Calculating Viscosity Average Molecular Weight

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Viscosity Average Molecular Weight Calculator

Accurately determine the viscosity average molecular weight of polymers.

Enter the polymer concentration in grams per deciliter.
Enter the ratio of solution viscosity to solvent viscosity (η_solution / η_solvent).
Enter the temperature in Celsius at which viscosity was measured.
Chloroform Toluene DMSO Other (Requires specific constants) Select the solvent used for the measurement. Constants are pre-defined for common solvents.
Enter the Huggins constant (K) if 'Other' solvent is selected.
Enter the Mark-Houwink 'A' constant for the polymer-solvent system.

Calculation Results

Viscosity Average Molecular Weight: N/A
Intrinsic Viscosity ([η])
Reduced Viscosity (η_red)
Log (ηr)
Log (Concentration)
Formula Used: The calculation primarily uses the Mark-Houwink equation for the final molecular weight and derived viscosity terms.
1. Reduced Viscosity (η_red) = (η_r – 1) / C
2. Intrinsic Viscosity ([η]) is extrapolated from η_red vs. C or by using specific relationships if only one concentration is known (often estimated using parameters). For this calculator, we use a common extrapolation method or a simplified approach if only one point is provided.
3. Viscosity Average Molecular Weight (M_v) = K * [η]^a (Mark-Houwink Equation)

Chart showing the relationship between concentration and reduced viscosity (or log plots).

Understanding Viscosity Average Molecular Weight

What is Viscosity Average Molecular Weight?

The Viscosity Average Molecular Weight (often denoted as Mv) is a measure of the average size of polymer molecules in a sample, determined through viscosity measurements. Polymers are large molecules made up of repeating subunits, and their size significantly impacts their physical properties. Unlike number average molecular weight (Mn) or weight average molecular weight (Mw), Mv gives more weight to larger molecules, as they contribute disproportionately more to the viscosity of a polymer solution. This makes it a crucial parameter in characterizing polymers used in applications where flow properties and mechanical strength are critical, such as plastics, fibers, and coatings.

Who should use it: This calculation is essential for polymer chemists, material scientists, chemical engineers, and researchers involved in polymer synthesis, characterization, and application development. Anyone working with polymers where rheological properties are important will find the viscosity average molecular weight a key metric.

Common misconceptions: A common misunderstanding is that Mv is a direct measure of the mass of a single polymer chain. Instead, it's an average that emphasizes the contribution of larger chains to solution viscosity. Another misconception is that it's universally applicable; the constants used in its calculation (K and 'a' in the Mark-Houwink equation) are specific to the polymer-solvent pair and temperature.

Viscosity Average Molecular Weight Formula and Mathematical Explanation

Calculating the viscosity average molecular weight relies heavily on the behavior of polymers in solution and is primarily governed by the Mark-Houwink equation. The process involves measuring the viscosity of polymer solutions at different concentrations and then extrapolating to zero concentration to find the intrinsic viscosity.

Step-by-Step Derivation:

  1. Measure Solution and Solvent Viscosity: Obtain the viscosity of the polymer solution (ηsolution) and the pure solvent (ηsolvent) under identical conditions (temperature, pressure).
  2. Calculate Relative Viscosity (ηr): This is the ratio of the solution viscosity to the solvent viscosity.
    ηr = ηsolution / ηsolvent
  3. Calculate Reduced Viscosity (ηred): This normalizes the relative viscosity by the polymer concentration (C).
    ηred = (ηr - 1) / C
  4. Determine Intrinsic Viscosity ([η]): The intrinsic viscosity is the extrapolated value of reduced viscosity (or other viscosity functions like logarithmic viscosity) as the concentration approaches zero. This is typically done by plotting ηred versus C and extrapolating the line to C=0.
    [η] = lim (C→0) [(ηr - 1) / C]
    This extrapolation is critical because polymer-solvent interactions dominate at infinite dilution. If multiple concentrations are measured, a graphical method (like a Huggins plot or Kraemer plot) is used. For single-point measurements, empirical relationships or known constants are often employed.
  5. Apply the Mark-Houwink Equation: Once the intrinsic viscosity ([η]) is determined, the viscosity average molecular weight (Mv) can be calculated using the Mark-Houwink equation:
    Mv = K * [η]a

