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Solvent-mediated contaminant removal from plastic waste using thermodynamic modeling
Plastics recycling is hindered by the compositional complexity of plastic waste, which can include numerous polymer components as well as low concentrations of additives and non-intentionally added substances. These latter small-molecule species, which we collectively refer to as contaminants, can harm human health and will build up in recycled plastic causing environmental and downstream processing challenges if not removed. In this work, we present molecular modeling approaches using the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) to guide the selection of solvents that are capable of removing targeted contaminants from plastic waste. By considering the thermodynamic partitioning of contaminant species between a solvent phase and polymer phase, we identify guidelines for solvent selection to promote either the low-temperature extraction of contaminants from plastic waste or the removal of contaminants as part of a dissolution-based plastics recycling process. We present four case studies to illustrate the application of the computational approach to the removal of brominated flame retardants, phthalates, and selected perfluoroalkyl substances, and compare to both literature and newly collected experimental data to illustrate model prediction accuracy. Furthermore, the case studies highlight the capability of the modeling approach to help design recycling processes that explicitly account for contaminant removal, thereby increasing product purity during dissolution-based recycling or facilitating chemical recycling of contaminant-free plastics.
Thermodynamic modeling of the no-vent fill methodology for transferring cryogens in low gravity
The filling of tanks with cryogens in the low-gravity environment of space poses many technical challenges. Chief among these is the inability to vent only vapor from the tank as the filling proceeds. As a potential solution to this problem, the NASA Lewis Research Center is researching a technique known as No-Vent Fill. This technology potentially has broad application. The focus is the fueling of space based Orbital Transfer Vehicles. The fundamental thermodynamics of the No-Vent Fill is described. The model is then used to conduct a parametric investigation of the key parameters: initial tank wall temperature, liquid-vapor interface heat transfer rate, liquid inflow rate, and inflowing liquid temperatures. Liquid inflowing temperature and the liquid-vapor interface heat transfer rate seem to be the most significant since they influence the entire fill process. The initial tank wall temperature must be sufficiently low to prevent a rapid pressure rise during the initial liquid flashing state, but then becomes less significant.
Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria
We have applied a new stochastic simulation approach to predict the metabolite levels, energy flow, and material flux in the different oxidative TCA cycles found in E. coli and Synechococcus sp. PCC 7002, and in the reductive TCA cycle typical of chemolithoautotrophs and phototrophic green sulfur bacteria such as Chlorobaculum tepidum. The simulation approach is based on equations of state and employs an assumption similar to that used in transition state theory. The ability to evaluate the thermodynamics of metabolic pathways allows one to understand the relationship between coupling of energy and material gradients in the environment and the selforganization of stable biological systems, and it is shown that each cycle operates in the direction expected due to its environmental niche. The simulations predict changes in metabolite levels and flux in response to changes in cofactor concentrations that would be hard to predict without an elaborate model based on the law of mass action. In fact, we show that a thermodynamically unfavorable reaction can still have flux in the forward direction when it is part of a reaction network. The ability to predict metabolite levels, energy flow and material flux should be significant for understanding the dynamics of natural systems and for understanding principles for engineering organisms for production of specialty chemicals, such as biofuels.
Thermodynamic modeling of the no-vent fill methodology for transferring cryogens in low gravity
The filling of tanks with cryogens in the low-gravity environment of space poses many technical challenges. Chief among these is the inability to vent only vapor from the tank as the filling proceeds. As a potential solution to this problem, the NASA Lewis Research Center is researching a technique known as No-Vent Fill. This technology potentially has broad application. The focus is the fueling of space based Orbital Transfer Vehicles. The fundamental thermodynamics of the No-Vent Fill process to develop an analytical model of No-Vent Fill is described. The model is then used to conduct a parametric investigation of the key parameters: initial tank wall temperature, liquid-vapor interface heat transfer rate, liquid inflow rate, and inflowing liquid temperatures. Liquid inflowing temperature and the liquid-vapor interface heat transfer rate seem to be the most significant since they influence the entire fill process. The initial tank wall temperature must be sufficiently low to prevent a rapid pressure rise during the initial liquid flashing stage, but then becomes less significant.
A thermodynamic model for the solubility of HfO2(am) in the aqueous K + – HCO 3 - – CO 3 2- –O - –H 2 O system
Solubility of HfO2(am) was determined as a function of KHCO3 concentrations ranging from 0.001 mol·kg-1 to 0.1 mol·kg-1. The solubility of HfO2(am) increased dramatically with the increase in KHCO3 concentrations, indicating that Hf(IV) makes strong complexes with carbonate. Thermodynamic equilibrium constants for the formation of Hf-carbonate complexes were determined using both the Pitzer and SIT models. The dramatic increase in Hf concentrations with the increase in KHCO3 concentrations can best be described by the formation of Hf(OH-)2(CO3)22- and Hf(CO3)56-. The log10 K0 values for the reactions [Hf4++2CO32-+2OH-⇌Hf(OH)2(CO3)22-] and [Hf4++5CO32-⇌Hf(CO3)56-], based on the SIT model, were determined to be 44.53±0.46 and 41.53±0.46, respectively, and based on the Pitzer model they were 44.56±0.48 and 40.20±0.48, respectively.
Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI
The modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in describing short-range ordering (SRO) in complex liquids such as molten salts, slag in metal processing, and electrolytic solutions. Here, the present work implements the MQMQA into the Python based open-source software PyCalphad for thermodynamic calculations. This endeavor facilitates the development of MQMQA-based thermodynamic database with uncertainty quantification (UQ) and propagation (UP) using the open-source software ESPEI. A new database structure based on Extensible Markup Language (XML) is proposed for ESPEI evaluation of MQMQA model parameters. Using the KF-NiF 2 , KCl-NaCl-MgCl 2 , and CaCl 2 -CaF 2 -LiCl-LiF salt systems as examples, we demonstrate the successful implementation of MQMQA in PyCalphad through thermodynamic calculations of Gibbs energy, equilibrium quadruplet fractions, and phase diagram, as well as database development with UQ and UP using ESPEI. Furthermore, as an application of the present implementation, both the LiF–TbF 3 and LiF-HoF 3 systems have been modeled by MQMQA for the first time, which are in good agreement with experiments. The present implementation hence offers an open-source capability for performing CALPHAD modeling for complex liquids with SRO using MQMQA plus a new XML database structure.
Hydration behavior of magnesium potassium phosphate cement and stability analysis of its hydration products through thermodynamic modeling
Magnesium potassium phosphate cement (MKPC) is normally applied in civil engineering because of its short setting time and superior mechanical properties. This study investigates the hydration behavior and hydration products of MKPC influenced by molar ratio between magnesia and phosphate (M/P ratio) through thermodynamic method. Results show that the composition of ultimate hydration products are controlled by concentration of KH{sub 2}PO{sub 4} and MgO, activity of water and pH value of solution. When M/P ratio is lower than 0.64, the hydration product is MgHPO{sub 4}·3H{sub 2}O; When M/P ratio is between 0.64 and 0.67, the hydration products are MgHPO{sub 4}·3H{sub 2}O and Mg{sub 2}KH(PO{sub 4}){sub 2}·15H{sub 2}O. When M/P ratio is between 0.67 and 1.00, hydration products are Mg{sub 2}KH(PO{sub 4}){sub 2}·15H{sub 2}O and KMgPO{sub 4}·6H{sub 2}O; When M/P ratio is higher than 1.00, the hydration product is KMgPO{sub 4}·6H{sub 2}O together with unreacted MgO. This study also investigated the effect of additives, namely B(OH){sub 3}, H{sub 3}PO{sub 4}, K{sub 2}HPO{sub 4} and KH{sub 2}PO{sub 4}. - Highlights: • A database particularly for MKPC system at 25°C, 0.1 MPa was established and verified. • The pH value corresponding to specific M/P ratio in MKPC system is successfully predicted at 25°C, 0.1 MPa. • The composition of hydration products influenced by M/P ratio and some additives is successfully predicted at 25°C, 0.1 MPa.
Latent Heating Retrieval from TRMM Observations Using a Simplified Thermodynamic Model
A procedure for the retrieval of hydrometeor latent heating from TRMM active and passive observations is presented. The procedure is based on current methods for estimating multiple-species hydrometeor profiles from TRMM observations. The species include: cloud water, cloud ice, rain, and graupel (or snow). A three-dimensional wind field is prescribed based on the retrieved hydrometeor profiles, and, assuming a steady-state, the sources and sinks in the hydrometeor conservation equations are determined. Then, the momentum and thermodynamic equations, in which the heating and cooling are derived from the hydrometeor sources and sinks, are integrated one step forward in time. The hydrometeor sources and sinks are reevaluated based on the new wind field, and the momentum and thermodynamic equations are integrated one more step. The reevalution-integration process is repeated until a steady state is reached. The procedure is tested using cloud model simulations. Cloud-model derived fields are used to synthesize TRMM observations, from which hydrometeor profiles are derived. The procedure is applied to the retrieved hydrometeor profiles, and the latent heating estimates are compared to the actual latent heating produced by the cloud model. Examples of procedure's applications to real TRMM data are also provided.
