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Results for “reactor network synthesis”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A generalized distillation network synthesis model

In this report we propose a generalized superstructure-based distillation network synthesis model with improved modeling capabilities resulting in an extended solution space. The model can assign multiple mixtures to be separated (e.g., reactor network effluents) to different columns of the network while considering the interactions among different separation steps. In terms of outlets, products with general specifications, including pure components and multi-component mixtures, as well as streams without strict specifications (e.g., reactor recycle streams) can be readily handled. Furthermore, stream bypass is considered to avoid unnecessary separations, and thermal coupling is considered to yield novel solutions. The proposed model enables seamless integration with reactor network synthesis models thereby leading to solutions that are superior to the ones obtained by conventional sequential approaches.

42 ENGINEERING↗
DOE OSTI2018

A superstructure optimization approach for process synthesis under complex reaction networks

Here in this work, we present mixed integer linear programming methods for the synthesis of processes that involve complex reaction networks. Specifically, we consider the modeling of reactors and interconnecting streams in systems where the composition of the reactor inlet streams can vary substantially, thereby making the determination of the limiting component as well as the calculation of the stream heating/cooling and power requirements challenging. First, towards the modeling of reactors, we develop an extent-based method which detects the limiting reactant of each reaction occurring in parallel with others, based on the inlet flows of the reactants. Second, we develop a computationally tractable method for the calculation of the work and heating/cooling duty needed to condition any stream of a process based on simple calculations that can be performed offline. Finally, we present how the two aforementioned components can be integrated in an optimization model generated based on a process superstructure. We demonstrate the application of the developed methods for the synthesis of a biorefinery.

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

A generalized superstructure-based framework for process synthesis

We propose a general framework for the formulation of superstructure-based optimization models for holistic process synthesis. First, we redefine the fundamental problems of reactor, separation, and heat exchanger network synthesis, by presenting generalized problem statements, to make them amenable to seamless integration with each other. Second, we describe the general forms of models that can be developed to address these generalized problems and identify some key characteristics. Notably, for each system, we identify internal variables used only within the system, cost variables used in the objective function, and, importantly, coupling variables for the coupling between systems. Third, we outline some literature models that can be used to address the generalized problems and present new models to couple the three systems. Finally, we show how the individual components (systems and coupling models) can be integrated to formulate a single simultaneous reactor, separation, and heat exchanger network synthesis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Stochastic solution of population balance equations for reactor networks

This work presents a sequential modular approach to solve a generic network of reactors with a population balance model using a stochastic numerical method. Full-coupling to the gas-phase is achieved through operator-splitting. The convergence of the stochastic particle algorithm in test networks is evaluated as a function of network size, recycle fraction and numerical parameters. These test cases are used to identify methods through which systematic and statistical error may be reduced, including by use of stochastic weighted algorithms. The optimal algorithm was subsequently used to solve a one-dimensional example of silicon nanoparticle synthesis using a multivariate particle model. This example demonstrated the power of stochastic methods in resolving particle structure by investigating the transient and spatial evolution of primary polydispersity, degree of sintering and TEM-style images. Highlights: •An algorithm is presented to solve reactor networks with a population balance model. •A stochastic method is used to solve the population balance equations. •The convergence and efficiency of the reported algorithms are evaluated. •The algorithm is applied to simulate silicon nanoparticle synthesis in a 1D reactor. •Particle structure is reported as a function of reactor length and time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

One-Pot Aqueous and Template-Free Synthesis of Mesoporous Polymeric Resins

This report explores the novel one-pot aqueous phase synthesis of mesoporous phenolic-hyperbranched polyethyleneimine resins without the use of a template, and their utility as heterogeneous catalysts in batch reactors and continuous microreactors. Catalyst surface areas of up to 432 m 2 /g were achieved with a uniform Pd distribution and an interconnected, highly porous, network structure, confirmed through Brunauer–Emmett–Teller (BET) surface area measurements, scanning electron microscopes (SEM), X-Ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), and Energy-dispersive X-ray spectroscopy (EDS). The heterogeneous catalysts achieved a maximum 98.98 ± 1% conversion in batch Suzuki couplings, with conversions being dependent upon reaction conditions, reactant chemistries, Pd loading and catalyst surface area. The catalysts were shown to be recyclable with only a marginal loss in conversion achieved after five runs. Up to 62 ± 5% and 46.5 ± 8% conversions at 0.2 mL/s and 0.4 mL/s flow rates, respectively, were achieved in a continuous microreactor. Understanding the mechanism of action of this mesoporous resin is a future research area, which could help expand the application vistas for this catalyst platform.

