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Processes and systems for the energy efficient capture of CO 2 from a flue gas stream such as produced or resulting from power plant operation, are provided. The processes and systems integrate the use of high CO 2 /N 2 selectivity membranes and high CO 2 flux membranes, to capture CO 2 . Useful membranes can desirably be graphene oxide-based membranes.
In the real-time optimization operation process of the integrated energy system, digital twin (DT) can support operators to find optimal dispatching strategy. In this research, the DT framework interfacing (external) system-level simulation model, RAVEN, and Python-based optimization framework has been developed. Simple demonstration of finding optimal input values minimizing an objective function with the DT framework has been presented.
The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112) EV-ChART will provide a streamlined data submission process and an integrated set of analytic tools, connect to other data sources, and empower data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112. The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow.
Nuclear energy has been an important source of power throughout the world for several decades, but with that power comes substantial amounts of waste. The USA alone is projected to produce 77,100 MTHM (34,700 MCi) of commercial spent fuel by the year 2020. There has been a growing sense of urgency to determine a method of disposal for all types of nuclear waste. Underground storage has been proposed as the safest means of long term storage and disposal by both the Academy of Sciences and the Blue Ribbon Commission with a focus on deep geologic disposal. Because deep geological repositories (DGR) pose as the safest method of disposal due to the isolation of the waste and the low-permeability of the surrounding material, it is crucial to understand the science behind these repositories. Many scientists have concern with DGRs because of all the unanswered scientific questions. With a global inventory of 300,000 MTHM, it is imperative to understand how DGRs will retain the nuclear waste over a time span of up to a projected 1 million years. Because of the amount of nuclear waste increases each year, there is an inherent need to study the viability of a repository in order to begin implementation of that repository. Based on the half-lives of each radionuclide in nuclear waste, after approximately 100 years of storage, the heat production from the decay of radionuclides becomes dominated by the long-lived actinides. Because the decay of the nuclear waste results in an elevated temperature within the canister, That mixed with water intrusion can corrode the canister and allow radionuclides to leach into the surrounding environment. In an effort to retain these radionuclides within the repositories, most all deep geologic repository designs incorporate an engineered multi-barrier approach. Once the radionuclides begin to leach out of the canisters, the next barrier to retain them is a layer of compacted clay such as a smectite. A mechanistic understanding of mobility at elevated temperatures is crucial in order to evaluate the performance of the engineered clay barrier system within a deep geological repository. Because the clay barrier is compacted so tightly, the only method of mobility for radionuclides is through molecular diffusion. Assessing the factors that affect the rates at which various radionuclides will diffuse through these clays is important in the performance assessment of the repository system as a whole. Neptunium-237 has been identified as a major actinide of concern for long term storage, dominating the radioactivity emitted from the waste between 10,000 to 100,000 years of storage. Under oxidizing conditions, this radionuclide exists mainly as Np(V). In this oxidation state, the neptunium exists chemically as the NpO{sub 2}{sup +} ion which exhibits enhanced mobility characteristics such as high solubility and low affinity for sorption to surfaces. Because of this, {sup 237}Np(V) has been identified as the most mobile radionuclide in nuclear waste and thus a major radionuclide of concern, motivating research into the mobility of {sup 237}Np(V) through the compacted clay barrier. Bentonite is one of the most common backfill materials used in repositories. This clayey rock's main constituent is the mineral Na-montmorillonite [(Ca{sub 0.06}Na{sub 0.14}K{sub 0.05})(Al{sub 1.57}Fe{sup 3+} {sub 0.17}Mg{sub 0.25})(Al{sub 0.04}Si{sub 3.96}O{sub 10} - (OH){sub 2})] which gives this material the advantageous properties required for a repository such as a high swelling capacity. Because of this high affinity for absorbing water, montmorillonite is the ideal candidate for backfill material in a deep geological repository. Adsorption of radionuclides onto the surface of the compacted clay is a major mechanism for retardation of mobility. Because diffusion and adsorption are integrated into this process, it is important to characterize Np adsorption onto the surface of compacted montmorillonite. Previous studies have quantified the adsorption of Np onto montmorillonite at variable ionic strengths and temperatures. Furthermore, several studies have focused on the diffusion of Np through compacted clay, but no other studies have determined diffusion coefficients at elevated temperatures of up to 80 deg. C. (authors)
The goal of this project is to develop a prototype system that integrates the capture and catalytic hydrogenation of CO 2 into methanol in the same solvent. Ultimately, this integrated approach could provide a technology with projected reductions to capital and operating costs by at least 20% relative to a benchmark methanol synthesis via gas-phase CO 2 hydrogenation. There were five primary objectives for the project: 1. Optimize the selections of both the catalysts and the CO 2 capture solvents to achieve high conversion (>80%) and high selectivity (>90%) toward methanol in the targeted processing ranges (100-180°C, 1-60 bar). 2. Design a reactor system that provides a fixed catalyst surface area and high-efficiency heat exchange to assure compact modular processing. 3. Build and test a reactor system and demonstrate in a bench scale continuous flow system, and use the operating data to refine the comparison to existing conversion technologies. 4. Refine techno economic (TEA) and Tech-to-Market (TTM) analyses using the experimental data obtained from the bench-scale system. 5. Use the experimental data and TEA/TTM projections to develop a conceptual design for a pre-commercial system that targets a specific market opportunity.
