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242 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Structural and chemical complexity of minerals: An update

The complexities of chemical composition and crystal structure are fundamental characteristics of minerals that have high relevance to the understanding of their stability, occurrence and evolution. This review summarises recent developments in the field of mineral complexity and outlines possible directions for its future elaboration. The database of structural and chemical complexity parameters of minerals is updated by H-correction of structures with unknown H positions and the inclusion of new data. The revised average complexity values (arithmetic means) for all minerals are 3.54(2) bits/atom and 345(10) bits/cell (based upon 4443 structure reports). The distributions of atomic information amounts, chemIG and strIG, versus the number of mineral species fit the normal modes, whereas the distributions of total complexities, chemIG,total and strIG,total, along with numbers of atoms per formula and per unit cell are log normal. The three most complex mineral species known today are ewingite, morrisonite and ilmajokite, all either discovered or structurally characterised within the last five years. The most important complexity-generating mechanisms in minerals are: (1) the presence of isolated large clusters; (2) the presence of large clusters linked together to form three-dimensional frameworks; (3) formation of complex three-dimensional modular frameworks; (4) formation of complex modular layers; (5) high hydration state in salts with complex heteropolyhedral units; and (6) formation of ordered superstructures of relatively simple structure types. The relations between symmetry and complexity are considered. The analysis of temporal dynamics of mineralogical discoveries since 1875 with the step of 25 years show the increasing chemical and structural complexities of human knowledge of the mineral kingdom in the history of mineralogy. In the Earth’s history, both diversity and complexity of minerals experience dramatic increases associated with the formation of Earth’s continental crust, initiation of plate tectonics and the Great Oxidation event.

complexity↗
DOE OSTI2020

Utilizing Commercial Submersible Mixer Pumps for Sludge Removal in Savannah River Site's Tank 26 - 20289

The Savannah River Site (SRS) Liquid Waste System (LWS) safely manages, stores, treats, and dispositions liquid radioactive waste. The LWS consists of 51 underground waste storage tanks (eight of which are operationally closed and filled with grout), waste evaporators, treatment facilities, and solidification facilities, known as the Defense Waste Processing Facility (DWPF) and Saltstone Production Facility (SPF). One of the waste storage tanks, Tank 26, was placed into service in 1980 as an F Tank Farm (FTF) Evaporator Feed Tank. From 1980 to 2013, Tank 26 received F Canyon receipts and dilute supernate that was then transferred to the 242-16F FTF Evaporator for volume reduction. In 2013, the steam tube bundle failed in the FTF Evaporator, and the decision was made not to repair/resume evaporator operation. During operation of Tank 26, solids built up to a level of 2.03 m in the tank with a volume of 1062.9 kL. Due to the evaporator failure and subsequent shutdown, the solids in Tank 26 were selected to feed Sludge Batch 10, which is collected and prepped prior to being sent to DWPF for final disposition. To accomplish solids removal, Commercial Submersible Mixer Pumps (CSMPs) were selected to slurry the solids in preparation to be sent to Tank 51. Four CSMPs were installed in Tank 26 with each one installed in a separate quadrant of Tank 26. This work would mark the first deployment of CSMPs in an SRS waste tank. The CSMPs were developed in response to operational issues from previous mixing pumps and budgetary constraints. The CSMPs use the concept of modifying commercially available equipment for nuclear waste applications. The CSMPs consist of a 230-horsepower submersible mixing pump (manufactured by GPM, Inc.) joined to a mast fabricated at SRS. For this application, Savannah River Remediation (SRR) design services was challenged to provide a mast design that required no steel superstructure support system on top of Tank 26. Also, SRR design services provided a simplified Tank 26 riser interface that did not require extensive machine parts to adjust height of the suction screen of the CSMP within the tank. Other design improvements include no requirements for tank top radiation monitors and no requirements for flushing of the CSMPs during startup/shutdown operations. The CSMPs were operated at an initial height of 2.29 m above the Tank 26 bottom for 10 days. After sludge sounding, the CSMPs were lowered to a height of 1.52 m with no issues due to proper work planning and the simplified riser interface. With the CSMPs lowered to a level of 1.52 meters above the tank bottom, the CSMPs were operated for 12 days and another sounding was performed. The sounding level came back matching the disturbance depth results of the first pump run. Chemistry samples were analyzed while the tank was left to settle. The analysis revealed enough weight percent solids to provide good feed to Sludge Batch 10. Also, the results revealed the supernate within the mixture would provide good salt solution feed to Salt Waste Processing Facility (SWPF) Salt Batch 3. So, the plan was modified to let the disturbed solids settle and decant the salt solution for addition to SWPF Salt Batch 3. Then water will be added back to Tank 26, and the CSMPs run in order to wash the solids to decrease settling time prior to being sent to Tank 51 for Sludge Batch 10. Utilizing CSMPs for waste removal in an SRS Tank has provided a cost-effective means for further waste removal efforts. In addition, the CSMPs are easier to operate by utilizing a robust and simplified design. The CSMPs performed quite well with no process shutdown or delays during operation. As a result, CSMPs are integral to the future of removing radioactive waste from storage tanks at SRS. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Membrane-based carbon capture process optimization using CFD modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2023

