Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “games”

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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Biological Electron Transfer and Catalysis Energy Frontier Research Center

The overarching objective of the BETCy EFRC project is to investigate the mechanisms and structural basis controlling electron bifurcation, electron-ion coupling, and redox catalysis in model enzymes. This detailed understanding of how biological systems control and exploit electron flow will be used to develop modular biochemical conversions for the production of hydrocarbon and hydrogen biofuels. This project will conduct an in-depth study of metalloenzyme structure-function relationships that enable retuning of catalytic sites, electron-transfer thermodynamics, and the evolution of tailor-designed chemical reactions involving two model enzymes: hydrogenase and nitrogenase. The center is organized into three major thrust areas: Thrust 1. Energy conservation and electron flow; Thrust 2. ATP-coupled electron transfer; and Thrust 3. Atomic level determinants of enzymatic redox properties and their relationship to catalytic bias. We will develop a collective knowledge in metalloenzymes by applying physical science and computational tools to characterize biochemical reactions catalyzed specifically by multi-subunit enzymes harboring iron-sulfur clusters and flavin cofactors, as models for redox reactions throughout biology. Understanding these mechanisms is central to overcoming the key thermodynamic barriers currently limiting production of reduced products and biofuels. The research plan of the BETCy EFRC has been designed to provide the basis to exploit unique biochemical mechanisms that have yet to be explored substantively in the context of bioenergy but have the potential for game-changing advancement. The successful outcome of this research will be a collection of fundamental principles that serve as a blueprint to enable the tailored re-design of biological systems and enzymes to control matter and energy at the level of electrons and molecules to provide the foundations to create new energy technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The 2019 Nonlinear Mechanics and Dynamics Research Institute

The 2019 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 17 to August 1, 2019. NOMAD brings together participants with diverse technical backgrounds to work in small teams to cultivate new ideas and approaches in engineering mechanics and dynamics research. NOMAD provides an opportunity for researchers especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 20 students came to Albuquerque, New Mexico to participate in the seven-week long program held at the Mechanical Engineering building on the University of New Mexico campus. The students collaborated on one of seven research projects that were developed by various mentors from Sandia National Laboratories, the University of New Mexico, and academic institutions. In addition to the research activities, the students attended weekly technical seminars, various tours, and socialized at various off-hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation on their research findings. Many of the research discoveries made at NOMAD are published as proceedings at technical conferences and have direct alignment with the critical mission work performed at Sandia.

42 ENGINEERING↗
DOE OSTI2020

Development and Integration of Predictive Models for Manufacturing and Structural Performance of Carbon Fiber Composites in Automotive Applications (Final Report)

The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Wildlife Management Plan for the Oak Ridge Reservation

This document outlines a plan for management of the wildlife resources on the US Department of Energy’s (DOE’s) Oak Ridge Reservation. Management includes wildlife population control through restoration of wildlife species; preservation, management, and enhancement of wildlife habitats; coordination of wildlife studies and characterization of areas, hunting, trapping, removal, and habitat manipulation; wildlife damage control; and law enforcement. Wildlife resources are divided into several categories, each with a specific set of objectives and procedures to attain the goals. These objectives are management of (1) wildlife habitats to ensure that all resident wildlife species exist on the Reservation in viable numbers; (2) focal species to promote healthy populations on designated land units; (3) game species for research, education, recreation, and public safety; (4) the Three Bend Scenic and Wildlife Management Refuge Area; (5) nuisance wildlife, including nonnative species, to achieve adequate population control for the maintenance of health and safety on the Reservation; (6) sensitive species (i.e., state or federally listed as Endangered, Threatened, Of Special Concern, or In Need of Management) through preservation and protection of both the species and habitats critical to the survival of those species; and (7) wildlife disease. Achievement of the objectives is a joint effort between Oak Ridge National Laboratory and the Tennessee Wildlife Resources Agency (TWRA) through agreements between DOE and the University of Tennessee (UT)-Battelle LLC, between TWRA and DOE, and between Tennessee Department of Environment and Conservation (TDEC) and DOE. Implementation of objectives is to be informed by leading-edge research and a strong collaborative approach between UT-Battelle and TWRA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Towards Integrated Strategic Deterrence - 3rd Annual Cross-Domain Deterrence Seminar, 2016