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

High-throughput reaction discovery for Cs–Pb–Br nanocrystal synthesis

High-throughput reaction discovery is necessary to understand complex reaction spaces for inorganic nanocrystal synthesis. Here, we implemented a high-throughput continuous flow millifluidic reactor to perform reaction discovery for Cs–Pb–Br nanocrystal synthesis using a ligand assisted reprecipitation (LARP)-type approach. 3D-printed flow resistors enable the screening of up to 16 different mixing ratios within a single 90 s run, allowing for >270 different precursor concentration ratios to be quickly tested to explore the phase space that results in CsPbBr 3 , Cs 4 PbBr 6 , a biphasic mixture, or no product. To construct a full phase map from these high-throughput experiments, a neural network was trained and validated to predict the product composition (~500 000 points in precursor concentration space). The phase map predicts product composition/phase as a function of Cs–Pb–Br feed ratio. As a result, this approach demonstrates how high-throughput flow chemistry can be used in tandem with machine learning to rapidly explore nanocrystal reaction spaces in flow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Creation of hollow silica-fiberglass soft ceramics for thermal insulation

Hollow-structured materials show promise in thermal insulation because the shells encapsulating gaseous voids can interrupt heat transport pathways. Here, in this study, we present two low-cost routes to fabricate hollow silica nanoshells, via gas-phase and liquid-phase methods. The gas-phase synthesis method generates hollow shells by a droplet surface precipitation mechanism in a flame aerosol reactor. The liquid-phase synthesis route forms hollow shells by removal of a carbon template, which is produced by hydrothermal reaction of glucose. Both approaches (gas- and liquid-phase) provide hollow silica with amorphous structure, low thermal conductivity (0.023 and 0.026 W m –1 K –1 ), small particle size (442 and 383 nm), thin shell (35 and 36 nm), and low density (0.015 and 0.033 g cm –3 ). We employed high shear mechanical mixing to fabricate hollow silica-fiberglass composite ceramics. The resulting three-dimensional network provides the ceramics with robust mechanical elasticity and fire-retardancy while maintaining low thermal conductivity, dramatically outperforming an analogous material using commercial silica gel in place of the hollow nanoshells. Our findings provide two practical routes to synthesize hollow silica, either of which can be used to manufacture a class of hollow shell-fiber nanocomposite soft ceramics for energy-saving applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Sealable femtoliter chamber arrays for cell-free biology

Cell-free systems provide a flexible platform for probing specific networks of biological reactions isolated from the complex resource sharing (e.g. global gene expression, cell division) encountered within living cells. However, such systems, used in conventional macro-scale bulk reactors, often fail to exhibit the dynamic behaviors and efficiencies characteristic of their living micro-scale counterparts. Understanding the impact of internal cell structure and scale on reaction dynamics is crucial to understanding complex gene networks. Here we report a microfabricated device that confines cell-free reactions in cellular scale volumes while allowing flexible characterization of the enclosed molecular system. This multilayered poly(dimethylsiloxane) (PDMS) device contains femtoliter-scale reaction chambers on an elastomeric membrane which can be actuated (open and closed). When actuated, the chambers confine Cell-Free Protein Synthesis (CFPS) reactions expressing a fluorescent protein, allowing for the visualization of the reaction kinetics over time using time-lapse fluorescent microscopy. Lastly, we demonstrate how this device may be used to measure the noise structure of CFPS reactions in a manner that is directly analogous to those used to characterize cellular systems, thereby enabling the use of noise biology techniques to characterize CFPS gene circuits and their interactions with the cell-free environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Surface-Initiated Atom Transfer Radical Polymerization Using Hydrogel Reactors