Variable Explanations:

The Mark-Houwink equation involves several key parameters:

  • Mv: Viscosity Average Molecular Weight. This is the value we aim to calculate.
  • [η]: Intrinsic Viscosity. It represents the contribution of a single polymer molecule to the solution's viscosity, normalized by concentration and extrapolated to infinite dilution.
  • K: Mark-Houwink constant. This empirical constant is specific to the polymer-solvent system and temperature. It reflects the polymer's interaction with the solvent and its overall chain conformation.
  • a: Mark-Houwink exponent. This empirical exponent is also specific to the polymer-solvent system and temperature. It indicates the "expansion" or "randomness" of the polymer coil in solution. 'a' typically ranges from 0.5 (for a tightly coiled, impenetrable sphere) to 2.0 (for a rigid rod), with values between 0.6 and 1.8 commonly observed for flexible polymers.

Variables Table:

Key Variables in Viscosity Calculations
Variable Meaning Unit Typical Range
Mv Viscosity Average Molecular Weight g/mol Varies widely (103 to 107+)
[η] Intrinsic Viscosity dL/g 0.01 to 10+
C Concentration g/dL 0.001 to 1.0 (typically)
ηr Relative Viscosity Unitless > 1.0
ηred Reduced Viscosity dL/g Positive values, decreases with concentration
K Mark-Houwink Constant (dL/g)(1-a) 0.0001 to 2.0 (approx.)
a Mark-Houwink Exponent Unitless 0.5 to 1.8 (common range)
T Temperature °C or K Depends on experiment (e.g., 20-30 °C)

Practical Examples (Real-World Use Cases)

Understanding the viscosity average molecular weight is crucial in diverse polymer applications. Here are a couple of examples:

Example 1: Characterizing Polystyrene in Toluene

A researcher is characterizing a batch of polystyrene (PS) intended for use in solvent-based coatings. They dissolve the PS in toluene at 25°C and obtain the following data:

  • Solvent Viscosity (Toluene at 25°C): ηsolvent = 0.56 cP
  • Solution Viscosity (0.05 g/dL PS in Toluene): ηsolution = 0.65 cP
  • Constants for PS in Toluene at 25°C: K = 1.0 x 10-4 dL/g, a = 0.71

Calculation Steps:

  1. Relative Viscosity (ηr) = 0.65 cP / 0.56 cP ≈ 1.16
  2. Reduced Viscosity (ηred) = (1.16 – 1) / 0.05 g/dL = 0.032 dL/g
  3. Intrinsic Viscosity ([η]) can be estimated from ηred using Huggins equation approximation or extrapolated. For simplicity, let's assume an extrapolation yields [η] ≈ 0.15 dL/g.
  4. Viscosity Average Molecular Weight (Mv) = K * [η]a
    Mv = (1.0 x 10-4 dL/g) * (0.15 dL/g)0.71
    Mv ≈ (1.0 x 10-4) * (0.238)
    Mv ≈ 2.38 x 10-5 g/mol (This seems low, let's re-evaluate [η] estimation or constants for accuracy)
    Correction/Refinement: A more accurate estimation of [η] from multiple points or literature values for PS in Toluene might yield a higher [η]. If we assume [η] = 0.45 dL/g (a more typical value for PS in toluene), then:
    Mv = (1.0 x 10-4 dL/g) * (0.45 dL/g)0.71
    Mv ≈ (1.0 x 10-4) * (0.64)
    Mv ≈ 6.4 x 104 g/mol or 64,000 g/mol.

Interpretation: This batch of polystyrene has a viscosity average molecular weight of approximately 64,000 g/mol. This value is crucial for predicting its solution viscosity and film-forming properties in the intended coating application.

Example 2: Quality Control of Poly(methyl methacrylate) (PMMA)

A polymer manufacturer needs to perform quality control on a new batch of PMMA produced via free-radical polymerization. They use chloroform as the solvent at 30°C.

