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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Economic and Jobs Impacts of Point-Source Carbon Capture in Cement Industry – Case Study

The cement industry accounts for an estimated 8% of global CO2 emissions, which surpasses that of the entire aviation sector. In contrast with other industries, where CO2 emissions can be drastically reduced via electrification or fuels substitution, cement production releases CO2 as part of its process, during the calcination of carbonates to yield oxides. Thus, point-source carbon capture has become a key technology in the cement industry’s decarbonization. Apart from the expected environmental benefits, point-source carbon capture in the cement industry can yield important economic benefits and create jobs. The objective of this study was to perform a preliminary assessment of the economic and workforce impacts associated with the construction and operation of a point-source carbon capture retrofit of an existing cement production facility, using as a basis the data from a front-end engineering design (FEED) study to install a 3.9 million metric tons per year (Mtpy) CO2 capture facility at Holcim Ste Genevieve cement plant in Missouri, United States of America. The advanced carbon capture technology used in this FEED study was Air Liquide’s Cryocap™ FG carbon capture technology. The study evaluated the direct, indirect, and induced economic impacts of the construction, operation, and maintenance activities of the project over its lifespan. It also covered how the project will generate new jobs, their nature, and quantity, along with strategies to prepare the workforce. To perform this study, construction, operation, and maintenance cost estimates, as well as construction and operation staffing plans from the FEED study were input into IMPLAN version 7.5 software, licensed by IMPLAN Group LLC (Huntersville, VC), to predict the direct, indirect and induced economic impacts of the project using industry multipliers from the software. Additionally, recruitment strategies were developed for hiring individuals who belong to groups that are historically underserved or underrepresented, as well as anticipated recruitment of workers from the local community (whether training will be required or if the skills are associated with an existing labor force). The analysis estimated that the construction and operation of the carbon capture at Holcim Ste. Genevive will result in over 24 thousand work-years of job opportunities, close to USD 10 billion of economic impacts, including over USD 460 million of tax revenue. These results encompass the direct, indirect, and induced effects. A strategy to maximize hiring from the project and neighboring counties was developed, leveraging training agreements with local trade groups and universities. The result of this study can be used for a strategic preliminary assessment of the potential regional economic and job impacts of retrofitting existing cement plants with point source carbon systems, and its methodology can be replicated to individual projects to aid in planning and workforce development.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Multi-Modal Characterization of Nuclear Fuels and Materials at the Idaho National Laboratory Materials & Fuels Complex

The Idaho National Laboratory (INL) leads cutting-edge research pertaining to the advancement of nuclear reactor technologies, including nuclear fuels and materials. The INL Irradiated Materials Characterization Laboratory (IMCL), Electron Microscopy Laboratory (EML), and future Sample Preparation Laboratory (SPL) are available to the nuclear research community to assess the behavior of nuclear fuels and materials, efficiently and comprehensively characterizing from the engineering to atomistic scale. The IMCL is a unique, 12,000-square-foot facility located at the INL Materials and Fuels Complex designed for analysis of irradiated materials. The facility operates advanced characterization instruments that are sensitive to vibration, temperature, and electromagnetic interference in modular radiological shielding and confinement systems, granting researchers the ability to assess the microstructural, chemical, mechanical and thermophysical properties of nuclear materials, especially irradiated fuels. The EML is dedicated to advanced characterization of materials with optical and electron microscopy tools, including scanning electron microscopy/focused-ion beam (SEM/FIB) and transmission electron microscopy (TEM). Upon construction, the SPL will be a 3 story, 49,000 sq. ft facility, that is the most modern reactor structural materials testing and analysis facility in the world, designed to investigate reactor structural materials in support of life-extension programs and development of advanced reactor concepts, including mechanical testing and advanced characterization capabilities. This presentation will showcase some of the main capabilities available at both IMCL, EML, and SPL, specifically illustrating how these characterization techniques are incorporated into multi-modal characterization work scopes to elucidate the degradation of nuclear structural materials and irradiated fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2023