Atom transfer radical polymerization (ATRP) is a controlled radical polymerization method that enables the synthesis of tailored polymeric materials with low dispersity, highlighting its immense potential for green fabrication of advanced materials. However, its broader implementation is limited by challenges in product isolation, maintaining catalyst activity, and mitigating atmospheric sensitivity arising from oxygen-sensitive metal catalysts. Here, gelatin hydrogels (GHs) are introduced as a soft “reactor” matrix for interfacial ATRP, operating with minimal metal-catalyst loading while exhibiting possibly an organoreductive behavior. This strategy leverages activator regeneration via electron transfer through a ligand–metal charge-transfer (LMCT) mechanism to reduce oxidized metal catalysts within the GH network. Polymerization is evaluated by growing polymer brushes at an active interface formed between GHs swollen in monomer solution and an initiating surface, and sequential growth experiments confirmed that GH-mediated ATRP preserves living character. Under UV illumination, LMCT is activated, producing polymers both at the desired interface and within the GH bulk. UV–Vis spectroscopy revealed active reduction of Cu(II) to Cu(I) along with concentration-dependent complex formation, indicating dynamic coordination chemistry within the hydrogel. The redox-active arginine- and glutamic acid-rich gelatin backbone coordinates and reduces the metal center, enabling ATRP at ppm-level catalyst concentrations. While polymerization proceeds in GH-Cu(II) reactors, adding external mobile ligands to the GH results in longer polymer brushes. Here, the results reported here are exploratory. More experiments are needed to characterize polymer brush growth in GHs and compare it to conventional surface-initiated polymerization in solution.

Absorption↗
DOE OSTI2020

Microfluidic, One-Batch Synthesis of Pd Nanocrystals on N-Doped Carbon in Surfactant-Free Deep Eutectic Solvents for Formic Acid Electrochemical Oxidation

One of the grand challenges that impedes practical applications of nanomaterials is the lack of robust manufacturing methods that are scalable, cheap, and environmentally friendly. In this work, we address this challenge by developing a microfluidic approach that produces surfactant-free Pd nanocrystals (NCs) uniformly loaded on N-doped porous carbon in a one-batch process. The deep eutectic solvent (DES) prepared from choline chloride and ethylene glycol was employed as a novel synthesis solvent, and its extended hydrogen networks and abundant ionic species effectively stabilize Pd facets and confine nanocrystal sizes without using surfactants. The microreactors provide faster heat exchange and more uniform mass transport, which in combination with DES produced Pd NCs with better-defined shape and predominately exposed Pd (100) facet. Furthermore, we describe that the N-doped functional groups in porous carbon direct dense and uniform heterogeneous growth of Pd NCs in a one-batch process, thereby eliminating a separate catalyst deposition step that is often involved in conventional synthesis. The Pd NCs in the one-batch-produced Pd/C catalysts exhibited a size distribution of similar to ~13 ± 3.5 nm and a high ESCA of 46.0 m 2 /g and delivered 362 mA/mg for formic acid electrochemical oxidation with improved stability, demonstrating the unique potentials of microfluidic reactors and DES for the controllable and scalable synthesis of electrocatalyst materials for practical applications.

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

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2025

Low Temperature CO 2 Hydrogenation on Unsupported Mo 2 C Catalysts

CO 2 hydrogenation to methanol, a key reaction for decarbonizing the fuel and chemical industries, requires catalyst formulations that hydrogenate CO 2 selectively to methanol at temperatures where methanol conversion is not significantly equilibrium limited (<423 K). Herein we report continuous CO 2 hydrogenation at low temperatures (348-408 K, H 2 /CO 2 = 0.1-50, 5-35 bar) with high selectivity to methanol (up to ca. 80%) over unsupported β-Mo 2 C catalysts. Active site density quantification via titration with trifluoroacetic acid at reaction temperatures enables an assessment of site-specific rates. Methanation and reverse water gas shift (RWGS) occur concurrently with methanol synthesis during CO 2 hydrogenation over Mo 2 C. Reaction pathway analysis, product cofeeds, and reversibility formalisms show that all products form through primary reaction pathways from CO 2 , but secondary reactions of CO contribute significantly to rates of methanation. Dependences of forward rates on reactant and product concentration determined by independently varying the CO 2 , H 2 , CO, H 2 O, CH 3 OH, and CH 4 pressure in conjunction with reversibility formalisms reveal that all products form through H-assisted CO 2 activation and involve partially hydrogenated CO 2 -derived intermediates. Here, these inferences were verified by quantitative agreement between measured site-time yields and site-time yields predicted by closed form kinetic rate expressions in an integral reactor model over widely varying conditions (85-2000 kPa H 2 , 80-1500 kPa CO 2 , 0-45 kPa H 2 O, 0-21 kPa CO, 0-25 kPa CH 3 OH, 0-75 kPa CH 4 , 5-87 mol Mo s s mol CO 2 -1 ). Coverages calculated based on the kinetic model reveal that the Mo 2 C surface is covered with bidentate CO- and CO 2 -derived intermediates of the stoichiometry H 2 CO 2 and H 2 CO, indicating that H 2 and CO x do not compete for surface occupancy but instead adsorb cooperatively to form partially hydrogenated intermediates. Hydrogenation of the CO-derived H 2 CO** intermediate favors methanation, while hydrogenation of CO 2 -derived H 2 CO 2 ** favors methanol synthesis. Together, these findings demonstrate the ability of unsupported Mo 2 C to catalyze the hydrogenation of CO 2 to methanol at low temperatures and provide insight into the reaction network and mechanisms involved in its formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