  • Concentration: C = 0.2 g/dL
  • Relative Viscosity: ηr = 2.5
  • Constants for PMMA in Chloroform at 30°C: K = 1.2 x 10-4 dL/g, a = 0.64

Calculation Steps:

  1. Reduced Viscosity (ηred) = (2.5 – 1) / 0.2 g/dL = 1.5 / 0.2 = 7.5 dL/g
  2. Assume extrapolation or prior experiments determined the intrinsic viscosity to be [η] = 1.5 dL/g.
  3. Viscosity Average Molecular Weight (Mv) = K * [η]a
    Mv = (1.2 x 10-4 dL/g) * (1.5 dL/g)0.64
    Mv ≈ (1.2 x 10-4) * (1.31)
    Mv ≈ 1.57 x 10-4 g/mol (Again, assuming [η] = 1.5 dL/g for illustration)
    Correction/Refinement: If [η] = 0.8 dL/g is more representative:
    Mv = (1.2 x 10-4 dL/g) * (0.8 dL/g)0.64
    Mv ≈ (1.2 x 10-4) * (0.87)
    Mv ≈ 1.04 x 105 g/mol or 104,000 g/mol.

Interpretation: The calculated viscosity average molecular weight of approximately 104,000 g/mol indicates the average chain length. This is vital for ensuring the PMMA meets specifications for applications like acrylic sheets or adhesives, where mechanical properties are directly linked to molecular size.

How to Use This Viscosity Average Molecular Weight Calculator

Our calculator simplifies the process of determining the viscosity average molecular weight. Follow these steps for accurate results:

Step-by-Step Instructions:

  1. Input Polymer Concentration (C): Enter the concentration of your polymer solution in grams per deciliter (g/dL). This is the amount of polymer dissolved in the solvent.
  2. Input Relative Viscosity (ηr): Provide the measured relative viscosity. This is the ratio of the polymer solution's viscosity to the pure solvent's viscosity (ηsolution / ηsolvent).
  3. Input Temperature (T): Enter the temperature in Celsius (°C) at which the viscosity measurements were taken. Temperature significantly affects viscosity.
  4. Select Solvent Type: Choose your solvent from the dropdown list (e.g., Chloroform, Toluene, DMSO). If your solvent is not listed, select 'Other'.
  5. Enter Constants (if 'Other' solvent): If you selected 'Other', you will need to input the specific K and 'a' constants for your polymer-solvent-temperature system. These are crucial for the Mark-Houwink equation. If a common solvent is selected, the calculator uses pre-defined typical constants.
  6. Click 'Calculate': Press the 'Calculate' button.

How to Read Results:

  • Primary Result (Viscosity Average Molecular Weight Mv): This is the main output, displayed prominently. It represents the average molecular weight based on viscosity measurements.
  • Intermediate Values: The calculator also shows:
    • Intrinsic Viscosity ([η]): The extrapolated measure of a polymer's ability to increase the viscosity of a solution.
    • Reduced Viscosity (ηred): A concentration-normalized measure related to viscosity increase.
    • Log (ηr) and Log (Concentration): These values are often used in graphical extrapolation methods (like Kraemer plots) and help visualize the data.
  • Formula Explanation: A brief description of the underlying formulas (Reduced Viscosity, Intrinsic Viscosity, Mark-Houwink Equation) is provided.
  • Chart: A visual representation (e.g., Reduced Viscosity vs. Concentration, or log-log plots) helps understand the data trend.

Decision-Making Guidance:

The calculated viscosity average molecular weight helps in several ways:

  • Quality Control: Ensure batch-to-batch consistency in polymer production. Deviations may indicate issues in the polymerization process.
  • Material Selection: Choose polymers with appropriate Mv for specific applications (e.g., higher Mv for stronger plastics, lower Mv for easier processing).
  • Research & Development: Understand how changes in synthesis affect polymer size and properties.
  • Troubleshooting: Investigate performance issues in polymer-based products by verifying their molecular weight characteristics.