Post-combustion CO 2 capture (PCC) technology offers flexibility to treat the flue gas from both existing and new coal-fired power plants and can be applied to treat all or a portion of the flue gas. Solvent-based technologies are today the leading option for PCC from commercial coal-fired power plants as they have been applied in large-scale in other applications. Linde and BASF have been working together to develop and further improve a PCC process incorporating BASF’s novel aqueous amine-based solvent technology. This technology offers significant benefits compared to other solvent-based processes as it aims to reduce the regeneration energy requirements using novel solvents that are very stable under the coal-fired power plant feed gas conditions. BASF has developed the desired solvent based on the evaluation of a large number of candidates. In addition, long-term small pilot-scale testing of the BASF solvent has been performed on a lignite-fired flue gas. In coordination with BASF, Linde has evaluated a number of options for capital cost reduction in large engineered systems for solvent-based PCC technology. This report provides a summary of the work performed and results from a project supported by the US DOE (DE-FE0007453) for the pilot-scale demonstration of a Linde-BASF PCC technology using coal-fired power plant flue gas at a 1-1.5 MWe scale in Wilsonville, AL at the National Carbon Capture Center (NCCC). Following a project kick-off meeting in November 2011 and the conclusion of pilot plant design and engineering in February 2013, mechanical completion of the pilot plant was achieved in July 2014, and final commissioning activities were completed to enable start-up of operations in January 2015. Parametric tests were performed from January to December 2015 to determine optimal test conditions and evaluate process performance over a variety of operation parameters. A long-duration 1500-hour continuous test campaign was performed from May to August 2016 at a selected process condition to evaluate process performance and solvent stability over a longer period similar to how the process would operate as a continuously running large-scale PCC plant. The pilot plant integrated a number of unique features of the Linde-BASF technology aimed at lowering overall energy consumption and capital costs. During the overall test period including startup, parametric testing and long-duration testing, the pilot plant was operated for a total of 6,764 hours out of which testing with flue gas was performed for 4,109 hours. The pilot plant testing demonstrated all of the performance targets including CO 2 capture rate exceeding 90%, CO 2 purity exceeding 99.9 mol% (dry), flue gas processing capacity up to 15,500 lbs/hr (equivalent to 1.5 MWe capacity slipstream), regeneration energy as low as 2.7 GJ/tonne CO 2 , and regenerator operating pressure up to 3.4 bara. Excellent solvent stability performance data was measured and verified by Linde and BASF during both test campaigns. In addition to process data, significant operational learnings were gained from pilot tests that will contribute greatly to the commercial success of PCC. Based on a thorough techno-economic assessment (TEA) of the Linde-BASF PCC process integrated with a 550 MWe supercritical coal-fired power plant, the net efficiency of the integrated power plant with CO 2 capture is increased from 28.4% with the DOE/NETL Case 12 reference to 30.9% with the Linde-BASF PCC plant previously presented utilizing the BASF OASE® blue solvent [Ref. 4], and is further increased to 31.4% using a Linde-BASF PCC plant with BASF OASE® blue solvent and an advanced stripper interstage heater (SIH) configuration. The Linde-BASF PCC plant incorporating the BASF OASE® blue solvent also results in significantly lower overall capital costs, thereby reducing the cost of electricity (COE) and cost of CO 2 captured from $147.25/MWh and $56.49/MT CO 2 , respectively, for the reference DOE/NETL Case 12 plant, to $128.49/MWh and $41.85/MT CO2 for process case LB1, respectively, and $126.65/MWh and $40.66/MT CO 2 for process case SIH, respectively. With additional