Electron Target Cooling Analyses of the KIPT ADS Using MCNP and Ansys Fluent

This study presents multiphysics analyses of the electron target cooling system of the accelerator-driven system (ADS) of the Kharkiv Institute of Physics and Technology (KIPT) using MCNP and Fluent computer programs. MCNP has been used to transport electrons, gammas, and neutrons, and to calculate the energy deposition in the target materials. The MCNP mesh-tally data have been imported into Fluent by a C subroutine that has been compiled and linked to Fluent as a user-defined function.The KIPT ADS is located in Ukraine and was in operation until February 2022. The Fluent model is based on the computer-aided design files from the manufacturing process of the target assembly. Here, the Fluent results for the reference case match very well the literature results obtained by STAR-CCM+ during the design phase. Other cases that differ from the reference one have been analyzed; in these cases, it is assumed a malfunction of the electron accelerator or of the water cooling system. The target cooling system operates normally for all the analyzed cases except when the inlet water mass flow rate is decreased. The transient analysis showed that the target cooling system can operate for 180 s with full power when the inlet water mass flow rate is decreased down by 75%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Novel Algae Technology for CO2 Utilization

The United States, the world’s largest energy user and second largest CO2 emitter, is heavily dependent on fossil energy. In 2014, U.S. coal burning utilities emitted ~1562 million (MM) tons/year (TPY) of CO2 into the atmosphere, accounting for 76% of the total US power sector emissions1. Hence, reducing the CO2 emission footprint from coal plants is widely viewed as a key element in mitigating global warming. Despite significant interest, implementation of CO2 capture technologies has been constrained by the high capture cost which significantly increases the total cost of electricity. Not only is capturing CO2 with traditional technologies expensive, but generally the CO2 has little value and additional expense must be incurred for sequestration. This project funded by a SBIR grant from the U.S. D.O.E. to Helios-NRG in collaboration with the State University of New York at Buffalo (UB) and Membrane Technology and Research Inc. (MTR) aimed to develop a novel, algae based technology to capture CO2 from the effluent of coal-based power plants and convert it to renewable bio-fuels and higher value co-products such as animal feed and nutraceuticals with the potential to enable a substantial reduction in the net cost of carbon capture. The Phase 2 project was aimed at further demonstrating the technical feasibility of the proposed multi-stage continuous (MSC) flow CO2 capture system and the generation of high-value co-products to offset the CO2 capture cost. The project was completed and the project objectives were met and exceeded. A first-of-a-kind integrated, laboratory scale MSC process unit was fabricated and tested in a greenhouse. The tests were conducted with the preferred algae species identified in Phase I and simulated flue gas containing contaminants at levels typically present in the post flue gas desulfurization (FGD) stream, including ~12% CO2, acid gas (SOX, NOX), and a large number of heavy metals. The tests were successful and demonstrated a 25g/m2/day seasonal average algae productivity and an 80% CO2 capture efficiency. Two new algae species were identified for high-value nutraceutical production. Studies to improve growth rate and nutraceutical content of these algae species were performed and a pathway for further improvements was identified. A new dewatering technology called DeAqua was further advanced. Significant improvement in the performance index was achieved. The anti-fouling membrane was developed and fabricated into a module. The fabricated membrane module was tested with algae slurry and demonstrated improved fouling resistant properties, that can potentially reduce the cost and energy of the critical dewatering step. Test data were used to simulate operation of the overall process. The preliminary economic analysis was updated and modelled based on a 5000-acre algae farm. To the extent possible, the financial and operating assumptions used were the same as those used in the DOE’s 2022 projections for algae technology for CO2 capture and utilization. The results showed the proposed technology’s potential to significantly reduce the cost of CO2 capture compared to current options and that the high value products generated from the CO2 captured can make a step change in the cost of carbon capture. Plans to advance the technology to Phase 2B were developed and potential end-user partners were identified.

Maloney, James↗
DOE OSTI2024

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces

Learning operators between infinitely dimensional spaces is an important learning task arising in machine learning, imaging science, mathematical modeling and simulations, etc. This paper studies the nonparametric estimation of Lipschitz operators using deep neural networks. Non-asymptotic upper bounds are derived for the generalization error of the empirical risk minimizer over a properly chosen network class. Under the assumption that the target operator exhibits a low dimensional structure, our error bounds decay as the training sample size increases, with an attractive fast rate depending on the intrinsic dimension in our estimation. Our assumptions cover most scenarios in real applications and our results give rise to fast rates by exploiting low dimensional structures of data in operator estimation. We also investigate the influence of network structures (e.g., network width, depth, and sparsity) on the generalization error of the neural network estimator and propose a general suggestion on the choice of network structures to maximize the learning efficiency quantitatively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Techno-economic analysis of cathode material production using flame-assisted spray pyrolysis