Toward a Classical Thermodynamic Model for Retro-cognition
Retro-cognition--a human response before a randomly determined future stimulus--has always been part of our experience. Experiments over the last 80 years show a small but statistically significant effect. If this turns out to be true, then it suggests a form of macroscopic retro-causation. The 2nd Law of Thermodynamics provides an explanation for the apparent single direction of time at the macroscopic level although time is reversible at the microscopic level. In a preliminary study, I examined seven anomalous cognition (a.k.a., ESP) studies in which the entropic gradients and the entropy of their associated target systems were calculated, and the quality of the response was estimated by a rating system called the figure of merit. The combined Spearman's correlation coefficient for these variables for the seven studies was 0.211 (p = 6.4x10{sup -4}) with a 95% confidence interval for the correlation of [0.084, 0.332]; whereas, the same data for a correlation with the entropy itself was 0.028 (p = 0.36; 95% confidence interval of [-0.120-0.175]). This suggests that anomalous cognition is mediated via some kind of a sensory system in that all the normal sensory systems are more sensitive to changes than they are to inputs that are not changing. A standard relationship for the change of entropy of a binary sequence appears to provide an upper limit to anomalous cognition functioning for free response and for forced-choice Zener card guessing. This entropic relation and an apparent limit set by the entropy may provide a clue for understanding macroscopic retro-causation.
Solubility behavior and thermodynamic modeling of sodium monosulfoaluminate (“U‐phase”) in cementitious systems
Abstract The “U‐phase,” a sodium‐containing (alumino‐ferrite‐monosubstituent) AFm phase, has been observed to form in sodium‐enriched highly alkaline cementitious systems, for example, of relevance to nuclear waste, and saline industrial brine management. But, minimal information is available of the U‐phase's (e.g., solubility or thermodynamic properties) due to its limited stability and its tendency to transform into ettringite or monosulfoaluminate. Herein, the U‐phase was systematically synthesized at four temperatures (5, 15, 25, and 50°C) and fully characterized in terms of its thermochemical properties. The average composition of the synthesized U‐phase (4CaO·Al 2 O 3 ·1.85SO 3 ·0.85Na 2 O·12H 2 O) deviates slightly from typical disclosures in the literature. The solubility product of the U‐phase formation was measured from conditions of oversaturation. The measured thermodynamic data accurately predicted experimental observations of U‐phase formation in cementitious environments. In general, it was noted that the U‐phase forms and persists (i.e., remains stable) at pH > 13.7 and [Na + ] concentrations superior to 1 mol/L.
A thermodynamic model for subsolidus equilibria in the system CaO-MgO-Al2O3-SiO2
It is shown that the high temperature enthalpy of solution data for pure phases and solid solutions in the CMAS system are, for 'gabbroic' and 'peridotitic' compositions, consistent with available phase equilibrium data for the MAS, CAS and CMAS systems. A refined set of values of thermodynamic properties for these phases and solid solutions is tabulated. The small differences between the new data set and that of Helgeson et al. (1978) arise from new data on heat capacity and enthalpy being incorporated. The important constraints applied and the major difficulties in fitting which arose are summarized.
Upper Stage Tank Thermodynamic Modeling Using SINDA/FLUINT
Modeling to predict the condition of cryogenic propellants in an upper stage of a launch vehicle is necessary for mission planning and successful execution. Traditionally, this effort was performed using custom, in-house proprietary codes, limiting accessibility and application. Phenomena responsible for influencing the thermodynamic state of the propellant have been characterized as distinct events whose sequence defines a mission. These events include thermal stratification, passive thermal control roll (rotation), slosh, and engine firing. This paper demonstrates the use of an off the shelf, commercially available, thermal/fluid-network code to predict the thermodynamic state of propellant during the coast phase between engine firings, i.e. the first three of the above identified events. Results of this effort will also be presented.
Magnetic BiMn-α phase synthesis prediction: First-principles calculation, thermodynamic modeling and nonequilibrium chemical partitioning
BiMn-α is promising permanent magnet. Due to its peritectic formation feature, there is a synthetic challenge to produce single BiMn-α phase. The objective of this study is to assess driving force for crystalline phase pathways under far-from-equilibrium conditions. First-principles calculations with Hubbard U correction are performed to provide a robust description of the thermodynamic behavior. The energetics associated with various degrees of the chemical partitioning are quantified to predict temperature, magnetic field, and time dependence of the phase selection. By assessing the phase transformation under the influence of the chemical partitioning, temperatures, and cooling rate from our calculations, we suggest that it is possible to synthesize the magnetic BiMn-α compound in a congruent manner by rapid solidification. The external magnetic field enhances the stability of the BiMn-α phase. In conclusion, the compositions of the initial compounds from these highly driven liquids can be far from equilibrium.