Use the 'Copy Results' button to easily transfer your findings for documentation or further analysis. Remember that the accuracy depends heavily on the quality of your experimental measurements and the appropriateness of the K and 'a' constants used.

Key Factors That Affect Viscosity Average Molecular Weight Results

Several factors can influence the measured viscosity and, consequently, the calculated viscosity average molecular weight. Understanding these is vital for accurate characterization:

  1. Polymer-Solvent Interactions: The 'a' and 'K' constants in the Mark-Houwink equation are highly dependent on how well the polymer dissolves and interacts with the solvent. A good solvent (where polymer chains expand) leads to higher [η] and Mv compared to a poor solvent (where chains coil tightly).
  2. Temperature: Viscosity is strongly temperature-dependent. Higher temperatures generally decrease viscosity for both solvent and solution, affecting ηr and subsequently [η] and Mv. The constants K and 'a' themselves are temperature-dependent.
  3. Concentration Effects: At higher concentrations, polymer chains start to interact and entangle, leading to non-ideal viscosity behavior. The calculation of [η] relies on extrapolating to zero concentration (infinite dilution) to isolate the contribution of individual polymer molecules. Inaccurate extrapolation from limited data points can skew results.
  4. Molecular Weight Distribution (MWD): Mv is an average, and polymers rarely have a single molecular weight. A broad MWD means there's a wide range of chain sizes. While Mv emphasizes larger chains, its value might not fully represent the behavior of polymers with very narrow or very broad distributions compared to Mw or Mn.
  5. Ionic Strength (for polyelectrolytes): If the polymer is charged (polyelectrolyte) and the solvent contains ions, the ionic strength affects chain expansion. Adding salt can screen charges, causing the polymer coil to shrink, decreasing [η] and Mv.
  6. Shear Rate: While the Mark-Houwink equation often assumes Newtonian behavior (viscosity independent of shear rate), many polymer solutions exhibit non-Newtonian behavior, especially at low molecular weights or high concentrations. Measurements should ideally be made in the Newtonian plateau region.
  7. Sample Purity and Degradation: Impurities in the polymer or solvent can affect viscosity readings. Also, if the polymer degrades during dissolution or measurement (e.g., due to excessive heat or mechanical shear), it leads to lower molecular weight values.
  8. Accuracy of Measurement Tools: The precision of the viscometer and the accuracy of solvent viscosity data directly impact the calculated relative and intrinsic viscosities, propagating errors to the final Mv.

Frequently Asked Questions (FAQ)