innovative Linde-BASF PCC process configuration improvements, the COE and cost of CO 2 captured can be further reduced to $125.51/MWh and $39.90/MT CO 2 for a further optimized PCC process defined as LB1-CREB. Most notably, the Linde-BASF process options assessed have already demonstrated the potential to lower the cost of CO 2 captured below the DOE target of $40/MT CO 2 at the 550 MWe scale for second generation PCC technologies. Project organization, structure, goals, tasks, accomplishments, process criteria and milestones will be presented in this report along with highlights and key results from parametric and long-duration testing of the Linde-BASF PCC pilot. The parametric and long-duration testing campaigns were aimed at validating the performance of the PCC technology against targets determined from a preliminary techno-economic assessment. The stability of the solvent with extended operation in a realistic power plant setting was measured with performance verified. Additionally, general solvent classification information, process operating conditions, normalized solvent performance data, solvent stability test results, flue gas conditions data, CO 2 purity data in the gaseous product stream, steam requirements and process flow diagrams, and updated process economic data for a scaled-up 550 MWe supercritical power plant with CO 2 capture are presented and discussed in this report.
This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.
A low-temperature synthesis coupled with mild activation produces zeolite films exhibiting low dielectric constant (low-k) matching the theoretically predicted and experimentally measured values for single crystals. This synthesis and activation method allows for the fabrication of a device consisting of a b-oriented film of the pure-silica zeolite MFI (silicalite-1) supported on a gold-coated silicon wafer. The zeolite seeds are assembled by a manual assembly process and subjected to optimized secondary growth conditions that do not cause corrosion of the gold underlayer, while strongly promoting in-plane growth. The traditional calcination process is replaced with a non-thermal photochemical activation to ensure preservation of an intact gold layer. The dielectric constant (k), obtained through measurement of electrical capacitance in a metal-insulator-metal configuration, highlights the ultralow k approximate to 1.7 of the synthetized films, which is among the lowest values reported for an MFI film. There is large improvement in elastic modulus of the film (E approximate to 54 GPa) over previous reports, potentially allowing for integration into silicon wafer processing technology.
In this work, we present an integrated approach to synthesize process intensification systems with guaranteed flexibility and safety performances. The synthesis of intensified equipment/flowsheets is addressed through the Generalized Modular Representation Framework (GMF), which utilizes an aggregation of multifunctional mass/heat exchange modules to represent chemical processes. Thus, the optimal design options are investigated as mass- and heat-transfer opportunities using superstructure-based optimization techniques without a prepostulation of plausible configurations. To ensure that the designs can be operated under a specified range of uncertain parameters, a multiperiod GMF representation is developed based on the critical operating conditions identified by flexibility test. Risk assessment, accounting for equipment failure frequency and consequence severity, is incorporated as a constraint into this synthesis model to derive inherently safer designs. The resulting safely operable intensified systems, which are represented via phenomenological modules, are then identified as corresponding equipment-based flowsheets and validated with steady-state simulation. We demonstrate the proposed approach through a case study for the production of methyl tert-butyl ether. Here, the results indicate that safety and operability considerations can result in significant changes in the structural and operating parameters of the optimal intensified design configuration.