M3SF-24LL010302062-NEA-TDB Management and International Collaborations in Sorption and Thermodynamic Modeling
This progress report (Level 3 Milestone Number M3SF-24LL010302062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline International Collaborations Work Package Number SF-24LL01030206. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. This includes participation in the Nuclear Energy Agency Thermochemical Database (NEA-TDB) Project and development of methodologies for integrating US and international thermodynamic databases for use in SFWST Generic Disposal System Assessment (GDSA) efforts. A continuing focus for FY24 efforts is to support the US participation in the NEA-TDB effort. The focus of FY24 activities was the development of an agreement for a Phase 7 activity that will start in Q1 of 2025. Mavrik Zavarin is now the US representative on both the Management Board and the Executive group to the NEA-TDB. He is also the POC for the Cements State of the Art Report that is undergoing peer review in FY24. In FY24, we used our position on the NEA-TDB MB and EG to facilitate the integration of NEA-TDB thermochemical data with LLNL’s SUPCRTNE thermodynamic database that supports the SFWST GDSA activities. This effort is coordinated with the Argillite work package SUPCRTNE database development efforts (Wolery, 2024). The goal is to provide a downloadable database that will be hosted on LLNL’s thermodynamics website which incorporates NEA-TDB data into the LLNL database where appropriate. We also began engagement with the EURAD2 program that was initiated in FY24 by our European collaborators at the Karlsruhe Institute of Technology (KIT), Germany. The primary focus of the engagement is with WP20: DITUSC Thermodynamic database evaluation program. A kickoff meeting for this activity is planned for early FY25. Finally, we have been selected to co-host (with Clemson University) the International Conference on Chemistry and Migration Behaviour of Actinides and Fission Products in the Geosphere in 2025 (Migration2025). The meeting will be held September 21-26, 2025, in New Orleans, Louisiana, and will focus on international efforts to understand the risks of radionuclide releases into the environment. This central focus of this conference is on international efforts to develop safe disposal options for nuclear wastes. As such, we are developing a theme focused on US underground nuclear waste repository science.
Thermodynamic Modeling of the Al-Ce-Cu-Mg-Si System and Its Application to Aluminum-Cerium Alloy Design
Recently discovered AlCe alloys have shown promise in a number of applications, but the propensity of Ce to react with Al and other alloying elements can complicate the phase equilibria and design approach. To solve this, the CALPHAD method is used to explore an alloy within the quinary Al-Ce-Cu-Mg-Si system by developing a thermodynamic database with self-consistent parameters. The database includes a description of all 10 binary systems and 8 ternary systems consisting of: (i) 6 Al-containing ternaries (Al-Ce-Cu, Al-Ce-Mg, Al-Ce-Si, Al-Cu-Mg, Al-Cu-Si and Al-Mg-Si); and (ii) 2 additional ternaries that include Mg and Si (i.e., Ce-Mg-Si and Cu-Mg-Si). The thermodynamic description for the Al-Ce-Mg and Al-Mg-Si systems were reassessed to ensure consistency with the binary systems and the Ce-Mg-Si system is presented for the first time and compared to theoretical data from DFT (Density Functional Theory). In addition to the ternary interactions, the quaternary compound Al3Cu2Mg9Si7 and solid solution extending from the ternary Al2CuMg phase (Al,Si)2CuMg are incorporated. The CALPHAD method is employed and leveraged through the use of a Materials Design Simulator (MDS) to accelerate the design of novel aluminum-cerium-based alloys. The combination of a CALPHAD-based framework with experimental efforts and industrial insight permits the development of three new Al-Ce alloys: Al-3.5Ce-0.4Mg-7Si (Ce-modified A356), Al-5Ce-1Cu-0.5Mg-10Si and Al-19Ce-0.9Mg-1.1Si.
Ab Initio Thermodynamic Modeling of Hydrogen Defects and Transport for Solid Oxide Fuel Cells and Tritium Producing Burnable Absorber Rod Applications
Presented by NETL at Materials Science and Technology, 09/19
Machine learning of consistent thermodynamic models using automatic differentiation
In this study, we propose a data-driven method to describe consistent equations of state (EOS) for arbitrary systems. Complex EOS are traditionally obtained by fitting suitable analytical expressions to thermophysical data. A key aspect of EOS is that the relationships between state variables are given by derivatives of the system free energy. In this work, we model the free energy with an artificial neural network and utilize automatic differentiation to directly learn the derivatives of the free energy. We demonstrate this approach on two different systems, the analytic van der Waals EOS and published data for the Lennard-Jones fluid, and we show that it is advantageous over direct learning of thermodynamic properties (i.e., not as derivatives of the free energy but as independent properties), in terms of both accuracy and the exact preservation of the Maxwell relations. Furthermore, the method implicitly provides the free energy of a system without explicit integration.