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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Minimizing exposure to legacy wells and avoiding conflict between storage projects: Exploring area of review as a screening tool

Elevated pressure from large-volume injection is a key driver of risk and project cost. If transmissive features (e.g., non-isolating wells or fracture systems) are present, increased injection-zone pressure can drive fluids from depth toward protected freshwater resources. In US Carbon Capture and Storage (CCS) law, the area at risk is known as the Area of Review (AoR). The size and number of potentially transmissive features to be evaluated and possibly remediated or managed is a function of the size and location of the AoR. The size of the AoR depends on several variables, including properties of the injection zone, properties of protected resources, and injection rate and duration. Evaluation of the intersection of these variables across a portfolio of sites highlights the injection zone depth and boundary conditions as top-level controls. Deep injection, use of multiple stacked injection zones, reduced injection rate and choice of injection well location can all be used to minimize AoR and the number of potentially transmissive features within it. Here, we introduce the concept of pressure space (defined as connected pore volume times pressure) as the key subsurface commodity for CO 2 storage and we suggest that it forms a more robust basis for leasing and regulation than pore space alone.

58 GEOSCIENCES↗
DOE OSTI2025

Ultra-high efficiency hydrogen production using a large-scale solid oxide electrolysis cell system

Efficient and cost-effective production of clean hydrogen is key to decarbonizing the production of hard-to-abate industries, such as chemicals, fuels, steel, cement and many other commodities that form the basis of modern societies. High-temperature steam electrolysis (HTSE) has recently become commercially available and offers opportunities for producing hydrogen at higher efficiency and lower cost than competing low temperature technologies. In this work, we report world record setting hydrogen production efficiency from large-scale prototype HTSE systems based on solid oxide electrolysis cell (SOEC) technology. Independent tests performed at Idaho National Laboratory (INL) employed a Bloom Energy 100 kW SOEC system to achieve a hydrogen production direct current specific electric energy consumption as low as 36.7 kWh per kilogram of hydrogen. Remarkably, similar high efficiencies in the range of 36–39 kW/kg-H2 were obtained over a wide range of hydrogen production rates and even during dynamic ramping as the hydrogen production and electric power consumption of the system were varied between 20 % and 100 % of nominal conditions. Furthermore, these test results validate previous projections that commercial SOEC systems can produce clean hydrogen at efficiencies approaching 100 % for less than 2 U S. dollars per kilogram when located near sources of inexpensive, low-grade heat and clean electricity.

08 HYDROGEN↗
DOE OSTI2018

Fundamental catalytic challenges to design improved biomass conversion technologies

During the past ten years, there has been significant interest and investment in the study of catalytic conversion of biomass-derived feedstocks into renewable fuels and chemicals. In the United States, an estimated $25 billion has been spent by venture capitalists, industry, and government agencies during this period of time to commercialize “renewable technologies” including solar energy, wind power, batteries, and biofuels (e.g., cellulosic ethanol). Four societal factors are driving these investments including: (1) the increased price of crude oil; (2) concerns about global warming; (3) the desire to improve rural economies where biomass is produced, and; (4) national goals to become energy self-sufficient. Furthermore, underlying these efforts is the realization that lignocellulosic biomass is the only realistic, near-term and non-food-competitive source of renewable organic carbon. To this end, legislative efforts, such as the US Renewable Fuel Standards, have been implemented to create subsidies, tax credits, mandates, and loan guarantees to help bring renewable fuel technologies to market. However, the representative body of industrial efforts to this end has faced significant challenges, with several startup companies having commercialized biomass conversion technologies but having struggled to reach commercial scale; in fact, many of these companies have filed for bankruptcy. This situation is likely due to the challenges associated with scaling up unproven pioneer processes, as well as neophyte investors not understanding the decade-long time frames and the sheer amount of funding that is often required to bring chemical process technologies to market. Nevertheless, several emerging catalytic technologies have either entered the market place, or are currently demonstrating their technologies in fully integrated pilot plants. Commercial and near commercial technologies for second generation biomass conversion technologies to-date include, among others: biomass-derived jet and diesel fuel from both waste vegetable oils and ethanol; small scale production of renewable jet and diesel from landfill gases via Fischer-Tropsch synthesis; catalytic conversion of carbohydrates into gasoline and aromatics; hydropyrolysis of biomass into gasoline and diesel, and; catalytic conversion of wood into aromatics. To be successful, biomass conversion technologies must ultimately be able to compete economically with petroleum technologies, which are already operating at large commercial scales and have been practiced for decades. To this end, various factors must be considered when evaluating the potential for new processes to compete with incumbent technologies; factors such as regional variations in feedstock quality and availability, government policy, subsidies and tax rates, and the proprietary positions of the ancillary technologies that might support the process. By any measure, however, a critical metric of the economic potential of a process is its efficiency with respect to the yield of products from raw materials, and this metric of performance is directly related to atom efficiency of the underlying chemical reactions. Therefore, while promising biomass conversion technologies continue to demonstrate progress towards commercialization, there remains an important need for the catalysis community to aid in this effort by: (1) designing more active, selective and stable catalysts, and (2) elucidating a more detailed understanding of the catalytic chemistries underlying these processes. Indeed, the study of catalytic biomass conversion has grown tremendously during the past decade; and new or emerging technologies that are in the laboratory stage have allowed for biomass to be converted into a wider variety of commodity chemicals and the full range of liquid fuels that are produced from petroleum. The objective of this perspective is to highlight some of the ongoing, fundamental challenges with respect to the catalytic conversion of biomass into renewable products, and to provide insight as to how the catalysis community can overcome several of these challenges. It is our belief that, as an international academic community of catalysis researchers, we can (and must) work together to address these challenges, and to drive progress toward the production of next-generation renewable chemicals and fuels from biomass.