The cost of cathode materials contributes approximately 32.7% of the total cell construction cost of lithium-ion batteries, significantly affecting the price of battery packs. To reduce the cathode material manufacturing cost, a flame-assisted spray pyrolysis (FSP) method has been developed to utilize a sustainable solvent of glycerol to manufacture the LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC333) cathode materials. The purpose of this study is to evaluate the minimum cathode material selling price (MCSP) of the FSP processes compared with a traditional carbonate co-precipitation pathway. Results show that the MCSP of the FSP is $\$$19.1/kg that is 17% lower than the traditional carbonate co-precipitation pathway as a result of lower fixed operating cost and variable overhead. Sensitivity analysis shows that when the new process is integrated with in-situ sintering and processing, the MCSP can be as low as $\$$15.6/kg. When all the material prices are decreased by 20%, the FSP process can synthesize NMC333 at a price of $\$$2.3/kg lower. According to the simulation result, LiNi 0·8 Mn 0·1 Co 0·1 O 2 (NMC811) has the best potential to meet the U.S. Department of Energy battery price target of $\$$125/kWh, demonstrating that the FSP process is an attractive manufacturing technology for NMC cathode powder material production.

25 ENERGY STORAGE↗
DOE OSTI2022

Advanced Reactor Control and Operations (ARCO): A University Research Facility for Developing Optimized Digital Control Rooms

The Advanced Reactor Control and Operations (ARCO) facility was constructed in January 2018 to serve as a test bed for advanced reactor control rooms and operator support systems. Since then, it has supported human-machine interface user experience research, fault detection and mitigation technology development, control room concept of operations development, and remote operations research. ARCO serves as the control room for the Compact Integral Effects Test (CIET) facility, which replicates the primary-side flow paths and thermal-hydraulic behavior of a fluoride-salt-cooled high-temperature reactor (FHR) using simulant fluids and scaling principles. New reactor designs feature different operating conditions and scenarios than those in existing reactors. ARCO supports the research and development of digital tools for operator communications, intuitive real-time data analysis, online health monitoring and prognostics, and control room cybersecurity. By integrating these different technologies, ARCO acts as a prototypical control system to iteratively develop methods and tools of operation in advanced small modular nuclear reactors. This paper describes the features of and challenges to operating advanced small modular reactors underlying the design basis for ARCO and its operator support systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes

Abstract The risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.

Chang, K. W.↗
DOE OSTI2025

Brazilian CBP - Technoeconomic analysis data

This data is related to the paper entitled "Techno-economic analysis of sugarcane bagasse and straw conversion into cellulosic ethanol via consolidated bioprocessing". That features the evaluation of sugarcane bagasse and straw conversion to ethanol at stand-alone facilities generating electricity from residues. The following scenarios were evaluated: Conventional, featuring hydrothermal pretreatment, fungal cellulase, and yeast fermentation (current commercial standard); Mid-term consolidated bioprocessing (CBP), relying on bagasse solubilization without pretreatment or cotreatment; and Mature CBP, incorporating cotreatment but no pretreatment and considering significant technological advance of the CBP. Available here are the spreadsheets used for Material and Energy balance calculation, Capital and Operational costs estimation and Cash flow analysis. Also available are the description and python code used for Monte Carlo analysis of the ethanol and capital investment variations. This data can be used as a source to implement other techno-economic analysis in the biorefinary context.

09 BIOMASS FUELS↗
DOE OSTI2023

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

DC distribution↗
DOE OSTI2025

Final Search for Short-Baseline Neutrino Oscillations with the PROSPECT-I Detector at HFIR

The PROSPECT experiment is designed to perform precise searches for antineutrino disappearance at short distances (7–9 m) from compact nuclear reactor cores. This Letter reports results from a new neutrino oscillation analysis performed using the complete data sample from the PROSPECT-I detector operated at the High Flux Isotope Reactor in 2018. The analysis uses a multiperiod selection of inverse beta decay neutrino interactions with reduced backgrounds and enhanced statistical power to set limits on electron neutrino disappearance caused by mixing with sterile neutrinos with 0.2–20 eV 2 mass splittings. Inverse beta decay positron energy spectra from six different reactor-detector distance ranges are found to be statistically consistent with one another, as would be expected in the absence of sterile neutrino oscillations. The data excludes at 95% confidence level the existence of sterile neutrinos in regions above 3 eV 2 previously unexplored by terrestrial experiments, including all space below 10 eV 2 suggested by the recently strengthened Gallium Anomaly. The best-fit point of the Neutrino-4 reactor experiment’s claimed observation of short-baseline oscillation is ruled out at more than 5 standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

TRANSP integrated modeling code for interpretive and predictive analysis of tokamak plasmas