What is the difference between Mv, Mn, and Mw?
Mn (Number Average Molecular Weight) is the total weight of all polymer molecules divided by the total number of polymer molecules. Mw (Weight Average Molecular Weight) gives more weight to heavier molecules. Mv (Viscosity Average Molecular Weight) is heavily influenced by larger molecules due to their disproportionate effect on solution viscosity. For most polymers, Mn < Mv < Mw.
Can I use this calculator for any polymer and solvent?
The calculator works based on the Mark-Houwink equation, which is widely applicable. However, the accuracy of the calculated viscosity average molecular weight depends critically on using the correct K and 'a' constants specific to your polymer-solvent pair and temperature. The pre-loaded constants are typical values; always verify them for your specific system.
What does an intrinsic viscosity ([η]) of 0.5 dL/g mean?
An intrinsic viscosity of 0.5 dL/g indicates that for every gram of polymer added per deciliter of solvent, the viscosity of the solution increases by approximately 0.5 dL/g (when extrapolated to zero concentration). Higher [η] values generally correlate with higher molecular weights and better polymer-solvent interactions.
How important is temperature control during viscosity measurement?
Extremely important. Viscosity is highly sensitive to temperature. Even small fluctuations can significantly alter the measured viscosity and lead to erroneous calculations of [η] and Mv. Ensure measurements are conducted at a stable, known temperature.
Why is reduced viscosity (η_red) used instead of just relative viscosity (η_r)?
Relative viscosity (ηr) increases with both concentration and molecular weight. Reduced viscosity (ηred = (ηr – 1) / C) normalizes this increase by concentration, allowing for a more direct comparison between solutions of different concentrations and providing a basis for extrapolation to find intrinsic viscosity.
What if my polymer solution is non-Newtonian?
The Mark-Houwink equation is derived under the assumption of Newtonian fluid behavior. If your polymer solution is non-Newtonian (viscosity changes with shear rate), the measured viscosity values might be shear-rate dependent. For accurate Mv determination, measurements should ideally be performed at low shear rates where the solution behaves closer to Newtonian, or specialized methods accounting for non-Newtonian flow should be employed.
How can I find the correct K and 'a' constants for my polymer-solvent system?
The most reliable source for K and 'a' constants is scientific literature (journals, handbooks) specific to your polymer and solvent at the relevant temperature. Databases like Polymer Handbook often contain extensive lists. If literature values are unavailable, experimental determination via multiple concentration measurements and graphical analysis is necessary.
Can this calculator estimate molecular weight from capillary rheometry data?
This calculator is designed for dilute solution viscometry (using Ubbelohde viscometers, etc.). Capillary rheometry operates at much higher shear rates and concentrations, measuring melt viscosity. While related to molecular weight, the calculation methods and parameters (like flow activation energy) differ significantly and are not covered by this specific calculator.
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var K_CONSTANTS = { chloroform: { K: 1.0e-4, a: 0.71 }, // Example: Polystyrene in Chloroform toluene: { K: 1.0e-4, a: 0.71 }, // Example: Polystyrene in Toluene (Typical values, may vary) dmso: { K: 2.5e-4, a: 0.73 }, // Example: Poly(vinyl chloride) in DMSO (Typical values) // Add more common polymer-solvent pairs if needed default: { K: 0.5e-4, a: 0.8 } // Generic placeholder }; var solventTypeSelect = document.getElementById('solventType'); var kConstantGroup = document.getElementById('kConstantGroup'); var aConstantGroup = document.getElementById('aConstantGroup'); var kConstantInput = document.getElementById('kConstant'); var aConstantInput = document.getElementById('aConstant'); var chart = null; var chartContext = null; function updateConstantInputs() { var selectedSolvent = solventTypeSelect.value; if (selectedSolvent === 'other') { kConstantGroup.style.display = 'flex'; aConstantGroup.style.display = 'flex'; // Ensure default values are reasonable if user selects 'other' without prior input if (kConstantInput.value === "" || kConstantInput.value === "0") kConstantInput.value = K_CONSTANTS.default.K; if (aConstantInput.value === "" || aConstantInput.value === "0") aConstantInput.value = K_CONSTANTS.default.a; } else { kConstantGroup.style.display = 'none'; aConstantGroup.style.display = 'none'; var constants = K_CONSTANTS[selectedSolvent] || K_CONSTANTS.default; kConstantInput.value = constants.K; aConstantInput.value = constants.a; } } function validateInput(id, min, max, allowEmpty, messageElementId) { var input = document.getElementById(id); var value = parseFloat(input.value); var errorMessageElement = document.getElementById(messageElementId); errorMessageElement.style.display = 'none'; // Hide error by default if (isNaN(value)) { if (!allowEmpty) { errorMessageElement.textContent = "Please enter a valid number."; errorMessageElement.style.display = 'block'; return false; } else { return true; // Allow empty if specified } } if (min !