09 BIOMASS FUELS↗
DOE OSTI2021

Promoting Diels-Alder reactions to produce bio-BTX: Co-aromatization of textile waste and plastic waste over USY zeolite

Producing commodity aromatic hydrocarbons from textile waste is a promising approach to promote carbon neutrality and circular economy. Catalytic degradation of flax waste (FW) to generate furans and its subsequent Diels-Alder transformation to monocyclic aromatic hydrocarbons over USY zeolite were conducted. Experimental results indicated that USY catalyzed FW resulted in a 5.5-fold increase in furans production compared with the non-catalytic trial. The Si/Al molar ratio in USY played a determining role in furans formation, and a 5-fold increase was observed over USY with a Si/Al ratio of 5.3 as opposed to that with a Si/Al ratio of 11. Plastic waste, polyethylene (PE), co-fed with FW yielded 1.6 times higher aromatic hydrocarbons than polypropylene (PP). The selectivity to aromatic hydrocarbons reached 81.6% under 20% PE co-fed with 80% FW, in which benzene, toluene, and xylenes (BTX) were predominant products with the maximum selectivity of 68%. Furthermore, this study presents a cleaner approach for value-added resource recovery and sustainable management of textile and plastic waste.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Comparative life cycle analysis on ethylene production from electrocatalytic reduction of carbon dioxide

Ethylene is one of the largest greenhouse gas emitters and the most diversly used commodity chemicals globally. Electrocatalytic reduction of CO 2 to ethylene received great attention from the research society to decarbonize the ethylene production. Here, in this study, a life-cycle analysis is conducted using the Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model on the three electrocatalytic CO 2 -reduction pathways (or “e-ethylene” pathways): i) cascade conversion via carbon monoxide intermediate; ii) single-step conversion in membrane electrode assembly (MEA); and iii) single-step conversion in alkaline flow cell. The results showed that the electricity consumption is the lowest for the cascade pathway (164 MJ/kg), thus resulting in the lowest cradle-to-gate carbon intensity [18 kgCO 2 e/kg with United States (US) average grid)] among the three pathways followed by the single-step MEA (32 kgCO 2 e/kg) and then by the single-step alkaline (56 kgCO 2 e/kg). However, all three e-ethylene pathways were significantly more carbon-intensive than their fossil-based counterpart (1.1 kgCO 2 e/kg) due to their excessive energy consumption with the current state of technology. With renewable electricity, all three pathways yielded negative carbon intensity: from -3.1 kgCO 2 e/kg to -1.6 kgCO 2 e/kg depending on the source of CO 2 . The threshold carbon intensity of electricity (TCIE), defined as the upper bound of the carbon intensity of electricity to achieve lower carbon intensity for e-ethylene compared to fossil-based ethylene, is calculated for both current and future state of e-ethylene technologies. The cascade pathway had the highest TCIE out of the three e-ethylene pathways for both current (92 gCO 2 e/kWh) and future (124 gCO 2 e/kWh) state of technologies. However, the carbon intensity of average US grid (i.e., 467 and 303 gCO 2 e/kWh for current and future projections) were higher than the TCIEs of the corresponding timeline. Thus, reducing electricity requirement for e-ethylene pathways and bringing low-carbon generation mix in the United States (US) grid faster than the current projection are both essential to decarbonize ethylene and its downstream chemicals/polymers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Valorization of waste polyolefins to butene, unsaturated fatty alcohols, and branched alkenes using CO 2 and plasma catalyst