THE C({sup 3}P) + NH{sub 3} REACTION IN INTERSTELLAR CHEMISTRY. II. LOW TEMPERATURE RATE CONSTANTS AND MODELING OF NH, NH{sub 2}, AND NH{sub 3} ABUNDANCES IN DENSE INTERSTELLAR CLOUDS

A continuous supersonic flow reactor has been used to measure rate constants for the C({sup 3}P) + NH{sub 3} reaction over the temperature range 50–296 K. C({sup 3}P) atoms were created by the pulsed laser photolysis of CBr{sub 4}. The kinetics of the title reaction were followed directly by vacuum ultra-violet laser induced fluorescence of C({sup 3}P) loss and through H({sup 2}S) formation. The experiments show unambiguously that the reaction is rapid at 296 K, becoming faster at lower temperatures, reaching a value of (1.8 ± 0.2) × 10{sup −10} cm{sup 3} molecule{sup −1} s{sup −1} at 50 K. As this reaction is not currently included in astrochemical networks, its influence on interstellar nitrogen hydride abundances is tested through a dense cloud model including gas–grain interactions. In particular, the effect of the ortho-to-para ratio of H{sub 2}, which plays a crucial role in interstellar NH{sub 3} synthesis, is examined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Synthesis, Characterization, and Testing of High-Lithium-Density Composite Breeders

Solid tritium breeder materials must first and foremost have sufficiently high concentrations of lithium to enable a plant-scale tritium breeding ratio greater than 1:1. However, in addition to lithium content, such breeder materials must also meet other performance metrics including high tritium release rates, thermal conductivities, and irradiation damage tolerance. Perhaps most importantly, tritium breeders must maintain their mechanical integrity during reactor operation so as to avoid degradation which can jeopardize the functionality of the tritium breeder blanket module, which in most designs takes the form of a pebble bed geometry. Unfortunately, the mechanical robustness of most lithium-bearing ceramics under investigation for fusion applications is often inversely related to the lithium atom density. For example, a material such as lithium oxide (Li2O), which has one of the highest lithium atom densities, has a much lower mechanical splitting strength than lithium metatitanate (Li2TiO3), though Li2TiO3 has less than half the lithium atom density of Li2O. This work seeks to provide an alternative to monolithic ceramic tritium breeders, in the form of metal-reinforced composite tritium breeders. Specifically, composite tritium breeders have been synthesized combining Li2O with various ferrous metal reinforcements via electric field assisted sintering (EFAS), also known as spark plasma sintering (SPS). As the metal reinforcement content is increased, metallic networks are observed, via electron microscopy and X-ray computed tomography, to form throughout the composite material. Through destructive mechanical testing, even dilute metal reinforcement loading enables drastic mechanical strength improvements over pure Li2O while higher loadings give rise to quasi-ductile behavior and higher ultimate strengths than Li2TiO3 – while still maintaining a higher density of lithium atoms than Li2TiO3 and many other breeder candidates. In addition to microstructural characterization and mechanical testing, thermal property measurements and hydrogen permeability testing are underway to further assess the suitability of such composites for fusion reactor applications.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Preliminary Design of Nuclear Reactor Heat Delivery Systems: Integration with Reference Oil Refinery, Methanol Synthesis, and Hydrogen Production

The Department of Energy’s (DOE) Integrated Energy Systems (IES) program is generating comprehensive analyses validating the opportunity for using nuclear energy in a variety of applications including future clean grids, providing heat for direct use, and providing heat to help reduce emissions in chemical commodities. This work focuses on the preliminary designs of thermal delivery systems that can integrate heat produced from a nuclear core to industrial processes. The key research question that needs to be answered is: what is the prospective method for integrating nuclear generated heat energy into non-electric applications that can facilitate combined heat and power operations by advanced nuclear reactor systems? This research is a composition of case studies showing preliminary conceptual designs for thermal delivery systems integrating advanced nuclear systems with a few industrial systems including high temperature steam electrolysis, a reference oil refinery, and potential future methanol systems that supplant some natural gas use with nuclear energy. Piping and instrumentation diagrams have been developed to show the conceptual integration of nuclear systems with representative industrial systems. Different features of the configurations are dependent on the specific integration requirements including energy source conditions, demand quantity, and require energy application conditions. Design concepts are validated using thermodynamic balance calculations to verify system performance including calculating system losses during transport. Key components: pumps and compressors, heat exchangers, and network piping are reported with key design information and sizing.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Crystal structure and catalytic properties of three inorganic–organic hybrid constructed from heteropolymolybdate and aminopyridine