This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Sensitivity Analysis and Effective Parametrization of PEM Fuel Cell Models

The cost of proton-exchange-membrane fuel cells (PEMFCs) remains a major hurdle in large-scale commercialization of this technology. To improve their performance and reduce cost, novel materials and electrode designs are continuously envisioned, e.g., non-PGM catalyst layers, ultra-thin Pt/Pt-Ni based catalyst layers, structured ionomer arrays or NSTF catalyst layers.1 Understanding the impact of these improvement strategies can be extremely time and cost intensive due to complex physical phenomena and large design space. We have previously developed a PEMFC modeling framework2 which has been a time and cost effective tool for understanding and optimizing the complex multi-physics phenomena within PEMFCs; however, several of the cell parameters used in the modeling have large spread in measured data.3 Furthermore, several transport parameters such as water adsorption kinetics have not been accurately measured and the approximations are spread over several orders of magnitude. These uncertainties cause problems in ascertaining accuracy of the modeling approach and they reduce the predictive power of the numerical models. The aim of this work is to identify the sensitivity of PEFC numerical model outputs to various input parameters. The previously in-house developed MEA modeling framework2 is used for PEMFC modeling. The sensitivity of the model outputs with respect to inputs parameters is obtained by analyzing the condition numbers for different output-input pairs at varying operating conditions. An example of the sensitivity analysis is shown in Figure 1. The condition numbers are obtained for the entire possible range of input parameters at varying operating conditions to identify the most crucial parameters of the PEMFC model. Based on our preliminary analysis, parameters related to kinetics (exchange current density and ECSA) and heat/water management in electrodes and ionomer (ionomer fraction, thermal conductivity) are most crucial. One of the major goals of this work is to identify the most crucial set of parameters towards which the model shows maximum sensitivity. This will guide future experimentalists to measure these properties with higher accuracy. Furthermore, the sensitivity analysis will also enable us to optimize the PEMFC performance by selectively targeting the most sensitive parameters and thereby making the largest impact. Acknowledgements The work is funded under the Fuel Cell Performance and Durability Consortium (FC-PAD), by the Fuel Cell Technologies Office (FCTO), Office of Energy Efficiency and Renewable Energy (EERE), of the U.S. Department of Energy under contract number DE-AC02-05CH11231. The authors would like to thank Nathan Craig at Robert Bosch LLC for his valuable input in designing the sensitivity analysis. The authors would also like to thank Giovanna Bucci and Matthias Hanauer at Robert Bosch for their valuable inputs and discussion. References P. K. Sinha, W. Gu, A. Kongkanand and E. Thompson, J. Electrochem. Soc., 158, B831 (2011). L. M. Pant, M. R. Gerhardt, N. Macauley, R. Mukundan, R. L. Borup and A. Z. Weber, Electrochim. Acta, 326, 134963 (2019). R. Vetter and J. O. Schumacher, ArXiv181110091 Phys. (2018). Figure 1

Pant, Lalit↗
DOE OSTI2022

MIONet: Learning Multiple-Input Operators via Tensor Product

As an emerging paradigm in scientific machine learning, neural operators aim to learn operators, via neural networks, that map between infinite-dimensional function spaces. Several neural operators have been recently developed. However, all the existing neural operators are only designed to learn operators defined on a single Banach space; i.e., the input of the operator is a single function. Here, for the first time, we study the operator regression via neural networks for multiple-input operators defined on the product of Banach spaces. We first prove a universal approximation theorem of continuous multiple-input operators. We also provide a detailed theoretical analysis including the approximation error, which provides guidance for the design of the network architecture. Based on our theory and a low-rank approximation, we propose a novel neural operator, MIONet, to learn multiple-input operators. MIONet consists of several branch nets for encoding the input functions and a trunk net for encoding the domain of the output function. Here, we demonstrate that MIONet can learn solution operators involving systems governed by ordinary and partial differential equations. In our computational examples, we also show that we can endow MIONet with prior knowledge of the underlying system, such as linearity and periodicity, to further improve accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

