---
title: "Cortix Tech AI Assistant Discussion on DB: \\texttt{usecase-04}"
author: Valmor F. de Almeida 
date: 30 Oct 2025
---
# Cortix Tech AI Assistant Discussion Transcript
**SW Developer:** Valmor F. de Almeida, Ph.D.; 30 Oct 2025. <br>

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## User: Please briefly describe your role.

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## Assistant: 

### My role

- I am a Cortix Tech AI Assistant that answers questions based on the provided context (Solvex-generated data stored under the knowledge table usecase-04).  
- I specialize in explaining and reporting on the Stage module and the TBP / diluent / $\mathrm{H_2O}$ / $\mathrm{HNO_3}$ / $\mathrm{UO}_2^{2+}$ / air mixing use case.  
- I will primarily use the supplied context to form answers and will say when the context does not contain enough information.  
- I will double-check responses against the provided context and iterate as needed to improve accuracy.  
- I cannot run external code or access resources beyond the given context, but I can summarize, analyze, and generate reports from it on request.

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## User: Provide a tabular summary describing this usecase and any sub-usecase available; use the usecase Id number and make the table concise (max. 4 columns) such that it fits in a letter-size PDF document.

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## Assistant: 

### Tabular summary (concise; max 4 columns)

| Usecase Id | Title | Scope / Objectives | Key features / Notes |
|---:|---|---|---|
| 04 | TBP-Diluent-$\mathrm{\:H_2O}$-$\mathrm{\:HNO_3}$-$\mathrm{\:UO}_2^{2+}$-Air Mixing | Develop a mixed-phase TBP extraction scenario (aqueous, organic, vapor); test implementation and present results. | Mixed-phase Stage module; aqueous/organic/vapor phases; ODE time integration; port-based connectivity; reaction-mechanism coupling. |
| 04.1 | TBP-Diluent-$\mathrm{\:H_2O}$-$\mathrm{\:HNO_3}$-$\mathrm{\:UO}_2^{2+}$-Air Parameter Study | Parametric study of tau (0.1, 0.5, 1.0, 1.5) with matched relative humidity; quantify stage efficiency time-histories. | 17 time samples (0 → 247.699 s); final mean efficiencies: tau=0.1: 91.75%; 0.5: 69.31%; 1.0: 53.24%; 1.5: 43.73%. Final stds: 2.13%, 6.29%, 7.76%, 7.75% (respectively). |

### Knowledge database entries (concise)
- Usecase 04 — TBP-Diluent-$\mathrm{\:H_2O}$-$\mathrm{\:HNO_3}$-$\mathrm{\:UO}_2^{2+}$-Air Mixing  
- Usecase 04.1 — TBP-Diluent Parameter Study (tau / relative humidity)  

Note: this list is drawn from the provided context and may be incomplete.

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## User: Elaborate on the objectives of the usecase and sub-usecase.

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## Assistant: 

### Usecase 04 — Objectives

- Develop a realistic mixed‑phase solvent‑extraction scenario for tri‑n‑butyl phosphate (TBP) interacting with aqueous species $ \mathrm{H_2O}$, $ \mathrm{HNO_3}$, and $ \mathrm{UO_2^{2+}}$ including an explicit vapor phase.  
- Implement and validate a Stage module that models aqueous, organic and vapor containers with port‑based connectivity and internal chemical reaction coupling.  
- Simulate time evolution using ODE integration (fixed time step + internal scipy.integrate.odeint stepping) to produce transient mass‑balance histories.  
- Couple ReactionMechanism data (species, molar masses, rate/generation functions) into the stage mass‑balance RHS to capture chemistry and phase coupling.  
- Test and present results (efficiency time‑histories, stage behavior) to demonstrate the model and its outputs.  
- Use limited AI assistance (CortixAI) for explanation, reporting and iterative refinement of the scenario and outputs.

### Usecase 04.1 — Objectives (Parametric study)

- Extend Usecase 04 into a parametric study that systematically varies key parameters (e.g., residence time tau and matched relative humidity / inflow RH) to quantify sensitivity.  
- Provide a minimal framework and driver loop (pseudo‑code) to run multiple fixed‑parameter simulations and archive results for post‑processing and plotting.  
- Assess mass transfer and inflow relative humidity effects on extraction performance (time‑histories and final efficiencies/statistics).  
- Produce concise summary metrics (e.g., mean and standard deviation of final efficiencies across parameter sets) and time‑sampled histories for comparison.  
- Enable iterative AI‑assisted analysis (multiple AI calls if results need refinement) and document the simulation configuration and outcomes.

Note: All objectives above are taken from the provided usecase context; if you want, I can expand any objective into implementation steps or list required input parameters.

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## User: Provide a description and analysis of all phases present. Enumerate the chemical reactions in the reaction mechanism, and include key simulation results with Stage efficiency. Use markdown typesetting for species names; always inline LaTeX into markdown.

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## Assistant: 

### Phases present — description and analysis
- Aqueous phase — contains $\mathrm{H_2O(a)}$, $\mathrm{H^+(a)}$, $\mathrm{N_2(a)}$, $\mathrm{NO_3^-(a)}$, $\mathrm{O_2(a)}$, $\mathrm{UO_2^{2+}(a)}$; hosts ionic chemistry (acid, nitrate) and the dissolved metal ($\mathrm{UO_2^{2+}}$) that is the target for TBP extraction, exchanges mass with organic (extraction/complexation) and with vapor (evaporation/aeration); aqueous–vapor water transfer shows elevated steady efficiency compared with other steps.
- Organic phase — contains TBP and TBP-derived complexes, e.g. $\mathrm{[C_4H_9O]_3PO(o)}$, $\mathrm{H_2O\cdot[C_4H_9O]_3PO(o)}$, $\mathrm{HNO_3\cdot[C_4H_9O]_3PO(o)}$, $\mathrm{UO_2[NO_3]_2\cdot[[C_4H_9O]_3PO]_2(o)}$; functions as the extractant phase where neutral complexation of $\mathrm{HNO_3}$ and $\mathrm{UO_2^{2+}}$ occurs (physical solvation/ligand coordination); organic complexation reactions grow in efficiency during start‑up and settle near ~50% in steady state.
- Vapor phase — contains $\mathrm{H_2O(v)}$, $\mathrm{N_2(v)}$, $\mathrm{O_2(v)}$; only physical phase‑transfer (vaporization / aeration) processes appear in the KB (no gas‑phase chemistry); mass transfer is finite‑rate (stage efficiencies substantially <100%), and vapor concentrations approach quasi‑steady values (e.g., reported plateaus near $\mathrm{N_2}\!\approx\!0.9085\ \mathrm{g\,L^{-1}}$, $\mathrm{O_2}\!\approx\!0.25793\ \mathrm{g\,L^{-1}}$, $\mathrm{H_2O(v)}\!\approx\!0.02719\ \mathrm{g\,L^{-1}}$).

### Reaction mechanism — enumerated reactions (all reversible phase labels shown)
- $\mathrm{[C_4H_9O]_3PO(o) + H_2O(a) \leftrightarrow H_2O\cdot[C_4H_9O]_3PO(o)}$
- $\mathrm{2\,[C_4H_9O]_3PO(o) + 2\,H_2O(a) \leftrightarrow [H_2O]_2\cdot[[C_4H_9O]_3PO]_2(o)}$
- $\mathrm{3\,[C_4H_9O]_3PO(o) + 6\,H_2O(a) \leftrightarrow [H_2O]_6\cdot[[C_4H_9O]_3PO]_3(o)}$
- $\mathrm{H^+(a) + NO_3^-(a) + [C_4H_9O]_3PO(o) \leftrightarrow HNO_3\cdot[C_4H_9O]_3PO(o)}$
- $\mathrm{H^+(a) + NO_3^-(a) + 2\,[C_4H_9O]_3PO(o) \leftrightarrow HNO_3\cdot[[C_4H_9O]_3PO]_2(o)}$
- $\mathrm{UO_2^{2+}(a) + 2\,NO_3^-(a) + 2\,[C_4H_9O]_3PO(o) \leftrightarrow UO_2[NO_3]_2\cdot[[C_4H_9O]_3PO]_2(o)}$
- $\mathrm{H_2O(a) \leftrightarrow H_2O(v)}$
- $\mathrm{O_2(v) \leftrightarrow O_2(a)}$
- $\mathrm{N_2(v) \leftrightarrow N_2(a)}$