Butene, branched alkenes, and short-chain unsaturated fatty alcohols are among the chemicals that have a wide range of industrial applications in the production of fuels, chemicals, and polymers. In this work, we produced these valuable commodity chemicals from waste plastics using a single-step plasma-catalytic process at atmospheric pressure CO 2 . The study shows that combining non-thermal plasma and zeolite could convert polyolefins at a temperature of 200 °C within 15 minutes, producing liquids rich in C 5 and C 6 branched alkenes and C 6 -C 8 unsaturated fatty alcohols. Additionally, gaseous products include a high yield of butene. Comparative studies indicate that combining CO 2 plasma with zeolite synergistically increases reaction rates and alters product compositions. Product selectivity was strongly dependent on reaction conditions, including plasma power, gas flow rates, reactor temperature, and catalyst loading. Furthermore, this process was applicable to common polyolefins and post-consumer polyethylene, indicating that the plasma catalytic approach has promising potential to valorize waste plastics and greenhouse gas CO 2 into versatile chemicals.

42 ENGINEERING↗
DOE OSTI2011

Development of a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI)

Satellite-observed radiance is a nonlinear functional of surface properties and atmospheric temperature and absorbing gas profiles as described by the radiative transfer equation (RTE). In the era of hyperspectral sounders with thousands of high-resolution channels, the computation of the radiative transfer model becomes more time-consuming. The radiative transfer model performance in operational numerical weather prediction systems still limits the number of channels we can use in hyperspectral sounders to only a few hundreds. To take the full advantage of such high-resolution infrared observations, a computationally efficient radiative transfer model is needed to facilitate satellite data assimilation. In recent years the programmable commodity graphics processing unit (GPU) has evolved into a highly parallel, multi-threaded, many-core processor with tremendous computational speed and very high memory bandwidth. The radiative transfer model is very suitable for the GPU implementation to take advantage of the hardware's efficiency and parallelism where radiances of many channels can be calculated in parallel in GPUs. In this paper, we develop a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI) launched in 2006 onboard the first European meteorological polar-orbiting satellites, METOP-A. Each IASI spectrum has 8461 spectral channels. The IASI radiative transfer model consists of three modules. The first module for computing the regression predictors takes less than 0.004% of CPU time, while the second module for transmittance computation and the third module for radiance computation take approximately 92.5% and 7.5%, respectively. Our GPU-based IASI radiative transfer model is developed to run on a low-cost personal supercomputer with four GPUs with total 960 compute cores, delivering near 4 TFlops theoretical peak performance. By massively parallelizing the second and third modules, we reached 364x speedup for 1 GPU and 1455x speedup for all 4 GPUs, both with respect to the original CPU-based single-threaded Fortran code with the -O{sub 2} compiling optimization. The significant 1455x speedup using a computer with four GPUs means that the proposed GPU-based high-performance forward model is able to compute one day's amount of 1,296,000 IASI spectra within nearly 10 min, whereas the original single CPU-based version will impractically take more than 10 days. This model runs over 80% of the theoretical memory bandwidth with asynchronous data transfer. A novel CPU-GPU pipeline implementation of the IASI radiative transfer model is proposed. The GPU-based high-performance IASI radiative transfer model is suitable for the assimilation of the IASI radiance observations into the operational numerical weather forecast model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs

This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O(N) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Finite difference numerical method for the superlattice Boltzmann transport equation and case comparison of CPU(C) and GPU(CUDA) implementations

We present a finite difference numerical algorithm for solving two dimensional spatially homogeneous Boltzmann transport equation which describes electron transport in a semiconductor superlattice subject to crossed time dependent electric and constant magnetic fields. The algorithm is implemented both in C language targeted to CPU and in CUDA C language targeted to commodity NVidia GPU. We compare performances and merits of one implementation versus another and discuss various software optimisation techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A review on advances in oxidative coupling of methane (OCM) for industrial use and prospects of CO 2 –H 2 O splitting integration