Lawrence Livermore National Laboratory (LLNL) hosted the 3rd Annual Cross-Domain Deterrence (CDD) Seminar on November 15-17, 2016 in Livermore, CA. The seminar was sponsored by LLNL’s National Security Office (NSO) and Center for Global Security Research (CGSR). The primary purpose of the seminar was to utilize the crossdomain framework to work toward an approach for comprehensive and integrated strategic deterrence. The seminar focused on a tabletop exercise (TTX) to explore the dynamics of escalation and de-escalation in cyber space, outer space, and the nuclear domain. The TTX explored a scenario involving a NATO Article V defense of a Baltic ally. To help inform game “play,” the exercise was preceded by expert panel discussions about the CDD strategies of Russia and NATO. The exercise was followed by two panels on lessons learned and next steps, to help derive lessons from the TTX.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Medium-duty Urban Range Extended Connected Powertrain (Final Scientific Technical Report)

The project goal is to develop and demonstrate a Class 4 delivery vehicle that reduces fuel consumption by 50% or more when compared to an equivalent vehicle with a conventional internal combustion engine (ICE) powertrain driven on a comparable duty cycle. This shall be achieved using a plug-in hybrid electric (PHEV) configuration that optimizes the efficiency of the ICE. The proposed solution aims to be commercially viable for fleets to procure the system without additional incentives. To accomplish this, commercialized light-duty vehicle electric drive components shall be used. A PHEV configuration for Class 4 MD/HD vocational vehicles using commercialized light-duty vehicle electric drive components will require the development of a new topology for the hybrid powertrain applicable to medium-duty vehicles. Prior research indicates that an identified novel power split device could provide a fuel economy improvement potential of up to 51%. Utilizing an advanced battery management algorithm that will allow operation closer to the battery limits, the project will minimize battery capacity to achieve the desired performance results while maintaining the cost target for high commercialization. The solution must be cost effective to purchase and integrate into a Class 4 delivery vehicle, deliver the intended fuel economy improvement, and perform as well, or better, than the current conventional ICE powertrain. MD/HD vehicles typically require higher power, which is one factor that results in high costs for the powerful electric machines typical in larger HEV/PHEV systems. A key element in the project is the use of commercially available Bosch electric drive components (e.g., motors, batteries, and power electronics) from the larger passenger vehicle segment. This leverages the economies of scale to decrease cost and improve reliability beyond current purpose-built low-volume commercial vehicle components. These innovations will result in a game-changing PHEV system that meets DOE’s 50% fuel consumption reduction target, grants the vehicle an uncompromised driving range, and achieves the cost point for widespread adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Testing the possibility of magnetic domain imaging based on circular & linear dichroism using photoemission electron microscopy

In recent years, an increasing number of memory and spintronic devices have been developed exploiting the combination of ferromagnetic (FM) and anti-ferromagnetic (aFM) materials. Consequently, magnetic imaging based on continuous-wave (CW) ultraviolet (UV) (λ = 266nm and longer wavelength) photoemission electron microscopy (PEEM) is gaining considerable attention due to the possibility of determining magnetizations for FM and aFM materials with 10 nm lateral resolution at video rate image acquisition. This PEEM-based approach exploits the polarization-dependent photoemission yield, which is subject to the polarization vector and the FM or aFM magnetization direction. Because of this unique attribute, magnetic imaging using PEEM when coupled to a laser with multiple illumination geometries allows for characterizing in-plane and out-of-plane magnetizations. This concept, however, has not been tested using a deep-UV laser (λ = 213nm), which has a much broader application space than the longer wavelength excitation used in previous reports. The purpose of this project in FY17 was to show the proof-of-concept of magnetic circular dichroism (MCD)-PEEM imaging using a λ = 210nm pulsed laser. Our results demonstrated the feasibility of in-plane and out-of-plane magnetic imaging with the limitations in the lateral resolution, data acquisition time, and signal-to-noise ratio anticipated for using a pulsed laser of moderate power. The project goal for FY18 is to construct the automated polarization-controlled data acquisition, and to establish the new lab facility in anticipation of acquiring a state-of-the-art high-power 213nm CW laser, planned to be installed in FY19. We successfully demonstrate the former by measuring dielectric stacks with polarization-dependent photoemission yield. Extrapolating from our result, we conclude that the capability of PEEM-based magnetic imaging using a CW deep UV laser could be a potential game-changer for scientific investigations and technological developments of magnetic materials and spintronic devices. In addition, polarization controlled PEEM imaging shows the potential for ellipsometry imaging of embedded nanomaterials exploiting their subtle differences in optical constants with respect to their surrounding dielectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The 2018 Nonlinear Mechanics and Dynamics Research Institute

The 2018 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 18 to August 2, 2018. NOMAD brings together participants with diverse technical backgrounds to work in small teams to cultivate new ideas and approaches in engineering mechanics and dynamics research. NOMAD provides an opportunity for researchers -- especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 17 students came to Albuquerque, New Mexico to participate in the seven-week long program held at the Mechanical Engineering building on the University of New Mexico campus. The students collaborated on one of six research projects that were developed by various mentors from Sandia National Laboratories, University of New Mexico, and academic institutions. In addition to the research activities, the students attended weekly technical seminars, various tours, and socialized at various off-hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation on their research findings. Many of the research discoveries made at NOMAD are published as proceedings at technical conferences and have direct alignment with the critical mission work performed at Sandia.