### Key simulation results and Stage efficiency (concise)
- Overall stage behavior — most reactions converge near ~50% efficiency in steady state (finite‑rate stage mass/chemical transfer; not full thermodynamic equilibrium).
- Per‑reaction steady‑state means (last three times: 206.416, 258.02, 309.624 s): $\mathrm{[C_4H_9O]_3PO + H_2O}$: 50.069% (50.020–50.135).
- Per‑reaction steady‑state means: $\mathrm{2\,TBP + 2\,H_2O}$ complex: 50.071% (50.020–50.140).
- Per‑reaction steady‑state means: $\mathrm{3\,TBP + 6\,H_2O}$ complex: 50.204% (50.055–50.408).
- Per‑reaction steady‑state means: $\mathrm{H^+ + NO_3^- + TBP \to HNO_3\cdot TBP}$: 49.694% (49.384–49.920).
- Per‑reaction steady‑state means: $\mathrm{H^+ + NO_3^- + 2\,TBP \to HNO_3\cdot(TBP)_2}$: 49.815% (49.621–49.954).
- Per‑reaction steady‑state means: $\mathrm{UO_2^{2+} + 2\,NO_3^- + 2\,TBP}$: 49.576% (49.151–49.886).
- Vapor/aeration steady‑state: $\mathrm{H_2O(a)\leftrightarrow H_2O(v)}$ = 54.321% (54.319–54.324).
- Vapor/aeration steady‑state: $\mathrm{O_2(v)\leftrightarrow O_2(a)}$ = 49.990% (49.980–49.997).
- Vapor/aeration steady‑state: $\mathrm{N_2(v)\leftrightarrow N_2(a)}$ = 49.957% (49.915–49.988).
- Representative overall stage efficiency reported (up to 309.62 s) — approximately $50.46\% \pm 1.36\%$ (finite‑rate mass transfer dominated).
- Start‑up trends (0 → 48.16 s) — neutral/organic complexation reactions (TBP–H2O complexes) rose fastest (to ~45–51%); acid and uranyl extraction reactions increased more slowly (to ~27–31% at 48 s); $\mathrm{H_2O(a)\leftrightarrow H_2O(v)}$ rose from ~35% to ~51.53%; $\mathrm{O_2}$ and $\mathrm{N_2}$ exchanges remained ~50% with only minor changes.
- Parametric sub‑usecase (Usecase 04.1) summary — final mean efficiencies vs residence time $\tau$: $\tau\!=\!0.1$: 91.75% (std 2.13%); $\tau\!=\!0.5$: 69.31% (std 6.29%); $\tau\!=\!1.0$: 53.24% (std 7.76%); $\tau\!=\!1.5$: 43.73% (std 7.75%) — showing strong dependence of final efficiency on $\tau$ (shorter $\tau$ → higher reported efficiency in that parametric study).

Note: all species lists, reaction equations, and numerical results above are taken from the provided Stage Knowledge Base / simulation outputs. If you want a formatted CSV or a one‑page PDF layout tuned for printing, I can produce that next.

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## User: Comment on the Stage module (i.e. its key methods), describe the simulation setup including initial conditions, inflow, and time-integration including elapsed runtime.

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## Assistant: 

### Note
- I am a Cortix Tech AI Assistant and will use the provided usecase-04 context to comment on the Stage module and the simulation.

### Stage module — high‑level role
- Models a single solvent‑extraction stage with three explicit phases: aqueous, organic and vapor.
- Couples reaction kinetics to phase mass balances and solves transient behavior with an ODE integrator.
- Synchronizes port I/O to time‑step boundaries so inflow/outflow occur at step completion.

### Stage module — key methods and components
- run() — top‑level time‑integration loop; calls __step() then __call_ports() each cycle.
- __step() — advances the internal integrator for the current time step (invokes ODE solver).
- __call_ports() — performs port I/O (inflow/outflow updates) after each step; keeps I/O synchronized to step boundaries.
- __mbal_rhs_func(...) — mass‑balance right‑hand side; builds phase‑resolved balances that combine inflow/outflow mass rates and reaction source terms (g_vec from the reaction mechanism).
- Reaction‑mechanism population utilities — load species, molar masses and rate/generation functions into stg.rxn_mech.data used by __mbal_rhs_func.
- Conversion utilities — unit and concentration conversions used during initialization and inflow assignment.
- __check_mass_conservation(u_vec, write=False) — computes mass‑rate‑density residual via __total_mass_generation_rate_density_residual and asserts the residual is within tolerance.
- compute‑total‑mass‑flowrates utilities — diagnostic helpers to print total inflow/outflow mass rates for monitoring.
- Monitors / flags — stg.monitor_mass_flowrates, stg.monitor_mass_conservation_residual, stg.mass_bal_rate_dens_res_tol control diagnostics and assertion tolerances.

### Simulation setup — physical and numerical initial conditions
- Mix volume — mix_volume = 1 L.
- Phase volumetric flows — vol_flowrate_aqu = 500 mL/min; vol_flowrate_org = 600 mL/min.
- Vapor flow fractions — vol_flowrate_vap set as percentages: (3.7% of organic flow, 8.1% of aqueous flow) via vol_flowrate_vap = (3.7*vol_flowrate_org/100, 8.1*vol_flowrate_aqu/100).
- Phase list supplied as vol_flowrates = [vol_flowrate_org, vol_flowrate_aqu, vol_flowrate_vap].
- Temperature — stage temperature set from 40 °C converted to Kelvin (stg_temperature = unit.convert_temperature(40, 'C', 'K')).
- Stage instantiation and registration — stg = Stage(mix_volume, vol_flowrates, stg_temperature); system_net.module(stg).

### Inflow conditions (notable details)
- Vapor inflow temperature and pressure — inflow_temperature = unit.convert_temperature(20, 'C', 'K') (293.15 K); inflow_pressure = 1.1 bar.
- Vapor inflow humidity — inflow_relative_humidity = 25.0 (%).
- Vapor composition computed by air_vapor_content(...) returning per‑species mass concentrations which are assigned to both aqueous and organic vapor inflow ports for $\mathrm{N_2(v)}$, $\mathrm{O_2(v)}$, and $\mathrm{H_2O(v)}$.
- Aqueous/organic initial species populations and reaction data are populated from stg.rxn_mech.data (species, molar masses, g_vec generation functions).

### Time‑integration configuration and step selection
- Start‑up period — end_time set to one flow residence time: end_time = 1 * stg.flow_residence_time_avg.
- Time‑step selection — compute ave_tau = mean([data['tau'] for data in stg.rxn_mech.data]); time_step = ave_tau / 15.
- Display cadence — show_time = (True, 10*time_step).
- Simulation flags — stg.name = 'Stg-1'; stg.save = True; stg.verbose = True; stg.perturb_flowrates = False; stg.time_step assigned to computed time_step; stg.end_time assigned to end_time.
- Port I/O synchronization — run() sequence ensures __call_ports() executes only after each internal step, so boundary exchanges happen at discrete step boundaries.

### Mass conservation, diagnostics and tolerances
- Mass conservation check — __check_mass_conservation uses total mass generation rate density residual and asserts it is within stg.mass_bal_rate_dens_res_tol.
- Example tolerance used in the run — stg.mass_bal_rate_dens_res_tol set to 1.e-8 * unit.micro * unit.gram / unit.L / unit.second for that run.
- Monitors can be enabled/disabled: stg.monitor_mass_flowrates and stg.monitor_mass_conservation_residual were disabled in the reported run.

### Observed runtime and diagnostics from the provided run
- Logged step progress — example log lines: Stg-1::run():time[m]=0.0, time[m]=0.6, time[m]=0.9 (et[s]=0.6).
- Mass balance diagnostic printed — total mass rate density residual [g/L-s] = -1.66533e-16.
- Sample flow diagnostics printed — total mass inflow rate = 7.419e+02 g/min; total mass outflow rate = 7.161e+02 g/min; net total mass flow rate = -2.580e+01 g/min.
- Elapsed wall‑clock time for the system run — run()::Elapsed wall clock time [s]: 441.38 (close() reported same elapsed time).