The discovery of shale gas reserves has encouraged the development of direct methods for methane conversion into valuable chemicals, offering an alternative to indirect approaches that involve an energy-intensive and intermittent syngas production step, leading to high CO 2 emissions. Amongst the direct methods, the oxidative coupling of methane (OCM) is a potential pathway to reduce CO 2 emissions and can produce commodity chemicals such as ethylene, a chemical regarded as central to the petrochemical industry. Even though OCM has been studied for over four decades, the technology still has not found commercial application. Amongst the challenges regarding industrial deployment of OCM, the most significant one is the requirement of a high ethylene yield of 30 % which is currently reported to be around 20 %. Moreover, the highly exothermic nature of the process and controlling the carbon selectivity over oxides of carbon (COx) is the heart of the problem. Numerous researchers have presented promising results in terms of catalysts, reactor designs and feeding strategies for OCM. However, due to lack of inclusiveness in the results, none of the combination of catalysts, reactors and system optimizations has been able to bring about its industrial viability. The current paper presents an extensive review of the noteworthy attempts to achieve industrial targets for OCM. Moreover, a comprehensive criteria is presented which highlights the desired end state for the industrial deployment of OCM technology. Furthermore, the criteria is based on literature survey and a comparison with industrially deployed ethylene production plants i.e., naphtha or ethane steam cracker plants. Finally, a novel integration technology is presented which includes a combination of OCM and CO 2 -H 2 O splitting in a chemical looping reactor design to enable efficient energy utilization and minimal heat losses to the environment.

CO2 Splitting↗
DOE OSTI2024

Electrochemical sulfate production from sulfide-containing wastewaters and integration with electrochemical nitrogen recovery

Electrochemical methods can help manage sulfide in wastewater, which poses environmental and health concerns due to its toxicity, malodor, and corrosiveness. In addition, sulfur could be recovered as fertilizer and commodity chemicals from sulfide-containing wastewaters. Wastewater characteristics vary widely among wastewaters; however, it remains unclear how these characteristics affect electrochemical sulfate production. Here, in this study, we evaluated how four characteristics of influent wastewaters (electrolyte pH, composition, sulfide concentration, and buffer strength) affect sulfide removal (sulfide removal rate, sulfide removal efficiency) and sulfate production metrics (sulfate production rate, sulfate production selectivity). We identified that electrolyte pH (3 × difference, i.e., 25.1 to 84.9 μM h –1 in average removal rate within the studied pH range) and sulfide concentration (16 × difference, i.e., 82.1 to 1347.2 μM h –1 in average removal rate) were the most influential factors for electrochemical sulfide removal. Sulfate production was most sensitive to buffer strength (6 × difference, i.e., 4.4 to 27.4 μM h –1 in average production rate) and insensitive to electrolyte composition. Together, these results provide recommendations for the design of wastewater treatment trains and the feasibility of applying electrochemical methods to varying sulfide-containing wastewaters. In addition, we investigated a simultaneous multi-nutrient (sulfur and nitrogen) process that leverages electrochemical stripping to further enhance the versatility and compatibility of electrochemical nutrient recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Remote visual analysis of large turbulence databases at multiple scales

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Who Did the Ethanol Tax Credit Benefit? An Event Analysis of Subsidy Incidence

At the end of 2011, the Volumetric Ethanol Excise Tax Credit (VEETC), which had subsidized the blending of ethanol in gasoline, was allowed to expire. During its tenure, the subsidy was the subject of intense scrutiny concerning who benefited from its existence. Using commodity price data, we estimate the subsidy incidence accruing to corn farmers, ethanol producers, gasoline blenders, and gasoline consumers around the time of expiration. Our empirical approach contributes methodologically to the event studies literature by analyzing futures contract prices (as opposed to spot prices) when possible. Ultimately, we find compelling evidence that, at the date of VEETC expiration, ethanol producers captured about 25 cents of the 45 cents subsidy per gallon of ethanol blended. We find suggestive, albeit inconclusive, evidence that a portion of this benefit (about 5 cents per gallon) was passed further upstream from ethanol producers to corn farmers. Most of the remainder seems most likely to have been captured by the blenders themselves. On the petroleum side, we find no evidence that oil refiners captured any part of the subsidy. We also find no evidence that the subsidy was passed downstream to gasoline consumers in the form of lower gasoline prices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The many phases of CaC{sub 2}