42 ENGINEERING↗
DOE OSTI2013

Veterans Commissioning Training Program for Commercial Healthcare Facilities [Final Report]

This project was designed to develop a building energy training curriculum, with hopes for creating immediate, long-term job opportunities for returning Iraq and Afghanistan veterans as energy commissioning agents within both public and private sectors. As part of this proposed effort, an online version of the curricula were developed in part using a modified version of the Association of Energy Engineers (AEE) Certified Building Commissioning Professional program. Case studies utilizing building information modeling (BIM) data from actual retrocommissioning projects and 3D gaming platform were developed as part of the curriculum. In addition to using materials from existing literature, the PIs also conducted scientific-based research on energy retrofitting related to building envelopes using numerical simulation approach. And the research findings and recommendation were incorporated in the developed curriculum. Currently, there are a lack of scientific-based guidance on envelope retrofitting practice. Many retrofitting practices were based on experiences, and are limited by the lack of scientific evidence. Existing retrofitting training material have limitations due to this missing piece. We have succeeded in producing some scientific evidence to guide and provide solutions to some building envelope design and retrofitting. The results from some of our research using computational fluid dynamics have demonstrated the feasibility of using our recommended solutions. Research results and findings were disseminated to the research and industry communities through conference papers (Appendix B) and presentations (Appendix C), and some results and findings were incorporated into the developed training curriculum (Appendix A).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

How AI Predicts the Untrained and Unseen

Focus Area: Model predictability improvements (Primary); Data optimization (secondary); Data complexity insights (secondary). The Scientific Challenge: If we believe that a future under extreme conditions will look very differently from today, we can likely agree that ML/AI models trained on past and present datasets will not be adequate to make reliable predictions into the future. This is true for water cycling, as well as biogeochemistry and other Earth system components and behaviors. Additionally, ML/AI models are inherently non-physical. Despite the flourishing success of ML/AI in many applications, such as computer vision, natural language process, and gaming, even the most sophisticated AI models don’t understand the very basic physical laws. Therefore, a natural question is: Can we trust ML/AI based predictions of Earth system behaviors that are fundamentally driven by physical laws? So, are physics models with meticulous process representation a better choice? Not exactly. Physical models, when firmly rooted in first principles, work great at predicting behaviors of systems with a well-defined set of boundary conditions and variables. However, as a complex system, the number of parameters and the degree of complexity and dynamics in processes, coupling, and scale dependent emergent behaviors make the Earth system behaviors very challenging to predict with physical models composed of deterministic laws. In addition, due to the lack of fundamental understandings, physical models often implement empirical correlations derived from observations with biases from locality of data generation. Because correlation is not necessarily causation or comply with first principles, scaling of model predictions beyond locality is often invalid. Beyond the limitation of models, physics or AI, our knowledge of the Earth system is limited by the lack of observational technologies and resources. Insufficient data density, dimensionality and diversity only offer a sliced (or projected) view of the Earth system, e.g. Plato’s Cave analogy, limiting our capability to better understand and represent fundamental processes in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The CanBikeCO Mini Pilot: Preliminary Results and Lessons Learned