### How to recover post‑run data (example)
- Recover stage object — stg = system_net.modules[0].
- Obtain number of time stamps (startup) — n_startup = len(stg.organic_phase.time_stamps).

### Caveats and scope
- All descriptions above are taken directly from the provided usecase-04 context; if you want, I can produce a one‑page printable summary (PDF layout) or extract specific port/state arrays (time histories) if you provide which species/phases to export.

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## User: What are the governing equations solved? Inline LaTeX formulae in the markdown output.

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## Assistant: 

### Governing equations solved

- State vector  
  - The solver advances a state vector $\mathbf{u}(t)$ containing mass concentrations for every tracked species $k$ in each phase $p$ (units: $\mathrm{g\,L^{-1}}$): $\mathbf{u}=\{\rho_{k,p}\}$.

- ODE form (generic)  
  - The system of ODEs has the standard form $$\frac{d\mathbf{u}}{dt}=\mathbf{f}(\mathbf{u},t)\,,$$ where $\mathbf{f}$ assembles inflow/outflow, chemical source terms and inter‑phase transfer for all species and phases.

- Per‑species, per‑phase mass balance (display form)  
  - For species $k$ in phase $p$ the mass balance written in mass‑density form is:  
    $$\frac{d\rho_{k,p}}{dt}=\dot{m}^{\mathrm{in}}_{k,p}-\dot{m}^{\mathrm{out}}_{k,p}+M_k\sum_j\nu_{k,j}\,r_j+\dot{m}^{\mathrm{transfer}}_{k,p}\,,$$  
    where each term has units $\mathrm{g\,L^{-1}\,s^{-1}}$.

- Meaning of terms in the per‑species balance  
  - $\rho_{k,p}$ is the mass concentration of species $k$ in phase $p$ ($\mathrm{g\,L^{-1}}$).  
  - $\dot{m}^{\mathrm{in}}_{k,p}$ and $\dot{m}^{\mathrm{out}}_{k,p}$ are mass flow‑rate densities into/out of the stage for that species/phase (mass per volume per time).  
  - $M_k$ is the molar mass of species $k$ ($\mathrm{g\,mol^{-1}}$).  
  - $\nu_{k,j}$ is the stoichiometric coefficient of species $k$ in reaction $j$ (positive for production, negative for consumption).  
  - $r_j$ is the reaction rate density for reaction $j$ in molar units (e.g., $\mathrm{mol\,L^{-1}\,s^{-1}}$); note that some reported rates are in $\mathrm{mM\,s^{-1}}$ so conversion $1\ \mathrm{mM\,s^{-1}}=10^{-3}\ \mathrm{mol\,L^{-1}\,s^{-1}}$ is required.  
  - $\dot{m}^{\mathrm{transfer}}_{k,p}$ collects mass exchange with other phases (inter‑phase transfer + partitioning), in $\mathrm{g\,L^{-1}\,s^{-1}}$.

- Reaction source term (molar→mass conversion)  
  - Reaction contributions are assembled as mass source terms via the molar→mass conversion: $$\dot{m}^{\mathrm{rxn}}_{k,p}=M_k\sum_j\nu_{k,j}\,r_j\quad\left(\mathrm{g\,L^{-1}\,s^{-1}}\right).$$

- Inter‑phase (phase‑transfer) models (general / first‑order relaxation)  
  - Phase transfer is represented in the code by partitioning and/or first‑order relaxation terms (relaxation times $\tau$ are attached to mechanism entries). A generic first‑order transfer contribution between phase $p$ and $q$ for species $k$ has the form:  
    $$\dot{m}^{\mathrm{transfer}}_{k,p\leftarrow q}=\frac{M_k}{\tau_{k,p\leftarrow q}}\big(c^{\mathrm{eq}}_{k,p}-c_{k,p}\big)\quad\text{with}\quad c_{k,p}=\frac{\rho_{k,p}}{M_k}\,,$$  
    where $c^{\mathrm{eq}}_{k,p}$ may be computed from partition coefficients (e.g., $c^{\mathrm{eq}}_{k,p}=K_{p\leftarrow q}\,c_{k,q}$) or from an explicit equilibrium fraction used at initialization.

- Port inflow / outflow coupling (volumetric flows)  
  - Inflow/outflow terms are tied to volumetric flowrates and port compositions; mass flow contributions are converted to densities consistent with the stage mixing volume, e.g. $$\dot{m}^{\mathrm{in}}_{k,p}=\frac{\dot{M}^{\mathrm{in}}_{k,p}}{V_{\mathrm{mix}}}\,,$$ where $\dot{M}^{\mathrm{in}}_{k,p}$ is mass flow into the stage (g s^{-1}) and $V_{\mathrm{mix}}$ is the stage mixing volume (L).

- Total mass conservation / residual computed for diagnostics  
  - Total mass conservation is monitored via the residual (mass‑rate‑density units $\mathrm{g\,L^{-1}\,s^{-1}}$):  
    $$\mathcal{R}_{\mathrm{mass}}(t)=\sum_{k,p}\frac{d\rho_{k,p}}{dt}-\Big(\sum_{\mathrm{ports}}\dot{m}^{\mathrm{in}}_{\mathrm{port}}-\sum_{\mathrm{ports}}\dot{m}^{\mathrm{out}}_{\mathrm{port}}\Big)\,,$$  
    and the reported runs show $\mathcal{R}_{\mathrm{mass}}$ on the order of $10^{-16}\!-\!10^{-17}\ \mathrm{g\,L^{-1}\,s^{-1}}$ (numerical noise).

- Numerical integrator and step procedure (how the ODEs are solved)  
  - The code advances the ODE system $$\frac{d\mathbf{u}}{dt}=\mathbf{f}(\mathbf{u},t)$$ with an internal ODE integrator (scipy.integrate routines are used in the implementation) inside Stage.__step(), and port I/O updates are synchronized and applied after each internal step by Stage.__call_ports().

- Notes about parameters influencing the equations  
  - Relaxation times $\tau$ used in phase transfer / mechanism entries are derived from stage flow/residence time (e.g., entries in rxn_mech.data get a ['tau'] based on stg.flow_residence_time_avg).  
  - Partition coefficients (e.g., partition_o2_aqu, partition_n2_aqu) set equilibrium targets used in the transfer terms.  
  - Reaction rate densities in reports are given in $\mathrm{mM\,s^{-1}}$ (convert to $\mathrm{mol\,L^{-1}\,s^{-1}}$ by $10^{-3}$) before multiplying by molar mass to obtain $\mathrm{g\,L^{-1}\,s^{-1}}$.

- Limitation / unspecified detail (context)  
  - The KB does not provide explicit algebraic formulas for every transfer coefficient $K$ or every $\tau_{k,p\leftarrow q}$; where not specified the implementation uses mechanism entries (rxn_mech.data) and partition functions to set those quantities. If you want, I can extract the per‑reaction stoichiometries and the reported rate‑density time series from the provided data to build explicit numerical forms for each active $r_j(t)$.

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## User: What were the elapsed times for startup and steady-state? Show one Stage efficiency plot at start-up and an additional plot of Stage efficiency at steady-state. Include the image metadata.

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## Assistant: 

### Elapsed times — reported and simulated

- Simulation wall‑clock elapsed time for the reported run: 441.38 s (≈ 7 min 21.4 s).  
- Start‑up (physical simulated time window shown in the start‑up plot): sampled up to 48.1638 s (≈ 0.80 min).  
- Steady‑state (time axis in the steady‑state plot): spans $0$ to $6\,\tau$; the trajectory approaches steady state by $\approx 2\,\tau$ and is effectively settled by $\gtrsim 3\,\tau$ (within ~1% of the asymptote).  
- Note: to convert $\tau$ to seconds or minutes you must supply the numeric value of $\tau$ for that run (examples in the parametric study use $\tau_f\!=\!0.1,0.5,1.0,1.5\ \text{min}$).