Polymorphic CaC{sub 2} was prepared by reacting mixtures of CaH{sub 2} and graphite with molar ratios between 1:1.8 and 1:2.2 at temperatures between 700 and 1400 °C under dynamic vacuum. These conditions provided a well controlled, homogeneous, chemical environment and afforded products with high purity. The products, which were characterized by powder X-ray diffraction, solid state NMR and Raman spectroscopy, represented mixtures of the three known polymorphs, tetragonal CaC{sub 2}-I and monoclinic CaC{sub 2}-II and -III. Their proportion is dependent on the nominal C/CaH{sub 2} ratio of the reaction mixture and temperature. Reactions with excess carbon produced a mixture virtually free from CaC{sub 2}-I, whereas high temperatures (above 1100 °C) and C-deficiency favored the formation of CaC{sub 2}-I. From first principles calculations it is shown that CaC{sub 2}-I is dynamically unstable within the harmonic approximation. This indicates that existing CaC{sub 2}-I is structurally/dynamically disordered and may possibly even occur as slightly carbon-deficient phase CaC{sub 2-δ}. It is proposed that monoclinic II is the ground state of CaC{sub 2} and polymorph III is stable at temperatures above 200 °C. Tetragonal I represents a metastable, heterogeneous, phase of CaC{sub 2}. It is argued that a complete understanding of the occurrence of three room temperature modifications of CaC{sub 2} will require a detailed characterization of compositional and structural heterogeneities within the high temperature form CaC{sub 2}-IV, which is stable above 450 °C. The effect of high pressure on the stability of the monoclinic forms of CaC{sub 2} was studied in a diamond anvil cell using Raman spectroscopy. CaC{sub 2}-II and -III transform into tetragonal CaC{sub 2}-I at about 4 and 1GPa, respectively. - Graphical abstract: The famous tetragonal form of CaC{sub 2}, CaC{sub 2}-I, is dynamically unstable. Why does it exist? Display Omitted - Highlights: • Critical review of complex polymorphism of the commodity chemical CaC{sub 2}. • Tetragonal CaC{sub 2}-I is identified as dynamical instable and its existence attributed to disorder. • With pressure monoclinic CaC{sub 2}-II and –III transform into tetragonal CaC{sub 2}-I. • The high temperature form CaC{sub 2}-IV is assigned a key role for understanding the polymorphism of CaC{sub 2}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

High entropy alloys as catalysts: A focused review

A brief literature review of recent experimental and computational efforts on the use of high entropy alloys (HEAs) as catalysts is presented, while also sharing some perspectives and future insights. To fully broach the vast compositional possibilities of HEA materials, integrating computational modeling with high-throughput experimental synthesis and validation is necessary to accelerate their design and development. Once identified, specific HEAs can be a class of materials for the next generation of catalysts when addressing global challenges related to energy independence, commodity chemical production, environmental remediation, abating emissions, and modernized domestic supply chain resilience.

42 - ENGINEERING↗
DOE OSTI2021

Design of a bifunctional TEMPO-tertiary amine mesoporous silica catalyst for the three-step cascade synthesis of a chromene derivative

A key challenge is design of materials and processes whereby competing reagents or conditions do not harm the multi-step sequence, thus allowing for more efficient chemical synthesis with elimination of work-up and separation steps. In this work, a three-step reaction cascade is performed using a porous bifunctional dimethylpropylamine-TEMPO-MCM41 catalyst, converting the commodity chemicals benzyl alcohol, sodium hypochlorite, and malononitrile to a biologically active anti-cancer, and anti-malarial 2-amino-chromene derivative. The cascade first utilizes a TEMPO-catalyzed oxidation of benzyl alcohol to benzaldehyde with NaOCl as the terminal oxidant. This is followed by a two-step, dual base catalyzed Knoevenagel condensation with malononitrile followed by a Michael addition with lawsone. Optimal conditions converting benzyl alcohol to 2-amino-5,10-dioxo-4-phenyl-5,10-dihydro-4H-benzo[g]chromene-3-carbonitrile include the delayed addition of malononitrile and lawsone during the three-step reaction sequence, which results in a 2-amino-chromene yield of over 80%. The importance of stepwise reagent addition is rationalized due to the unfavorable adsorption of acidic lawsone on the surface-grafted base catalyst. Tertiary Brønsted base sites of dimethylpropylamine outperform the more Lewis basic primary propylamine functionalized catalyst. This work outlines a simple and effective method for generating mesoporous materials with two types of active sites via co-condensation and thiol-ene coupling procedures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