In fall 2020, the Colorado Energy Office, as part of the State of Colorado’s “Can Do Colorado” initiative, initiated a project aimed at encouraging energy-efficient transportation during the COVID-19 pandemic. The initial mini-pilot provided e-bikes to 13 low-income households under an individual ownership model. This report assesses the impact of providing this additional mobility option on the travel behavior of participants. It also outlines the lessons learned from deploying a continuous monitoring platform to track the travel behavior. These lessons will influence the evaluation component for the full pilot, which will cover multiple geographic regions, starting in summer 2021, and run for 2 years. The continuous data collection was enabled by a customized version of the open-source e-mission platform, called CanBikeCO, configured with a behavioral gamification feature. The Colorado Energy Office used this system to collect a unique data set consisting of 3 months of partially automated travel diaries, combining sensed and surveyed data and linked with demographic information, from 12 participants. The data collection process worked well overall: users generally liked the app, appreciated the game, and did not complain about battery life. The long tracking period introduced behavioral challenges in user engagement, which we plan to address using repeated patterns and automated status checks for the full pilot. The analysis results, based on the subset of trips with user-reported labels (68%), indicate that the e-bike was the dominant commute mode share (31%), in sharp contrast to the census bicycle commute mode share (<1%). E-bike trips primarily replaced single-occupancy vehicle (SOV) trips (28%), followed closely by walking (24%) and regular bike (20%). The nonmotorized mode replacement corresponds to lower travel time and increased productivity enabled by the program. The emissions impact analysis of the program, computed using trip-level energy intensity factors, indicates savings of 1,367 lbs. of CO 2 . Although the results are strongly positive, the narrow demographic profile of study participants, their limited mobility alternatives, and nonuniform labeling indicate caution in broader interpretation. These preliminary results do suggest that such programs, supported by real-time education and support from program managers, can simultaneously meet equity and sustainability goals. The planned full pilot, addressing the data collection challenges and broadening the geographic scope, will provide additional insights into the generality of this approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Deployment of Community Scale Solar Photovoltaic Energy Systems in Forest County Potawatomi Community

FCPC is a federally recognized tribe with a membership of more than 1400. The Tribe has a reservation in Forest County, Wisconsin, and tribal trust lands in Milwaukee County, Wisconsin, with significant governmental and business operations in both areas. Until relatively recently, FCPC was one of the poorest tribes in the Midwest. Due to its successful gaming operations, it now has improved its financial situation and is using its resources to benefit both its members and the general public through environmental and other community efforts, many of which are long-delayed because of the extended period of abject poverty. The Tribe has developed the long-term goal of becoming energy independent using renewable resources. In order to meet this goal, the Tribe has taken several important steps. As an interim step, FCPC is purchasing nearly 55 million kilowatt hours of renewable energy certificates (“RECs”) annually from certified renewable energy facilities in the United States. These RECs offset more than 100% of the present electricity use at all of the Tribe’s facilities. The Tribe is currently ranked number 11 on the Environmental Protection Agency’s (EPA) Top 20 Local Government list of green power purchasers and is a member of the EPA’s Green Power Partnership. The original project suggested small scale installations on tribal homes and certain government buildings. The Tribe suggested that the project would result in 730 kw installed. By revising the project, the Tribe was able to install 938 kw and owns the largest installation in Northern Wisconsin with the 800 kW installation at the Potawatomi Carter Casino Hotel (“PCCH”). The PCCH installation, in summer months, can provide near 90% of the use during daylight hours. Although tracking was not immediately available FCPC has since confirmed significant production with certain quarterly savings nearing $210,000. These installations provide a reduction in facility costs providing more revenue for Tribal services including cultural, health, sustainable food sources, environmental preservation and other Tribal initiatives. Further, the installations have resulted in positive steps towards the Tribe’s goals of energy sovereignty and the use of 100% renewable clean energy. Finally, the PCCH project, specifically, has had the additional benefit of providing a likely area for a microgrid. The size of the installation and offset achieved have pushed the Tribe toward planning for storage and a microgrid system that would both further the Tribe’s energy goals and provide a safe haven for the Community during times of need.

14 SOLAR ENERGY↗
DOE OSTI2021

Optimizing and Extending the Functionality of EXARL for Scalable Reinforcement Learning [Slides]

The main goal of the Co-Design Summer School 2021 is to provide algorithmic improvements to EXARL framework by improving performance and by adding functionalities. This presentation includes an introduction to reinforcement learning and to EXARL. The researchers expanded the capability of EXARL by including additional agents like (Asynchronized) Advantage Actor Critic (A2C/A3C) and Twin Delayed Deep Deterministic Policy Gradient (TD3). They also explored algorithmic improvements such as v-trace and Prioritized Experience Replay. They found that A2C/A3C performed best with v-trace and outperformed Deep Q-Network (DQN) on both the CartPole game and the ExaBooster scientific environment. Additionally, they found that TD3 performed as good as the existing Deep Deterministic Policy Gradient (DDPG) agent and that adding Prioritized Experience Replay to DDPG accelerated convergence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tensor Text-Mining Methods for Malware Identification and Detection, Malware Dynamics Characterization, and Hosts Ranking