### Start‑up plot (image metadata and caption)

- Title: Stage Efficiency @ 40.0 C Start‑Up plot.  
- DB table title: run simulation (module-run integration loop handles port I/O).  
- DB file_name: 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md.  
- img_filename: img_08.png.  
- VLM: gpt-5.  
- Caption: mean stage efficiency rises from ≈ 15% at start to ≈ 43% by the end of the sampled start‑up window; uncertainty narrows from ≈ ±21 percentage points at $t\!=\!0$ to ≈ ±9 pp at the end.  
- Image availability: an image is available and will be displayed after this response by the chat program.

### Steady‑state plot (image metadata and caption)

- Title: Stage Efficiency @ 40.0 C Steady‑State plot.  
- DB table title: run simulation (module-run integration loop handles port I/O).  
- DB file_name: 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md.  
- img_filename: img_21.png.  
- VLM: gpt-5.  
- Caption: stage efficiency rises quickly and asymptotes near $\approx 50.5\%$; by $t\!\approx\!1\,\tau$ $E\!\approx\!44\%$, by $t\!\approx\!2\,\tau$ $E\!\approx\!49$–$50\%$, and for $t\!\ge\!3\,\tau$ the mean and uncertainty are essentially steady (uncertainty $\approx\pm1$ pp).  
- Image availability: an image is available and will be displayed after this response by the chat program.

If you want, I can (a) embed the two images inline in a single PDF‑ready page layout, or (b) convert the reported $\tau$ benchmarks to explicit seconds using a chosen $\tau$ value.

 Image found in database 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md.

![ Stage Efficiency @ 40.0 C Start-Up plot.](data:image/png;base64,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 Image found in database 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md.

![ Stage Efficiency @ 40.0 C Steady-State plot.](data:image/png;base64,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```text
==========================================================================================
```

## User: Describe any parameter variation study setup and results, if available, and summarize lessons learned.

```text
==========================================================================================
```

## Assistant: 

### Parameter variation study — setup
- Study type: paired parametric sweep (4 runs) varying reaction relaxation scaling and inflow relative humidity together.  
- Reaction time‑scale factors swept: param_tau_factors = [0.1, 0.5, 1.0, 1.5].  
- Inflow relative‑humidity factors swept (matched to tau): param_inflow_rh_factors = [0.1, 0.5, 1.0, 1.5].  
- Implementation: for each run the base rxn_tau_factors tuple was multiplied by the chosen param_tau_factor to set the mechanism ['tau'] entries (params['tau-factor-0'] … params['tau-factor-8']); inflow-relative-humidity = 25 * param_inflow_rh_factor.  
- Runs executed: 4 runs (one per paired factor), each producing a stage object appended to stages and an efficiency time history with 17 samples (0 → 247.699 s, Δt ≈ 15.4812 s).  

### Quantitative results (final steady values at t = 247.699 s)
- $\tau=0.1$, RH = 2.5%: mean efficiency = 91.7541%, std = 2.13177%, CV ≈ 2.3%.  
- $\tau=0.5$, RH = 12.5%: mean efficiency = 69.3127%, std = 6.29286%, CV ≈ 9.1%.  
- $\tau=1.0$, RH = 25.0%: mean efficiency = 53.2426%, std = 7.76401%, CV ≈ 14.6%.  
- $\tau=1.5$, RH = 37.5%: mean efficiency = 43.7338%, std = 7.75183%, CV ≈ 17.7%.  
- Early‑time contrast (t ≈ 15.48 s): $\tau=0.1$: 81.5425%; $\tau=0.5$: 44.0396%; $\tau=1.0$: 29.5123%; $\tau=1.5$: 23.7769% (shows rapid separation by $\tau$).  

### Supporting diagnostics (mass flow & conservation)
- Mass residuals reported on the order of $10^{-16}$–$10^{-17}\ \mathrm{g\,L^{-1}\,s^{-1}}$ (numerical noise), indicating good numerical mass conservation.  
- Example inflow / outflow diagnostics printed per paired run:  
- $\tau=0.1$: total mass inflow = 7.478e+02 g/min; outflow = 7.462e+02 g/min; net = -1.593e+00 g/min.  
- $\tau=0.5$: total mass inflow = 7.525e+02 g/min; outflow = 7.507e+02 g/min; net = -1.790e+00 g/min.  
- $\tau=1.0$: total mass inflow = 7.540e+02 g/min; outflow = 7.471e+02 g/min; net = -6.939e+00 g/min.  
- $\tau=1.5$: total mass inflow = 7.366e+02 g/min; outflow = 7.393e+02 g/min; net = +2.717e+00 g/min.  

### Lessons learned and actionable recommendations
- Shorter relaxation times ($\tau$ small) produce higher final stage efficiency and lower variability: e.g., $\tau=0.1$ gives ≈92% ±2.1%, while $\tau=1.5$ gives ≈44% ±7.8%.  
- Transient behavior is strongly $\tau$‑dependent: small $\tau$ attains high efficiency rapidly; large $\tau$ yields slow approach and lower early and final efficiencies.  
- Relative uncertainty (CV) increases with $\tau$, meaning worse precision for larger relaxation times.  
- Because the study scaled inflow relative humidity in lockstep with $\tau$, the experiment cannot unambiguously separate the effects of $\tau$ and RH; recommendation: run orthogonal sweeps (vary $\tau$ while holding RH fixed and vice versa) to decouple effects.  
- Numerical/nondimensional guidance: choose time_step relative to the characteristic $\tau$ (in these runs ave_tau used and time_step = ave_tau/15) to ensure stable/accurate integration; small $\tau$ needs smaller time steps.  
- Operational recommendation: if the objective is high extraction efficiency and low variability, target operating conditions and process design that reduce effective relaxation times (improve mass‑transfer rates or reduce characteristic residence times where appropriate).  

### Suggested follow‑ups
- Decouple $\tau$ and inflow RH in a factorial design to quantify independent contributions.  
- Expand the parametric grid (more $\tau$ values and RH values) and compute sensitivity indices (e.g., Sobol) if a global sensitivity study is desired.  
- Report species‑level transfer and reaction sensitivities to identify which mechanisms are most $\tau$‑sensitive and may be targeted for process improvement.

```text
==========================================================================================
```

## User: Were there any surprising results from the simulations? or noteworthy aspects?

```text
==========================================================================================
```

## Assistant: 

### Surprising / noteworthy results (concise)

- Large absolute aqueous concentration increases were observed for $\mathrm{UO_2^{2+}(a)}$ (+22.84 g·L^{-1}) and $\mathrm{NO_3^-(a)}$ (+11.07 g·L^{-1}), which is notable given the active extraction chemistry.  
- The UO$_2$ extraction reaction ($\mathrm{UO_2^{2+}(a)+2\,NO_3^-(a)+2\,[C_4H_9O]_3PO(o)\leftrightarrow UO_2[NO_3]_2\cdot[[C_4H_9O]_3PO]_2(o)}$) shows the largest absolute and relative increase in reaction‑rate density (Col 5: $\sim$1.11×10^{-6} → 0.663 mM·s^{-1}$, factor $\approx6.0\times10^5$).  
- Neutral solvation/hydration rates (Cols 0–2) start high then fall monotonically while acid/nitrate/metal complexation rates (Cols 3–5) grow from near‑zero — the system shifts from solvation‑dominated to extraction‑dominated activity during start‑up.  
- Organic phase shows a very large TBP drawdown ($\mathrm{[C_4H_9O]_3PO(o)}$: 291.75 → 191.977 g·L^{-1}, ≈100 g·L^{-1} loss) while the $\mathrm{UO_2}$ complex accumulates strongly (final $\approx$ 68.3955 g·L^{-1}), indicating substantial mass transfer into the organic.  
- Steady‑state reaction efficiencies cluster tightly near $\approx50\%$ for most reactions, with the $\mathrm{H_2O(a)\leftrightarrow H_2O(v)}$ transfer unusually higher at $\approx54.32\%$, implying strong but finite phase‑transfer limitation.  
- Parametric study result is striking: very small relaxation/residence time ($\tau=0.1$) yields mean stage efficiency $\approx91.75\%$, whereas larger $\tau$ values give much lower efficiencies (e.g., $\tau=1.5$ → $\approx43.73\%$), showing strong sensitivity to mass‑transfer time scales.  
- The parametric study confounded $\tau$ and inflow relative humidity (RH) by scaling both together, which complicates attribution of effects to either parameter alone — this is a noteworthy experimental design caveat.  
- Species generation/consumption steady‑state averages show major net consumers ([TBP], $\mathrm{H_2O(a)}$, $\mathrm{NO_3^-(a)}$) and modest net producers (UO$_2$ complex, hydrated TBP complexes); however the summed production ($\approx+2.0623$ mM·s^{-1}) and consumption ($\approx-8.5844$ mM·s^{-1}) do not close internally, indicating additional flows/sinks not listed in the summary.  
- Shut‑down behavior is pronounced: when TBP inflow is cut the TBP consumption and coupled $\mathrm{UO_2}$ fluxes drop by orders of magnitude within one step and relax toward near‑zero, showing rapid process sensitivity to feed interruption.  
- Numerical diagnostics are good: total mass residuals reported $\sim10^{-16}$–$10^{-17}$ g·L^{-1}·s^{-1}$, indicating excellent numerical mass conservation for the implemented scheme.  

### Short implications / recommendations

- Decouple $\tau$ and RH in future sweeps to isolate their separate influences.  
- Investigate the non‑closed steady‑state production/consumption balance to locate unreported sinks/sources (port losses, untracked species, or reporting subset).  
- Target process changes that reduce effective relaxation times (improve mass transfer) if the objective is to raise stage efficiency (per the parametric results).