System Analysis Support of Consent-Based Siting Efforts - 23400

To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the Integrated Waste Management (IWM) program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring the development and application of system analysis tools capable of analyzing various system options for the management of spent nuclear fuel (SNF) and high-level radioactive waste. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate things like the implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed system operation start dates. Some example system analysis results have been published previously. With the passage of the consolidated appropriations acts for fiscal years 2021 and 2022, Congress provided funding and direction for the DOE to move forward with interim storage to support near-term action in managing the nation’s SNF as an important component of an IWMS. Consent-based siting is a phased, adaptive, and collaborative approach to siting facilities that focuses on the needs and concerns of people and communities. Communities participate in the siting process by working carefully through a series of phases and steps with the DOE (as the implementing organization). Each step and phase helps a community determine whether and how hosting a facility to manage SNF is aligned to the community’s goals. By its nature, a consent-based siting process must be transparent, flexible, adaptive, and responsive to community concerns. Thus, the phases and steps are intended to serve as a guide, not a prescriptive set of instructions. System analysis research analysts interface with DOE’s consent-based siting for a federal interim storage program and can perform preliminary system analyses as requested to support various aspects of the consent-based siting team’s work. This paper provides an overview of IWM program’s system analysis activities that support the ongoing consent-based siting process. The questions that decision-makers, planners, communities, and stakeholders might have during the consent-based siting process are similar to questions that have been explored by system analysts previously. Specifically, this paper discusses work that will inform consent-based siting efforts in the areas of community impacts, cost estimates, various SNF acceptance rates by potential facilities, potential consolidated interim storage facility (CISF) capacities and configurations, and the implications of a CISF on the overall waste management system. It is expected that system analysis will continue to be performed to support the consent-based siting process in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI1996

Nuclear Safety [Vol. 37, No. 2, April-June 1996]

Nuclear Safety is a journal that covers significant issues in the field of nuclear safety. Its primary scope is safety in the design, construction, operation, and decommissioning of nuclear power reactors worldwide and the research and analysis activities that promote this goal, but it also encompasses the safety aspects of the entire nuclear fuel cycle, including fuel fabrication, spent-fuel processing and handling, and nuclear waste disposal, the handling of fissionable materials and radioisotopes, and the environmental effects of all these activities. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 97 The Nuclear Community and the Public: Cognitive and Cultural Influences on Thinking About Nuclear Risk, M. A. Meyer; 109 Twenty-Third Water Reactor Safety Information Meeting, D. A. Copinger; ACCIDENT ANALYSIS: 126 Analysis of a PWR LBLOCA Without SCRAM, Trevor N. Tyler, Rafael Macian-Juan and John H. Mahaffy; DESIGN FEATURES: 139 Vulnerability of Multiple-Barrier Systems, N. C. Lind; ENVIRONMENTAL EFFECTS: 149 A Study of Wet Catalytic Oxidation of Radioactive Spent Ion Exchange Resin by Hydrogen Peroxide, Xingchao Jian, Tianbao Wu, and Guichun Yun; 157 A Comparison Study and Resolution of Differences Between Emergency Response and Safety Analysis Codes Used at the Savannah River Site, A. A. Simpkins; OPERATING EXPERIENCES: 164 Reactor Shutdown Experience, Compiled by J. W. Cletcher; RECENT DEVELOPMENTS: 167 Reports, Standards, and Safety Guides, D. S. Queener; 172 Proposed Rule Changes as of Dec. 31,1995; ANNOUNCEMENTS: 178 American Nuclear Society 1997 Annual Meeting; 178 American Nuclear Society Nuclear Criticality and Safety Division Topical Meeting; 176 The Authors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Linewidth narrowing in self-injection-locked on-chip lasers

Abstract Stable laser emission with narrow linewidth is of critical importance in many applications, including coherent communications, LIDAR, and remote sensing. In this work, the physics underlying spectral narrowing of self-injection-locked on-chip lasers to Hz-level lasing linewidth is investigated using a composite-cavity structure. Heterogeneously integrated III–V/SiN lasers operating with quantum-dot and quantum-well active regions are analyzed with a focus on the effects of carrier quantum confinement. The intrinsic differences are associated with gain saturation and carrier-induced refractive index, which are directly connected with 0- and 2-dimensional carrier densities of states. Results from parametric studies are presented for tradeoffs involved with tailoring the linewidth, output power, and injection current for different device configurations. Though both quantum-well and quantum-dot devices show similar linewidth-narrowing capabilities, the former emits at a higher optical power in the self-injection-locked state, while the latter is more energy-efficient. Lastly, a multi-objective optimization analysis is provided to optimize the operation and design parameters. For the quantum-well laser, minimizing the number of quantum-well layers is found to decrease the threshold current without significantly reducing the output power. For the quantum-dot laser, increasing the quantum-dot layers or density in each layer increases the output power without significantly increasing the threshold current. These findings serve to guide more detailed parametric studies to produce timely results for engineering design.

47 OTHER INSTRUMENTATION↗