Malware is one of the most persistent and costly cyber threats endangering reputation, confidentiality, integrity, and availability for organizations and national security. Consequently, many of the incident detection and prevention systems, and incident responders have begun to utilize machine learning as a helper in the fight against malware and other cyber threats. However, cyber defenders rely on interpretability and generalizability, yet the popular machine learning methods are black-box and often use traditional supervised solutions that do not generalize to novel malware. Therefore, there is a need to improve the existing solutions. At the same time, the majority of the prior research ignored essential evaluation criteria when reporting the results of their methods, which disables the safe reproducibility of the methods in a production environment. Tensor decomposition, on the other hand, enables interpretable unsupervised analysis of the large-scale data for the discovery of hidden patterns. Our findings, performed on real-world and large-scale experiments, show that tensor factorization-based methods yield performance results that surpasses or competes with existing supervised solutions with the added benefit of interpretability and generalizability. With the ability to analyze complex and large-scale data using tensors, we report results that reflect real-world production environments. We propose to develop new game- changing tools for malware identification and characterization that can trace malware evolution, rank the infected or malicious hosts, and streamline the work of incident response teams, malware analysts, and incident detection and prevention systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Exploring Electrocatalysis of Methane on Transition Metal Surfaces

Methane is a potent greenhouse gas because it has a heat-absorbing ability that is 20 times stronger than the better-known carbon dioxide. It is also the dominant component of nature gas (>70%). Its current greenhouse effect is only second to carbon dioxide largely because of its relatively low atmospheric concentration. Alarmingly, however, the latter has seen a 1.5-time increase since 1750, mainly due to anthropogenic livestock farming, coal and natural gas mining, and organic matter decomposing in waste landfills. Mitigating such a trend effectively and efficiently is therefore highly desirable and intensely sought for. This final technical report describes some exciting research progresses made over the last three years supported financially by the aforementioned award. The research conducted focused on exploring electrochemical direct methane to methanol (DMTM) conversion under mild conditions. The goal of research was to explore the possibility of developing potentially game-changing electrocatalysts and electrocatalysis that can convert methane directly to methanol in a most sustainable way for curbing its effect on global warming. Progress has been made in the following three directions. First, by adapting a hydrogen fuel-cell configuration that enables gaseous methane to be transported directly to the electrocatalyst surface, we have overcome the perennial difficulty in measuring activity of methane electro-oxidation at low temperature and ambient pressure that has prevented any meaningful studies of electrocatalysis of methane conversion thus far. Second, we have developed a novel and operational in situ electrochemical infrared (IR) spectral cell for studying electrocatalysis of direct methane to methanol conversion. This novel cell is also expected to alleviate the measuring difficulty caused by low solubility of methane in aqueous electrolyte and low sticking coefficient for methane adsorption onto transition metal surface. It will improve significantly the IR’s signal to noise ratio. Third, we have successfully synthesized nano-sizing copper (Cu) exchanged zeolite mordenite (Cu-ZMOR) and coated it with carbon that enabled electrochemical access to the encaged Cu ions. This opens a door to unravel the chemistry of Cu ions in catalyzing direct methane to methanol conversion under mild experimental conditions. Altogether, these progresses achieved have laid a solid foundation for further exploring electrocatalysis of direct methane to methanol conversion in general where there exists “a plenty of room” for new discoveries and developments.

03 NATURAL GAS↗
DOE OSTI2022

Novel Approaches to the Isolation of Glucaric Acid from Fermentation Broth. Final report

Kalion has successfully demonstrated a fermentation route using glucose as the feedstock. This game-changing technology allows Kalion to economically produce large-scale quantities of high-purity glucaric acid products. Kalion has also developed a novel downstream processing strategy for isolating and purifying glucaric acid forms, including the free acid, monoammonium glucarate, and monopotassium glucarate. Despite the low solubility of these products, significant water removal is needed prior to crystallization, requiring energy intensive evaporation or reverse osmosis. Here, we work in collaboration with the Separations Consortium to develop novel, low-cost means of water removal in Kalion’s glucarate/glucaric acid purification process. This proposed CRADA project with national labs (ORNL, ANL, and NREL) evaluated various technologies developed by the Separations Consortium as applied to glucaric acid purification, intended to generate a scalable, cost-effective, energy-efficient process. Four approaches were evaluated with mock aqueous solutions of glucaric acid or glucarate, and the results analyzed with respect to separation effectiveness and potential cost savings. The leading technology will then be further developed and tested with actual clarified or non-clarified broth (depending on the approach) obtained from 20L fermentations provided by Kalion, that will contain inorganic ions, byproducts, and residual sugars in addition to the product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