Three new organic–inorganic hybrid compounds (2-C{sub 5}H{sub 7}N{sub 2}){sub 3}·(SiMo{sub 12}O{sub 40})·(C{sub 4}H{sub 8}N{sub 4}){sub 0.5}·(C{sub 5}H{sub 6}N{sub 2}){sub 2}·(H{sub 2}O){sub 2} (1), (3-C{sub 5}H{sub 7}N{sub 2}){sub 8}·(SiMo{sub 12}O{sub 40}){sub 2}·(C{sub 5}H{sub 7}N{sub 3}){sub 2}·(H{sub 8}O{sub 4})·(H{sub 2}O){sub 8} (2) and (4-C{sub 5}H{sub 7}N{sub 2}){sub 6}·(SiMo{sub 12}O{sub 40}) (3) composed the heteropolymolybdate α-H{sub 4}SiMo{sub 12}O{sub 40} and the organic substrate 2/3/4-aminopyridine have been hydrothermally synthesized and characterized by routine methods. Compounds 1 and 2 exhibit a three-dimensional supramolecular network via hydrogen bond and π–π stacking interactions. Compound 2 contains a tetramolecular water cluster which consists of four water molecules connected by hydrogen bonds. These compounds exhibit good thermal stability and photoluminescent phenomena. Compounds 1 and 3 are active for catalytic oxidation of methanol in a continuous-flow fixed-bed micro-reactor, when the initial concentration of methanol is 2.75 g m{sup −3} in air and flow rate is 10 mL min{sup −1} at 150 °C, corresponding to the elimination rate of methanol i.e. 87.7% and 76.8%, respectively. - Three new Keggin type inorganic–organic hybrid frameworks were synthesized. Compounds exhibit an extended three-dimensional supramolecular network. Compounds 1 and 3 have better catalytic activity for eliminating methanol. Highlights: ► Three 3-D Keggin inorganic–organic hybrid frameworks were synthesized. ► The π–π stacking interactions are existed in Compounds 1 and 2. ► Compound 2 contains a tetramolecular water cluster connected by hydrogen bond. ► Compounds 1 and 3 are active in the catalytic oxidation of methanol into CO{sub 2} and H{sub 2}O.

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

Model Development and Analysis of a High-Fidelity Neutron Transport Sensor: The Quadrupole Detector Concept for Measurement of the Neutron Flux Gradient

Accurate reconstruction of the neutron flux distribution within a reactor core is essential for safe and efficient reactor operation. Traditional power shape synthesis in Light Water Reactors relies on hundreds of in-core detectors. However, this approach becomes impractical for Advanced Reactors and Microreactors due to limited space and harsh environments. To address this challenge, we propose a data-driven methodology that combines high-fidelity modeling with real-time ex-core sensor measurements, enabling the reconstruction of core power distribution while minimizing the reliance on intrusive in-core instrumentation. This project began in FY24 and achieved two initial milestones: (1) the definition of a three-year development plan for a Digital Twin framework and (2) the development of high-fidelity neutronics models of the Purdue University Reactor One (PUR-1) using both MCNP6 and OpenMC. The PUR-1 reactor, a zero-power facility, was selected due to its suitability for neutronics-focused modeling and the availability of experimental data for validation. Both models were benchmarked using neutron flux measurements obtained from irradiated gold foils, which were strategically placed within the core during a dedicated campaign in July 2024. This report marks the continuation and completion of those foundational tasks. The OpenMC model has been refined (improved geometric accuracy, expanded cross-section libraries, and refined sampling) and validated using additional experimental data. An updated sensor design—based on quadrupole configuration—was designed to measure both ex-core flux and its spatial gradient. These measurements will serve as inputs to a neural network-based reconstruction algorithm. Finally, the methodology was demonstrated on a two-dimensional test case representative of the heterogeneous material composition of the PUR-1 reactor core. A neural network implementation of the Kirchhoff-Helmholtz integral equation was employed to solve the boundary value problem using peripheral sensor measurements. The preliminary results confirm the strong potential of the proposed approach for accurate and minimally invasive neutron flux reconstruction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