```text
==========================================================================================
```

## User: How would you go about simulating the shutdown of the mixer? Show examples of Cortix Solvex code snippets.

```text
==========================================================================================
```

## Assistant: 

### Overview — approach to simulating mixer shutdown
- Use the Stage/module time control to advance the simulation by a few flow‑residence times while changing inflow conditions (abrupt cut or ramp).  
- Synchronize shutdown actions to the stage time variables: set `stg.initial_time`, update `stg.end_time`, adjust `stg.time_step` and `stg.show_time` as needed, then call `system.run()`.  
- Two common patterns: (A) abrupt feed cut (set inflow species to zero and run until drained), (B) controlled ramp (step the inflow concentration or flowrate down in small time increments, running the network between adjustments).  
- After run(s) complete call `system.close()` and recover the stage (`stg = system_net.modules[0]`) to inspect time histories and diagnostics (mass residuals, efficiencies).  

### Key preparatory notes
- Use the stage flow‑residence time `stg.flow_residence_time_avg` to pick shutdown horizons (typical: 3 × residence time).  
- Monitor or disable diagnostics as desired: e.g., `stg.monitor_mass_flowrates`, `stg.monitor_mass_conservation_residual`.  
- Verify mass conservation residuals after the run (the context shows residuals ~1e‑16 to 1e‑17 g·L⁻¹·s⁻¹).  

### Example A — Abrupt TBP turn‑off (matches provided context)
```python
# shutdown horizon (3 residence times) and time stepping
end_time = stg.end_time + 3.0 * stg.flow_residence_time_avg
time_step = 3.0 * stg.flow_residence_time_avg / 20.0
show_time = (True, 10 * time_step)

stg.time_step = time_step
stg.initial_time = stg.end_time
stg.end_time = end_time
stg.show_time = show_time

# abrupt turn-off of TBP in the organic-phase inflow
tbp_org_name = 'TBP(o)'           # adjust name to actual species label in rxn_mech
tbp_mass_cc_org = 0.0 * unit.gram / unit.L
stg.inflow_organic_phase.set_value(tbp_org_name, tbp_mass_cc_org)

# run and close Cortix
stg.monitor_mass_flowrates = False
stg.monitor_mass_conservation_residual = False
system.run()
system.close()

# recover stage after the run
stg = system_net.modules[0]
```

### Example B — Stepwise ramp down of TBP concentration (controlled shutdown)
```python
# parameters for ramp
ramp_steps = 10
ramp_horizon = 3.0 * stg.flow_residence_time_avg
dt = ramp_horizon / float(ramp_steps)

# initial and final TBP inflow concentration (g/L)
tbp_initial = stg.inflow_organic_phase.get_value('TBP(o)')  # read current inflow conc (if supported)
tbp_final = 0.0 * unit.gram / unit.L

for i in range(ramp_steps):
    # compute per‑step end time and new TBP concentration
    new_end = stg.end_time + dt
    frac = float(i+1) / ramp_steps
    tbp_now = (1.0 - frac) * tbp_initial + frac * tbp_final

    # update time bounds and time_step for short-run
    stg.initial_time = stg.end_time
    stg.end_time = new_end
    stg.time_step = dt / 20.0
    stg.show_time = (True, 5 * stg.time_step)

    # set inflow TBP for this interval
    stg.inflow_organic_phase.set_value('TBP(o)', tbp_now)

    # run the network for this small interval
    system.run()

# final close
system.close()
stg = system_net.modules[0]
```

### Example C — Shut off volumetric inflow (drain the stage)
- The exact API for setting port volumetric flow depends on the Stage/Port object (not exhaustively documented in the provided context).  
- If supported, set the inflow volumetric flow to zero and run for a few residence times; otherwise set inflow species concentrations to zero as in Example A.  
```python
# Pseudocode (API may vary)
stg.inflow_organic_phase.volumetric_flow = 0.0 * unit.milliliter / unit.minute
stg.inflow_aqueous_phase.volumetric_flow = 0.0 * unit.milliliter / unit.minute

# advance time to allow draining
stg.initial_time = stg.end_time
stg.end_time = stg.end_time + 3.0 * stg.flow_residence_time_avg
stg.time_step = (3.0 * stg.flow_residence_time_avg) / 20.0
system.run()
system.close()
```

### Verification and post‑shutdown checks
- Recover the stage: `stg = system_net.modules[0]`.  
- Inspect time histories: `stg.organic_phase.time_stamps`, `stg.organic_phase.states` (or equivalent API) and computed efficiencies.  
- Check mass conservation residual and printed diagnostics (expected residuals near numerical noise levels in the context).  
- If you need a consistent restart later, serialize state if the API supports it (the context does not document a `save_state` API — if available use it; otherwise serialize the species arrays manually).  

### Practical recommendations / tips
- Use at least 3× the mean flow residence time for shutdown to allow the stage to approach the drained condition.  
- Pick `stg.time_step` small enough relative to the smallest relaxation time $\tau$ (context used `time_step = 3*res_time / 20` for abrupt shutdown).  
- Prefer a multi‑step ramp if abrupt chemistry changes cause numerical stiffness or if you want to capture transients without spurious oscillations.  
- Monitor `stg.monitor_mass_conservation_residual` during development; re‑enable it to ensure no mass leaks during shutdown tests.  

### Notes / caveats
- The exact port and flow APIs (e.g., property names for volumetric flow) are not fully specified in the provided context; where an API is uncertain I used the documented `set_value(name, value)` approach for port compositions and recommended checking the Stage/Port object for flow properties.  
- If you want, I can produce a ready‑to‑run shutdown script tailored to your exact Stage/Port API (please paste the port property names if they differ).

```text
==========================================================================================
```

## User: Describe and show one species concentration plot, with multiple species charts, for each of the phases, namely organic, aqueous, and vapor, at steady-state; include image metadata.

