurate and efficient for complex aeropropulsion flows. Three significant new capabilities have been added to the code that improve its performance and functionality. First, a variety of explicit Runge-Kutta methods, including some with adaptive time stepping, were added to GFR with two methods offering a 33% improvement in time-to-solution. Second, GFR can now utilize fully unstructured, mixed-element meshes to more easily facilitate the grid generation process for complex geometries. Finally, a rotating reference frame capability has been added to GFR for solving rotating turbomachinery problems. A selection of results demonstrating these new capabilities are presented in this work. The Taylor-Green vortex problem is used to verify the new unstructured capability by showing similar accuracy and resolution for all element types. LES of the Turbulent Heat Flux Phase III (THX3) experiment with comparison to another high-order LES code and a popular Reynolds-averaged Navier-Stokes (RANS) code demonstrates the accuracy of the code for complex aeropropulsion flows. Finally, LES of a spacecraft cabin ventilation fan shows the ability of GFR to efficiently establish a fan performance map and identify operating points for further analysis at high orders of accuracy.

High-Order Methods↗

NASA NTRSDate not supplied

New Capabilities and Improvements to the High-Order Glenn Flux Reconstruction Code

Direct Numerical Simulations↗

NASA NTRS2007

Applications of Time-Reversal Processing for Planetary Surface Communications

Due to the power constraints imposed on wireless sensor and communication networks deployed on a planetary surface during exploration, energy efficient transfer of data becomes a critical issue. In situations where groups of nodes within a network are located in relatively close proximity, cooperative communication techniques can be utilized to improve the range, data rate, power efficiency, and lifetime of the network. In particular, if the point-to-point communication channels on the network are well modeled as frequency non-selective, distributed or cooperative beamforming can employed. For frequency-selective channels, beamforming itself is not generally appropriate, but a natural generalization of it, time-reversal communication (TRC), can still be effective. Time-reversal processing has been proposed and studied previously for other applications, including acoustical imaging, electromagnetic imaging, underwater acoustic communication, and wireless communication channels. In this paper, we study both the theoretical advantages and the experimental performance of cooperative TRC for wireless communication on planetary surfaces. We give a brief introduction to TRC and present several scenarios where TRC could be profitably employed during planetary exploration. We also present simulation results illustrating the performance of cooperative TRC employed in a complex multipath environment and discuss the optimality of cooperative TRC for data aggregation in wireless sensor networks

Barton, Richard J.↗

DOE OSTI2024

Recycling of Titanium Scrap by Shear Assisted Processing and Extrusion (ShAPE)

Titanium and its alloys are used in the aviation and automobile industries due to their remarkable strength to weight ratio, but, commonly, machining loss is high with ~90 wt.% of the material being converted to scrap. Recycling post-consumer Ti scrap directly into solid bulk products is a potential solution for repurposing valuable material. Further, reducing or even eliminating fresh Ti sponge during recycling might lead to lower energy and greenhouse gas emissions. In this study, a solid-phase process known as friction extrusion was utilized to recycle Ti-6Al-4V machining chips into solid wires which could be used as feedstock in additive manufacturing. The friction consolidation technique was first used to convert chips with varying degrees of oxygen content into solid billets for its use as feedstock material in subsequent friction extrusion. The extrudates were fabricated above the beta transition temperature, which was achieved by selecting rotation rate and feed rate, to process the billets near 1000°C using a tungsten-lanthana extrusion die. This work presents the first occurrence of friction extruded titanium alloy wires. The effect of friction extrusion on microstructural features, tensile properties, and texture are reported. Overall, the friction extrusion method is capable of recycling Ti-6Al-4V scrap directly into extruded wire.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Synthesis of Carbohydrates from Methanol Using Electrochemical Partial Oxidation over Palladium with the Integrated Formose Reaction

Electrochemically derived multicarbon products are a golden target for valorization of captured carbon dioxide due to the potential of turning a waste product into useful commodity chemicals with renewable energy sources. As a tantalizing approach toward their synthesis, the formose reaction utilizes catalytic condensation of formaldehyde to generate carbohydrates. Furthermore, while a sustainable approach to artificial carbohydrate production through electrochemical generation of formaldehyde is desirable, to date, it has not been fully realized. Here, we study the electrocatalytic conversion of methanol to formaldehyde on palladium with faradaic efficiency of over 90% at 0.9 V vs Ag/AgCl and with the partial current density of nearly 3 mA cm -2 at 1.6 V vs Ag/AgCl. We observe the concurrent generation of palladium oxides as a consequence of the high overpotentials employed, which may partially explain the higher selectivity toward the partial oxidation product. Moreover, we demonstrate that formaldehyde produced electrochemically from methanol is feasible for formose reactions without the need for further purification, achieving 21-28% carbon conversion to carbohydrates. This process, therefore, represents a potential avenue for the electrochemical generation of formaldehyde and its utilization in generating multicarbon products inaccessible by other electrocatalytic means.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