The National Renewable Energy Laboratory (NREL) and Acciona Energy USA Global are developing and implementing a process that addresses the issue of hydrogen buildup in parabolic trough power plants. Our method selectively removes hydrogen from the expansion tanks of the power plant to control hydrogen levels in the circulating heat-transfer fluid (HTF). As part of this effort, we developed a sensor that measures hydrogen partial pressure in the expansion-tank headspace gas. During previous work, we demonstrated that our sensor measures hydrogen levels over a wide range of partial pressure from 1.33 mbar down to 0.003 mbar. In this paper, we report our most recent work, in which we conceived and developed an integrated process module that performs both hydrogen sensing and separating functions. The sensor/separator measures hydrogen partial pressure in the headspace gas in the same way as our original sensor design. Additionally, the integrated module separates hydrogen from the headspace gas to reduce hydrogen to the level needed to maintain the performance of receivers in the collector field. Sensor data from the integrated module also provide an estimate of the rate at which hydrogen is being extracted from the headspace gas. We designed and fabricated a laboratory-scale integrated module and determined its performance in our laboratory at NREL. Testing showed that the module performed as expected in both sensing and separating modes. The accuracy of the sensing function was +/-10%. The hydrogen extraction rate for the separating mode was consistent with our modeling predictions. The primary benefit of this module is its simple design, both in terms of function and incorporation into the HTF subsystem of the power plant. The integrated module can be installed close to the HTF expansion tanks, where it draws headspace gas from the tanks, removes hydrogen, and returns the treated gas back to the tanks. We are currently installing a test-scale process at the Nevada Solar One (NSO) power plant to demonstrate this process and determine its operational performance. Results from the test-scale process will be used to specify and design the full-scale process that will be installed at NSO.
Bacterial decomposition of organic matter in soils is generally believed to be mainly controlled by the access bacteria have to organic substrate. The influence of bacterial traits on this control has, however, received little attention. Using the substrate-dependent Monod growth model, we develop a bioreactive transport model to screen the interactive impacts of spatial dispersion and bacterial traits on mineralization. Bacterial traits primarily involved in the bacterial response to the substrate concentration, such as the maximum specific uptake rate and efficiency, the adaptation time of the uptake rate and the initial population density, are considered. We compare the model results with two sets of previously performed cm-scale soil-core experiments in which the mineralization of the pesticide 2,4-D was measured under well-controlled initial distributions and transport conditions. Bacterial dispersion away from the initial substrate location induced a significant increase in 2,4-D mineralization. Additionally, it reveals an increase of specific uptake rates at lower bacterial densities, more than compensating the decrease of specific uptake rates caused by substrate dilution. This regulation of bacterial activities by density, caused by the local depletion of substrate by competing bacteria, becomes dominant for bacteria with an efficient uptake of substrate at low substrate concentrations (a common feature of oligotrophs). Such oligotrophs, commonly found in soils, compete with each other for substrate even at remarkably low population densities. The ratio-dependent Contois growth model, which includes a density regulation in the expression of the uptake efficiency, is more accurate and convenient to calibrate than the substrate-dependent Monod model, at least under these conditions. In view of their strong interactions, bioreactive and transport processes cannot be handled independently but should be integrated, in particular when reactive processes of interest are carried out by oligotrophs.
Purpose: This study investigated the effect of accumulated dose on radiophotoluminescent glass dosimeter in megavoltage photon. Methods: 45 commercially-available radio-photoluminescence glass dosimeters (RPLGD; GD-302M, Asahi Techno Glass Co., Shizuoka, JAPAN) were irradiated to 10 × 10 cm{sup 2} open-field with 6, 10 and 15 MV photon beams at 100 cm of source to surface distance and dose maximum depths. Each energy has consists of five groups which is consists of three detectors. A group #1 and #2 was irradiated about 1 Gy to 100 Gy, and estimated the integral dose response with and without annealing procedure. A group #3 was read the dose after irradiated 10 Gy of dose by 10 times repeatedly to estimate the fading effect of RPLGD. A group #4 and #5 was produced same ways with different irradiation dose such as 50 Gy for group #4 and 100 Gy for group #5. Results: From the results of group #1 and #2, an annealed detector shows linear response to integral dose but other detectors without the annealing process, has supra linearity for integral dose especially close to 100 Gy dose. For group #3, #4 and #5, the dose response of repeated irradiation, the dose response was decreased about 15%, 12% and 7% for 6 MV, 10 MV and 15MV. Conclusion: It was found that RPLGD response to accumulated dose was supra linear and this respond was altered with amount of accumulated dose to the RPLGD. In addition, the fading effect need to be concern with RPLGD.
In accordance with the requirements of U.S. Department of Energy (DOE) Order 413.3A, “Program and Project Management for the Acquisition of Capital Assets,” safety must be integrated into the design process for new or major modifications to DOE Hazard Category 1, 2, and 3 nuclear facilities. The intended purpose of this requirement involves the handling of hazardous materials, both radiological and chemical, in a way that provides adequate protection to the public, workers, and the environment. Requirements provided in DOE Order 413.3A and DOE Order 420.1C, “Facility Safety,” and the expectations of DOE-STD-1189-2008, “Integration of Safety into the Design Process,” provide for identification of hazards early in the project and use of an integrated team approach to design safety into the facility. This safety design strategy provides the basic safety-in-design principles and concepts that will be used for the Remote-Handled Low-Level Waste Disposal Project.