```text
==========================================================================================
```

## Assistant: 

### Steady‑state species concentration plots — Organic, Aqueous, Vapor

Below I describe one multi‑chart species concentration plot for each phase at steady state, summarize key steady values and behaviors, and include the image metadata.  
An image is available for each plot and will be displayed after this response by the chat program.

### Organic phase — multi‑chart species plot
- Plot description: multiple panels showing organic‑phase species time histories (0 → steady state).  
- Main species shown (steady values approx., units g·L^{-1}): $\mathrm{[C_4H_9O]_3PO(o)} \!\approx\! 191.98$, $\mathrm{H_2O\cdot[C_4H_9O]_3PO(o)} \!\approx\! 11.01$, $\mathrm{[H_2O]_2\cdot[[C_4H_9O]_3PO]_2(o)} \!\approx\! 2.29$, $\mathrm{[H_2O]_6\cdot[[C_4H_9O]_3PO]_3(o)} \!\approx\! 8.14$, $\mathrm{HNO_3\cdot[C_4H_9O]_3PO(o)} \!\approx\! 1.95$, $\mathrm{HNO_3\cdot[[C_4H_9O]_3PO]_2(o)} \!\approx\! 2.28$, $\mathrm{UO_2[NO_3]_2\cdot[[C_4H_9O]_3PO]_2(o)} \!\approx\! 68.40$, $\mathrm{[H_2O]_2\cdot[[C_4H_9O]_3PO]_2(o)} \!\approx\! 42.08$.  
- Behavior summary: rapid formation of TBP hydrates (monomer and dimer) within ~1 min, transient overshoot for some hydrate species, slower accumulation of the uranyl–TBP complex to a large steady mass, and a large net drawdown of free TBP (from ~292 g·L^{-1} → ~192 g·L^{-1}).  
- Axis scalers / notes: several panels use multipliers (e.g., ×$10^{1}$ or ×$10^{2}$) — check the axis label when reading each panel.  
- Image metadata:  
  - DB table title: run simulation (module-run integration loop handles port I/O)  
  - DB file_name: 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md  
  - img_filename: img_14.png  
  - VLM: gpt-5

### Aqueous phase — multi‑chart species plot
- Plot description: multiple panels showing aqueous‑phase species time histories (0 → steady state).  
- Main species shown (steady values approx., units g·L^{-1}): $\mathrm{H_2O(a)} \!\approx\! 9.87\times10^{2}$, $\mathrm{H^+(a)} \!\approx\! 5\times10^{-1}$, $\mathrm{N_2(a)} \!\approx\! 9.1\times10^{-3}$, $\mathrm{NO_3^-(a)} \!\approx\! 1.9\times10^{1}$, $\mathrm{O_2(a)} \!\approx\! 5.48\times10^{-3}$, $\mathrm{UO_2^{2+}(a)} \!\approx\! (8.5\text{–}8.8)\times10^{1}$.  
- Behavior summary: large increases in dissolved $\mathrm{NO_3^-}$ and $\mathrm{UO_2^{2+}}$ (tens of g·L^{-1}), modest acidification to $\sim0.5$ g·L^{-1}, small dissolved‑gas changes; water shows a slight nonmonotonic dip then recovers to a slightly lower plateau.  
- Axis scalers / notes: panels include scientific‑notation scalers (e.g., $\times10^{2}$ for water).  
- Image metadata:  
  - DB table title: run simulation (module-run integration loop handles port I/O)  
  - DB file_name: 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md  
  - img_filename: img_16.png  
  - VLM: gpt-5

### Vapor phase — multi‑chart species plot
- Plot description: multi‑panel vapor species plot at steady state (0 → steady state).  
- Main species shown (steady values approx., units g·L^{-1}): $\mathrm{H_2O(v)} \!\approx\! 2.719\times10^{-2}$, $\mathrm{N_2(v)} \!\approx\! 9.083\!\times\!10^{-1}$, $\mathrm{O_2(v)} \!\approx\! 2.579\!\times\!10^{-1}$.  
- Behavior summary: monotonic rises with first‑order–like relaxation; $\mathrm{H_2O(v)}$ equilibrates fastest (~1–2 min), $\mathrm{O_2(v)}$ and $\mathrm{N_2(v)}$ somewhat slower (N$_2$ ~3–5 min); N$_2$ dominates vapor mass.  
- Axis scalers / notes: $\mathrm{H_2O(v)}$ panel uses ×$10^{-2}$; $\mathrm{N_2(v)}$ and $\mathrm{O_2(v)}$ panels use ×$10^{-1}$.  
- Image metadata:  
  - DB table title: run simulation (module-run integration loop handles port I/O)  
  - DB file_name: 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md  
  - img_filename: img_18.png  
  - VLM: gpt-5

### Practical pointers for reading the plots
- Verify panel axis multipliers (e.g., ×$10^{1}$, ×$10^{2}$, ×$10^{-2}$) before interpreting tick numbers.  
- Use the provided numeric tables (supporting information) for exact sampled values if you need time‑stamp–level numbers rather than visual estimates.  
- If you want a single printable page (PDF) containing the three multi‑chart figures arranged for a letter page, I can prepare a layout (specify orientation: portrait or landscape).

 Image found in database 04-tbp-diluent-h2o-hno3-uo22plus-air-results-clean.md.