Regulating Cation Interactions for Zero–Strain and High–Voltage P2–type Na 2/3 Li 1/6 Co 1/6 Mn 2/3 O 2 Layered Oxide Cathodes of Sodium–Ion Batteries

Deep sodium extraction/insertion of sodium cathodes usually causes undesired Jahn–Teller distortion and phase transition, both of which will reduce structural stability and lead to poor long-cycle reliability. Here we report a zero-strain P2- Na 2/3 Li1/6Co 1/6 Mn 2/3 O 2 cathode, in which the lithium/cobalt substitution contributes to reinforcing the host structure by reducing the Mn 3+ /Mn 4+ redox, mitigating the Jahn–Teller distortion, and minimizing the lattice change. 94.5 % of Na + in the unit structure can be reversibly cycled with a charge cut-off voltage of 4.5 V (vs. Na + /Na). Impressively, a solid-solution reaction without phase transitions is realized upon deep sodium (de)intercalation, which poses a minimal volume deviation of 0.53 %. Finally, it attains a high discharge capacity of 178 mAh g –1 , a high energy density of 534 Wh kg –1 , and excellent capacity retention of 95.8 % at 1 C after 250 cycles.

25 ENERGY STORAGE↗
DOE OSTI2022

Network Optimization of the Electrosynthesis of Chemicals from CO2

Carbon dioxide electroreduction (ECO2R) is gaining attention due to its capacity to mitigate CO2 emissions while using electricity that would otherwise be curtailed. Its foreseeable industrial implementation requires of holistic methods to assess the technological and economic performance of ECO2R processes and integrate them in current chemical supply chains and power systems. Here, we combine techno-economic assessment and mathematical programming to find the optimal paths to electroreduce CO2 into valuable chemicals under variable electricity prices. The proposed approach is tested with a case study addressing the CO2 capture from flue gas or direct air and its electricity-powered reduction into carbon monoxide, formic acid or multi-carbon compounds. The results obtained demonstrate the ability of the framework to build ECO2R networks and provide operation profiles that respond to fluctuating electricity prices.

carbon dioxide↗
DOE OSTI2021

A systems engineering framework for the optimization of food supply chains under circular economy considerations

The current linear “take-make-waste-extractive” model leads to the depletion of natural resources and environmental degradation. Circular Economy (CE) aims to address these impacts by building supply chains that are restorative, regenerative, and environmentally benign. This can be achieved through the re-utilization of products and materials, the extensive usage of renewable energy sources, and ultimately by closing any open material loops. Such a transition towards environmental, economic and social advancements requires analytical tools for quantitative evaluation of the alternative pathways. Here, in this work, we present a novel CE system engineering framework and decision-making tool for the modeling and optimization of food supply chains. First, the alternative pathways for the production of the desired product and the valorization of wastes and by-products are identified. Then, a Resource-Task-Network representation that captures all these pathways is utilized, based on which a mixed-integer linear programming model is developed. This approach allows the holistic modeling and optimization of the entire food supply chain, taking into account any of its special characteristics, potential constraints as well as different objectives. Considering that typically CE introduces multiple, often conflicting objectives, we deploy here a multi-objective optimization strategy for trade-off analysis. A representative case study for the supply chain of coffee is discussed, illustrating the steps and the applicability of the framework. Single and multi-objective optimization formulations under five different coffee-product demand scenarios are presented. The production of instant coffee as the only final product is shown to be the least energy and environmental efficient scenario. On the contrary, the production solely of whole beans sets a hypothetical upper bound on the optimal energy and environmental utilization. In both problems presented, the amount of energy generated is significant due to the utilization of waste generated for the production of excess energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Optimization-Based Azeotropic Distillation System Synthesis Using Geometric Insights

The synthesis of azeotropic distillation systems is challenging due to the existence of compartments in the residue curve map coupled with the combinatorial aspects from numerous possible system configurations. In this work, an optimization-based approach is introduced to synthesize homogeneous azeotropic distillation systems. The approach employs a network-based representation generated via a matrix method. To design the distillation columns, the modified Underwood equations are adopted, in which pseudocomponent-based compositions are used. For cases where separatrices are significantly curved, corrections via piece-wise linear functions and collinearity properties are implemented. Two examples are presented to illustrate the proposed approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2024

Global Optimization via Quadratic Disjunctive Programming for Water Networks Design with Energy Recovery

Generalized disjunctive programming (GDP) models with bilinear and concave constraints, often seen in water network design, are challenging optimization problems. This work proposes quadratic and piecewise linear approximations for nonlinear terms to reformulate GDP models into quadratic GDP (QGDP) models that suitable solvers may solve more efficiently. We illustrate the benefits of the quadratic reformulation with a water treatment network design problem in which nonconvexities arise from bilinear terms in the mixers’ mass balances and concave investment cost functions of treatment units. Given the similarities with water network design problems, we suggest quadratic approximation for the GDP model for the optimal design of a large-scale reverse electrodialysis (RED) process. This power technology can recover energy from salinity differences between by-product streams of the water sector, such as desalination brine mixed with regenerated wastewater effluents. The solver Gurobi excels in handling QGDP problems, but weighing the problem’s precision and tractability balance is crucial. The piecewise linear approximation yields more accurate, yet larger QGDP models that may require longer optimization times in large-scale process synthesis problems.

Water Networks↗