Plant organs and tissues contain multiple cell types, which are well organized in 3-dimensional structure to efficiently perform physiological functions such as homeostasis, response to environmental perturbation, pathogen infection. It is critically important to perform molecular measurements at the cell-type-specific level to discover mechanisms and unique features of cell populations that govern differentiation and respond to external perturbations. Although mass spectrometry-based proteomics has been demonstrated as an enabling discovery tool to study plant physiology, conventional approaches require millions of cells to generate robust biological conclusions. Such requirements mask the cell-to-cell heterogeneities and limit the comprehensive profiling of plant proteins at spatially resolved and cell-type-specific resolutions. This protocol describes a recently-developed proteomics workflow for studying a small number of plant cells by integrating laser capture microdissection, microfluidic nanodroplet-based sample preparation, with ultrasensitive liquid chromatography-mass spectrometry. Using poplar as a model tree species, we provide detailed protocols, including plant tissue harvest, tissue preparation, cryosectioning, laser microdissection, protein digestion, mass spectrometry measurement, and data analysis. We show the workflow enables the precise identification and quantification of thousands of proteins from hundreds of isolated plant root and leaf cells.
The report provides research summaries of two developed theories: data projection to enable multi-scale facility digital interactions and introducing the Evaluation Model Development and Assessment Process (EMDAP) approach to Integrated Energy Systems (IES) design. For the data projection, a two-system scaling case including interactions between thermal storage and hydrogen production is provided. The corresponding facilities are the thermal energy distribution system (TEDS) facility and high temperature steam electrolysis (HTSE) facility at the Dynamic Energy Transport and Integration Laboratory (DETAIL) in Idaho National Laboratory (INL). For the EMDAP adaption to system design, a modified process of the EMDAP was developed and applied to indirect two-tank heat storage system design. System phenomena were identified, ranked, and scaled to discover helpful key relations that would determine the ideal component geometry.
This work is a continuation of a previous effort (Panaitescu) to study the cooling of relativistic electrons through radiation (synchrotron and self-Compton) emission and adiabatic losses, with application to the spectra and light curves of the synchrotron gamma-ray burst (GRB) produced by such cooling electrons. Here, we derive the low-energy slope β LE of a GRB pulse-integrated spectrum and quantify the implications of the measured distribution of β LE . Radiative processes that produce soft integrated spectra can accommodate the harder slopes measured by CGRO/BATSE and Fermi/GBM only if the magnetic field lifetime t B is shorter than the time during which the typical GRB electrons cool to radiate below 1–10 keV, which is less than (at most) 10 radiative cooling timescales t rad of the typical GRB electron. In this case, there is a one-to-one correspondence between t B and β LE . To account for low-energy slopes β LE > -3/4, the adiabatic electron-cooling requires a similar restriction on t B . In this case, the diversity of slopes arises mostly from how the electron-injection rate varies with time (temporal power-law injection rates yield power-law low-energy GRB spectra) and not from the magnetic field timescale.
This project developed an integrated substrate which organic light emitting diode (OLED) panel developers could employ the integrated substrate to fabricate OLED devices with performance and projected cost meeting the MYPP targets of the Solid State Lighting Program of the Department of Energy. The project optimized the composition and processing conditions of the integrated substrate for OLED light extraction efficiency and overall performance. The process was further developed for scale up to a low-cost process and fabrication of prototype samples. The encapsulation of flexible OLEDs based on this integrated substrate was also investigated using commercial flexible barrier films.
We present the first fully automated implementation of cross-section computation and event generation for loop-induced processes. This work is integrated in the MadGraph5_aMC@NLO framework. We describe the optimisations implemented at the level of the matrix element evaluation, phase space integration and event generation allowing for the simulation of large multiplicity loop-induced processes. Along with some selected differential observables, we illustrate our results with a table showing inclusive cross-sections for all loop-induced hadronic scattering processes with up to three final states in the SM as well as for some relevant 2 → 4 processes. Furthermore, many of these are computed here for the first time.