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![ Organic Phase Steady-State graph.](data:image/png;base64,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![ Organic Phase Steady-State graph.](data:image/png;base64,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i5c+fK399fMTEx+T4TAAAAAAAAkNPopAMAAAAgs+ikk0s5Oztr3Lhxeu655/Tee+9p6dKlSkxMlGTbFefuDjmpSS7ycXJy0lNPPaXx48erRo0ajgluMi8vrxT7rl69qqJFi5qQBgAAAAAA3KlmzZpavHixunTpolu3bkn6X6FOYmKiVq9erdWrV8vJyUk1a9ZU48aN5efnJw8PD+tCI1evXlVUVJQuXLigPXv26MiRI0pKSpL0v3sgd3YkdnV11a+//qpatWrl/AfOAk9PTz333HPq3LmzWrRooeLFi1vfS0xM1JYtW/T+++9ry5Yt1v1BQUHq37+/fv311wKTCQAAAAAA5B9t27Z12NgnTpzI1FyGYWj9+vUOy4O8h046AAAAADKLIp1crkaNGlq4cKFCQkL0448/6rffftNff/1lffjkXgzDUOPGjdWlSxf169dPFSpUcHBicyX/w/hO3t7eJiQBAAAAAACpad++vVasWKGePXsqKipKkm1RjXS78OPQoUM6fPhwumPd2X34znGS3/Pw8NCiRYvUvn17O34Cx6hcubLee+89Pffcc3Jzc0v1GGdnZ7Vu3VqBgYEaNGiQZsyYYX1v8eLFCgwMVJs2bfJ1JgAAAAAAkP9s3LgxQ4vUZlXyPSSLxaJNmzale5wjcyBvopMOAAAAgMyiSCePKF++vN599129++67iomJ0b59+3Ts2DGdO3dOV65c0Y0bN2SxWOTm5qaSJUuqfPnyuv/++9WgQQO5u7ubHT/H3LliqyRVqlRJLi4uJqUBAAAAAACpadu2rXbt2qXevXsrKCjI+vDD3UU2dxfhpCa1BycsFosaN26sefPm5YluwgEBAfL398/wPQxnZ2dNnz5dwcHB2rNnj3X/rFmz7FYQkxszAQAAAACA/C0j94IcNQfFOUhNdHS0oqOjJVGkAwAAACDjKNLJg9zd3dW8eXM1b97c7Ci5zuzZs222O3XqlO0xQ0NDFRYWlqlz7m6XHBMTo2vXrmU7S1Zdv3493W3kvOSbOJk9x9XV1QFpUsd1g6zgukFWcN0gK7hukBUF6bqJiYkxOwJwT9WrV9eOHTv07bffasKECdYVKVMr2MmI5AcsSpcurXfffVeDBg2Sk5OTfUM7SOfOnTN9jrOzs0aOHKmnn37auu/PP//M15kAAAAAAED+5qhCmTsLcyjGQWYk37MsUaJEgVokGQAAAED2UKSDfGPVqlXavHmzzb7+/ftne9zp06crICAgW2MEBQXp0qVL2c5iL0FBQWZHKPCuXr2a6XO2bt0qDw8PB6TJGK4bZAXXDbKC6wZZwXWDrMjP183Zs2fNjgBkiGEYevXVV/XCCy9o4cKFmjNnjrZs2aKEhIRUj5VSX+3U2dlZzZs3V//+/dWrVy8VKVLE4dlzgxYtWthsR0REKDY2VkWLFjUpUe7MBAAAAAAA8gYzO+kAqTl//rwkuugAAAAAyByKdJAvREZG6pVXXrHZ161bNzVt2tSkRAAAAAAAIKNcXV3Vp08f9enTR9euXdPWrVv1119/6dixYwoJCVFkZKRu3LghSXJzc5OXl5fKly+v+++/Xw0bNlSLFi1MXdTALF5eXin2Xb161dSCmNyYCcio8PDwdN/39vbOMx26AAAAACCvMgxDDz30kKZNmyYfH59sjWWxWNS5c2cdPXpUFotFhmHo5MmTdkqKgiC5k46fn5/JSQAAAADkJRTpIM9LSkpS7969FRISYt3n4eGhadOmmZgKAAAAAABkRYkSJdSpUyd16tTJ7Ci5XvJKnnfy9vY2Icn/5MZMKJi8vb0VGhqa5vvh4eGqXbu2zb67t+8WGhqa7QfEAAAAAAAptWzZUps3b7Z2Ut61a5c6deqkL774Qs8++2y2xnZxcbHZrlSpUrbGQ8GSXKRDJx0AAAAAmUGRDvK8ESNG6I8//rDZ991336lChQp2GX/QoEHq2bNnps45ceKEunXrZt1u2rSpatWqZZc8WXH9+nUFBQXZ5ClWrJhpeXDvlVlT07x5c5UqVcoBaVLHdYOs4LpBVnDdICu4bpAVBem6OXLkiNkRAOSALVu22GxXqlQpxYMnOS03ZkLB5OTkREENAAAAAOQRGzdu1LRp0/TOO+8oNjZWhmEoPDxcvXv31n//+1998803FEnAFMkL0tBJBwAAAEBmUKSDPG3atGn67LPPbPaNHDlSvXr1stscvr6+8vX1zdYY7u7uKlGihJ0SZV+xYsVyVZ6CyN3dXaGhoUpKStIjjzyiU6dOadKkSXrhhRfSPMfb21tOTk45mNIW1w2ygusGWcF1g6zgukFW5Ofrxt3d3ewIAHLA7NmzbbZzQ/eh3JgJAAAAAADkfkOHDlWnTp00YMAAbdu2TYZhyGKxaMWKFdq8ebM+/fTTdH+eDjgCnXQAAAAAZAVFOsizfv75Zw0bNsxmX//+/TVp0iRzAgGZkLya64oVK3Tq1Cl5enpq8ODBPEwJAAAAAMiQVatWafPmzTb7+vfvb06Y/89RmUJDQxUWFpapc06cOGGzHRMTo2vXrmU7S3Zcv3493W3krOjo6Cyd4+rq6oA0aeO6QWZxzSAruG6QFVw3yIqCdN3ExMSYHQHIk6pXr67Nmzdr6tSpGjNmjG7evClJunr1ql5++WX98ssvmjFjhipVqmRyUhQUdNIBAAAAkBUU6Ziobdu21q+rV6+uGTNmmJgmdQMHDrQ+1GAYhtavX29yottWrFihfv36yWKxWPf16NFDs2bNkmEYJiYDMufzzz+XJL388ssU6AAAAAAAMiQyMlKvvPKKzb5u3bqpadOmJiVybKbp06crICAgW2MEBQXp0qVL2c5iT0FBQWZHKNCuXr2a6XO2bt0qDw8PB6TJOK4bZBbXDLKC6wZZwXWDrMjP183Zs2fNjgDkWYZhaPjw4XriiSfUv39/7dy509pVZ+3atapbt64mTpyowYMHmx0VBQCddAAAAABkBUU6Jtq4caO1oCQqKsrcMGnYvXu3Dhw4IIvFkmuKXwIDA9WzZ08lJCRY9/n7+2vBggVydnY2MRmQOQcPHtT69evl7Oys1157zew4AAAAAIA8ICkpSb1791ZISIh1n4eHh6ZNm0YmAAAAAACQb9SoUUPbtm3TJ598orFjxyouLk7S7U5VQ4cO1S+//KLZs2erevXqJidFfpWUlGQt0qGTDgAAAIDMoEgnF7izGwzSt2vXLnXp0sXa0liSHn30US1dulQuLi4mJgMyL/lhpe7du6tixYompwEAAAAA8505c0Z//fWXjhw5on///VeXL19WeHi4rl+/rri4OBmGoSJFisjT01Nly5ZV1apVVbduXT366KOqVKmS2fFzxIgRI/THH3/Y7Pvuu+9UoUIFkxLlzkwAAAAAACDvMwxDI0eO1JNPPql+/fppz5491q46W7duVf369TVu3Di99dZbuWbhWeQfERERio+Pl2EYKlOmjNlxAAAAAOQhFOkgzzhw4IA6duyomJgY674GDRpo1apVKlasmInJgMwLCwvTTz/9JEkaNmyYuWEAAAAAwEQ7d+7UvHnztHLlSp09ezbF+6ktbpLaQxdVqlRRr1691L9/f913330OyWq2adOm6bPPPrPZN3LkSPXq1cukRDmTadCgQerZs2emzjlx4oS6detm3W7atKlq1aplt0xZcf36dQUFBVm3mzZtyj0tE4WHh2f6nObNm6tUqVIOSJM2rhtkFtcMsoLrBlnBdYOsKEjXzZEjR8yOAOQrtWrV0s6dO/Xxxx8rICBA8fHxkqQbN25o1KhR+vXXXzV79mzVqVPH5KTIT86fPy9J8vX1VeHChU1OAwAAACAvoUgHecKxY8fk7++vK1euWPfVqlVLf/75pzw8PExMBqQuKSlJERERab4/depU3bp1S/Xr19d9992nsLAweXt7y8nJKQdTAgAAAIB5VqxYoXHjxmnv3r2S7t1pOLkwx2KxpHrsyZMnNWnSJH388cfq1q2bJk6cmK+KdX7++ecUizz0799fkyZNMieQci6Tr6+vfH19szWGu7u7SpQoYadE9lGsWLFcl6kguXXrVqbPKV68uOm/Z1w3yCyuGWQF1w2ygusGWZGfrxt3d3ezIwD5jpOTk0aPHq0uXbqoX79+Cg4OtnbV2b17txo1aqR33nlH77zzjgoV4nEoZN+FCxckSeXKlTM5CQAAAIC8hqfBkeudOXNG7du3V2hoqHVflSpVtHbtWvn4+JiYDEhbRESE9SGi1F4TJ06UJO3fv1+lS5eWr69vukU9AAAAAJBfXLlyRd26dVPXrl21d+9ea9GNYRjpvpKld4zFYlFSUpKWLl2qunXravz48fcs/skLVqxYoX79+tl8lh49emjWrFmpdhUqqJkAAAAAAED+V6dOHe3atUsBAQEqVKiQ9b5QXFycAgIC1LhxYwUHB5sdE/lAcicdinQAAAAAZBZLR+QShw8fVtWqVc2OkULyqhBmuXjxotq1a6eQkBDrPj8/P61fv15+fn4mJgMAAAAAAJl18uRJ+fv76/Tp09bijowWdGSk086d3Xbi4uI0duxYbdmyRYsXL86zqxgHBgaqZ8+eSkhIsO7z9/fXggUL5OzsTCYgB4WHh9/zGDolAwAAAIDjOTs7a8yYMeratav69eun/fv3WxdwOXDggB5++GG9+eabGjdunNlRkYclPzPF80kAAAAAMosinVwiLi5Op0+fNjtGqsxa/TQyMlL+/v76999/rft8fHy0du1aValSxZRMAAAAAAAga8LDw9W2bVudPXtWkmwKapIZhqESJUooNjZW8fHxNvuTH7QoW7asPv74Yzk5Oenq1as6cuSIDhw4oL179yo6OjrF2OvWrVP79u21YcMGFS1aNKc+rl3s2rVLXbp00c2bN637Hn30US1dulQuLi5kAnJY7dq173lMaGgo3b8BAAAAIIfUq1dPu3fv1ocffqiJEycqMTFRkpSQkKDJkydr6dKlio6OzhedlpHz6KQDAAAAIKso0skFzCqCyc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```text
==========================================================================================
```

## User: What are the top 5 pressing technical questions I should ask about this work?

```text
==========================================================================================
```

## Assistant: 

### Top 5 pressing technical questions

1. Are the reaction relaxation time scaling ($\tau$) and inflow relative‑humidity (RH) effects decoupled in the design?; rationale: the parametric study multiplied $\tau$ and RH together so attribution is confounded; ask for an orthogonal factorial sweep (vary $\tau$ while holding RH fixed and vice‑versa) and compute sensitivity indices (e.g., Sobol or partial derivatives) to quantify independent contributions.

2. What are the per‑species partition coefficients and the explicit phase‑transfer resistances (or $\tau_{p\leftarrow q}$) used in the model?; rationale: phase transfer formulations control inter‑phase fluxes (strongly influence $\mathrm{TBP}$ drawdown and $\mathrm{UO_2^{2+}}$ uptake); request the numerical $K$ values, how they were derived (literature, fit, or assumed), and the mapping from mechanism ['tau'] to physical transfer rates.

3. How does the kinetic model compare against an equilibrium (thermodynamic) prediction for extraction (i.e., what would $E\to100\%$ equilibrium imply)?; rationale: stage efficiencies $E$ are far below 100% (kinetic/mass‑transfer limited); ask for a run enforcing local equilibrium (fast kinetics), compare species distributions and quantify error metrics (absolute and relative) vs the kinetic runs and time to approach equilibrium.

4. Is total mass/species balance fully closed for all reported time histories, and where do any non‑zero residuals originate?; rationale: summaries indicated some production/consumption sums that do not internally close and net mass flow mismatches; request full port flow logs, per‑species generation terms, and the mass residual time series to locate sinks (untracked species, numerical leak, ouputs) and confirm conservation within tolerances.

5. Are the time‑integration choices and solver settings adequate given possible stiffness (small $\tau$) and are results time‑step converged?; rationale: small $\tau$ requires small time steps and/or implicit stiff solvers; ask for solver name and tolerances, time_step vs min($\tau$) ratios, CPU elapsed times, and a time‑step/refinement convergence study (compare key outputs like $E(t)$ and species concentrations for e.g. time_step, time_step/2, time_step/4).

```text
==========================================================================================
```

## User: What is your evaluation of the content of this usecase? Feel free to consult the Supporting Information sections of the database.

```text
==========================================================================================
```

## Assistant: 

### Overall evaluation
- The usecase presents a coherent mixed‑phase solvent‑extraction Stage implementation that couples aqueous, organic and vapor phases with a reaction mechanism and time integration, and it demonstrates end‑to‑end simulation results (transients, steady behavior and a small parametric study).
- The report provides useful diagnostics (mass residuals, per‑reaction efficiencies, species time histories, elapsed wall‑clock time) that support confidence in the numerical implementation.
- The parametric study clearly illustrates dominant sensitivity to the relaxation/residence time parameter $\tau$ (but is confounded by RH being scaled together with $\tau$).

### Strengths
- Mass conservation diagnostics show residuals near numerical noise ($\sim10^{-16}$–$10^{-17}\ \mathrm{g\,L^{-1}\,s^{-1}}$), indicating good implementation of conservation checks.
- The Stage module API and internal methods are well documented in the context (e.g., Stage.run(), Stage.__step(), Stage.__call_ports(), __mbal_rhs_func(...)), enabling reproducibility of the run loop sequence.
- Reports include both transient startup behavior and long‑time steady values plus statistical summaries (mean/std/CV), which help quantify variability and convergence.
- Multiple useful plots and image metadata are available for start‑up, steady‑state and species concentrations across phases, aiding visual validation.
- Practical shutdown and perturbation examples are provided, with code snippets illustrating how to perform abrupt or ramped feed changes.

### Weaknesses and missing information
- Per‑species partition coefficients and explicit numerical phase‑transfer coefficients ($K_{p\leftarrow q}$ and $\tau_{k,p\leftarrow q}$) are not fully enumerated in the report; these parameters are central to interpreting the kinetics vs equilibrium behavior.
- The reaction rate laws (functional forms and parameter values) for each mechanism entry are not listed explicitly; only stoichiometries and observed rate histories are given.
- The parametric study couples $\tau$ and inflow relative humidity (RH) together, which prevents attribution of effects to each factor independently.
- Solver details are incomplete: the exact integrator (name, implicit/explicit, tolerances) and stiffness handling strategy are not fully specified in the text.
- Some summary tables indicate non‑closed production/consumption sums, suggesting either omitted flows/sinks in the excerpt or that only a subset of species were reported; the origin of those imbalances is not fully clarified in the supporting data.
- Units and scaling in some plots require close attention (axis multipliers) and might cause misinterpretation unless numeric tables are consulted.

### Data quality and reproducibility assessment
- Numerical conservation checks and reproducible time‑stamp arrays (17 samples for parametric runs, consistent spacing) support reproducibility of reported statistics.
- Wall‑clock runtime for the reported run (441.38 s) and examples of run logs are provided, which helps reproduce computational resource needs.
- Missing explicit parameter lists (partition coefficients, rate constants, solver options) reduce full reproducibility unless the rxn_mech.data and full input scripts are made available.
- The presence of image filenames and metadata (img_08.png, img_14.png, etc.) facilitates visual reproducibility, assuming the image assets are bundled with the database.

### Key technical issues to address (priority)
- Decouple $\tau$ and RH in parametric studies to isolate the physical influence of mass‑transfer time scales vs vapor humidity on extraction efficiency.
- Publish the full rxn_mech.data contents: species list, molar masses, stoichiometries, rate law functional forms, and numerical rate parameters.
- Report explicit partition coefficients and mapping from the mechanism ['tau'] entries to physical transfer coefficients so results can be interpreted physically (or compared to experimental mass‑transfer coefficients).
- Provide solver configuration (integrator type, relative/absolute tolerances, Jacobian options) and perform a time‑step/stiffness convergence study for representative small and large $\tau$ cases.
- Clarify and close any apparent bookkeeping gaps in reaction production/consumption summaries by providing full per‑species port flow logs and the complete set of tracked species.

### Recommended experiments and verification runs
- Orthogonal factorial sweep: vary $\tau$ at fixed RH and vary RH at fixed $\tau$ (full grid) to generate sensitivity surfaces and compute sensitivity indices (local derivatives and global Sobol indices).
- Equilibrium reference runs: enforce very fast kinetics (small $\tau$ or equilibrium assumption) to compute thermodynamic limits of extraction and compare to kinetic results to quantify kinetic limitation.
- Time‑step convergence study: run one small‑$\tau$ and one large‑$\tau$ case with time_step, time_step/2, time_step/4 and compare $E(t)$ and major species concentrations at common time stamps.
- Synthetic shutdown tests: abrupt cut and ramped cut with conserved mass diagnostics to ensure no hidden leaks and to characterize transient relaxation times for key species (e.g., $\mathrm{UO_2^{2+}}$).
- Laboratory validation: measure partition coefficients and mass‑transfer coefficients for $\mathrm{UO_2^{2+}}$, $\mathrm{HNO_3}$ and water/TBP systems under comparable conditions to parameterize and validate the model.

### Practical suggestions for documentation and dissemination
- Include a compact input deck (JSON/YAML) for each reported run containing all numeric parameters (flows, temperatures, rxn_mech entries, $\tau$ values, partition coefficients, solver options).
- Attach the full rxn_mech.data export and a README that maps data fields to physical quantities and units.
- Produce a short methods appendix that documents the ODE solver choice, tolerances, and mass‑conservation checks used during production runs.
- Publish the parametric results as a matrix (CSV) and include scripts (or Jupyter notebooks) to reproduce the figures and statistics.

### Final concise verdict
- The usecase is a well‑constructed demonstration of a mixed‑phase extraction Stage with credible numerical diagnostics and instructive parametric trends (notably strong $\tau$ sensitivity).  
- To reach production‑grade confidence and enable independent reproduction and mechanistic interpretation, provide the missing numerical details (partition coefficients, rate laws, solver settings), decouple confounded parameters in studies, and perform targeted verification runs (time‑step convergence and equilibrium comparisons).

## AI Discussion Control Parameters 
  + **Database:** CT_Solvex_db 
  + **Database table:** usecase-04 
  + **RAG # records:** 10 
  + **RAG search:** vector 
  + **Memory # questions:** 10 
  + **LLM:** gpt-5-mini 
  + **LLM cleverness:** 1.0 
  + **Total # tokens:** 166733 
  + **Discussion history size:** 26 
  + **Embedded images:** 5