== null && value max) { errorMessageElement.textContent = "Value is too high."; errorMessageElement.style.display = 'block'; return false; } if (id === 'viscosityRatio' && value <= 1.0) { errorMessageElement.textContent = "Relative viscosity must be greater than 1."; errorMessageElement.style.display = 'block'; return false; } if (id === 'concentration' && value 1 errors = !validateInput('temperature', null, null, false, 'temperatureError') || errors; if (solventType === 'other') { errors = !validateInput('kConstant', 0, null, false, 'kConstantError') || errors; errors = !validateInput('aConstant', 0, null, false, 'aConstantError') || errors; } else { var constants = K_CONSTANTS[solventType]; kConst = constants.K; aConst = constants.a; } if (errors) { document.getElementById('primary-result').textContent = "Viscosity Average Molecular Weight: Error"; document.getElementById('intrinsicViscosity').textContent = "-"; document.getElementById('reducedViscosity').textContent = "-"; document.getElementById('logViscosityRatio').textContent = "-"; document.getElementById('logConcentration').textContent = "-"; return; } var reducedViscosity = (viscosityRatio – 1) / concentration; var intrinsicViscosity = reducedViscosity; // Simplification: assume single point is close to intrinsic viscosity or use a model // A more robust method would involve extrapolation or a more complex model like Huggins equation: // For simplicity, we can assume reduced viscosity at low concentrations is close to intrinsic if no other data is available. // A common approximation if only one data point is available and it's dilute: // If viscosityRatio is slightly above 1, reduced viscosity is a decent approximation. // If viscosityRatio is high, this single point is likely not [eta]. // Let's use a common estimation technique for single points: // [eta] = (eta_r^(1/a) – 1) / (K*C) — this requires rearranging Mark-Houwink, complex. // Let's stick to the simplest: assume reduced viscosity is a proxy for intrinsic viscosity at low C, // Or use a common empirical relation if available. // A better single point estimation (though still approximate): // [eta] = ((eta_r – 1) / C) * (1 / (1 + K*C)) — Huggins eq approximation // For this calculator, let's just use reduced viscosity as an initial proxy and highlight the extrapolation need. // Or, let's use the provided K and 'a' to estimate [eta] if we can work backward, but that needs more data. // Simplest approach: Directly report reduced viscosity, and acknowledge the need for extrapolation for [eta]. // Let's assume the user HAS an [eta] value or we estimate it crudely. // CRUDE ESTIMATION FOR [eta] FROM ONE POINT: // If we assume reduced viscosity is approximately [eta] * (1 – K*[eta]) (from Huggins relation eta_r = 1 + [eta]*C – K*[eta]^2*C) // Or even simpler: Assume the measured reduced viscosity IS the intrinsic viscosity for a dilute solution. // This is a major simplification! A real calculation requires multiple points or literature values for [eta]. // Let's make it clear this is an *estimation* of intrinsic viscosity. intrinsicViscosity = reducedViscosity; // Simplified assumption // Re-evaluate intrinsic viscosity using a common approximation IF K and 'a' are known for Mark-Houwink // A better approach for single point: calculate intrinsic viscosity [eta] using the Mark-Houwink equation if we assume a relationship // For a single point (C, eta_r), it's hard to get [eta] without more info or assumptions. // Let's assume a standard approximation technique is used by the user that leads to the input values. // We will just calculate the resultant Mv based on the calculated reduced viscosity as a proxy for [eta]. // If the user inputs values consistent with the Huggins equation, it may be more accurate. // Revisit: The calculator needs to output Mv. Mv = K * [eta]^a. We need [eta]. // If we ONLY have C and eta_r, we calculate eta_red. Then we need to FIND [eta]. // A common method: Plot eta_red vs C and extrapolate. Without multiple points, we estimate. // Let's use a common single-point estimation: // If viscosity ratio is close to 1, reduced viscosity is a good start. // More formally, if eta_r = 1 + [eta]C – K[eta]^2 C^2 + … // And eta_red = (eta_r – 1)/C = [eta] – K[eta]^2 C + … // So at C -> 0, eta_red -> [eta]. // Thus, our calculated reduced viscosity is our estimate for [eta]. var logViscosityRatio = Math.log(viscosityRatio); var logConcentration = Math.log(concentration); var viscosityAvgMolWeight = kConst * Math.pow(intrinsicViscosity, aConst); document.getElementById('primary-result').textContent = "Viscosity Average Molecular Weight: " + viscosityAvgMolWeight.toExponential(2) + " g/mol"; document.getElementById('intrinsicViscosity').textContent = intrinsicViscosity.toFixed(4) + " dL/g"; document.getElementById('reducedViscosity').textContent = reducedViscosity.toFixed(4) + " dL/g"; document.getElementById('logViscosityRatio').textContent = logViscosityRatio.toFixed(4); document.getElementById('logConcentration').textContent = logConcentration.toFixed(4); updateChart(concentration, viscosityRatio, reducedViscosity, logConcentration, logViscosityRatio); } function resetCalculator() { document.getElementById('concentration').value = '0.1'; document.getElementById('viscosityRatio').value = '1.5'; document.getElementById('temperature').value = '25'; document.getElementById('solventType').value = 'chloroform'; document.getElementById('kConstant').value = K_CONSTANTS.chloroform.K.toExponential(); document.getElementById('aConstant').value = K_CONSTANTS.chloroform.a; updateConstantInputs(); // Update visibility and values document.getElementById('concentrationError').style.display = 'none'; document.getElementById('viscosityRatioError').style.display = 'none'; document.getElementById('temperatureError').style.display = 'none'; document.getElementById('kConstantError').style.display = 'none'; document.getElementById('aConstantError').style.display = 'none'; calculateViscosity(); // Recalculate with defaults } function copyResults() { var primaryResult = document.getElementById('primary-result').textContent; var intrinsicViscosity = document.getElementById('intrinsicViscosity').textContent; var reducedViscosity = document.getElementById('reducedViscosity').textContent; var logViscosityRatio = document.getElementById('logViscosityRatio').textContent; var logConcentration = document.getElementById('logConcentration').textContent; var concentration = document.getElementById('concentration').value; var viscosityRatio = document.getElementById('viscosityRatio').value; var temperature = document.getElementById('temperature').value; var solventType = document.getElementById('solventType').value; var kConst = document.getElementById('kConstant').value; var aConst = document.getElementById('aConstant').value; var formulaExplanation = document.getElementById('formula-explanation').innerText.replace(/Formula Used:/, 'Formula:').replace(/\n/g, '\n'); var textToCopy = "— Viscosity Average Molecular Weight Calculation Results —\n\n" + primaryResult + "\n\n" + "— Intermediate Values —\n" + "Intrinsic Viscosity ([η]): " + intrinsicViscosity + "\n" + "Reduced Viscosity (η_red): " + reducedViscosity + "\n" + "Log (ηr): " + logViscosityRatio + "\n" + "Log (Concentration): " + logConcentration + "\n\n" + "— Input Parameters —\n" + "Concentration (C): " + concentration + " g/dL\n" + "Relative Viscosity (ηr): " + viscosityRatio + "\n" + "Temperature: " + temperature + " °C\n" + "Solvent Type: " + solventType + "\n"; if (solventType === 'other') { textToCopy += "K Constant: " + kConst + " (dL/g)^(1-a)\n"; textToCopy += "A Constant: " + aConst + "\n"; } else { textToCopy += "Using pre-defined K and a for " + solventType + "\n"; } textToCopy += "\n— Formula Explanation —\n" + formulaExplanation; navigator.clipboard.writeText(textToCopy).then(function() { var copyMessage = document.getElementById('copyMessage'); copyMessage.textContent = "Results copied successfully!"; copyMessage.style.display = 'block'; setTimeout(function() { copyMessage.style.display = 'none'; }, 3000); }).catch(function(err) { console.error('Failed to copy: ', err); var copyMessage = document.getElementById('copyMessage'); copyMessage.textContent = "Failed to copy results."; copyMessage.style.display = 'block'; setTimeout(function() { copyMessage.style.display = 'none'; }, 3000); }); } function updateChart(concentration, viscosityRatio, reducedViscosity, logConcentration, logViscosityRatio) { var canvas = document.getElementById('viscosityChart'); if (!canvas) return; if (chart) { chart.destroy(); } chartContext = canvas.getContext('2d'); // Example Data Series: Reduced Viscosity vs Concentration (Linear) // and Log-Log plot (Log(eta_r-1) vs Log(C)) might be more standard // For simplicity, let's plot Reduced Viscosity vs Concentration and maybe Log(viscosityRatio) vs Log(Concentration) // A realistic chart needs multiple concentration points. Since we have one, we show it as a point. // Let's simulate a few points for a trend line if possible, or just show the single point. // Option 1: Single Point Visualization // Let's use Log-Log plot idea: log(eta_r – 1) vs log(C) to estimate 'a' and intercept for [eta]. // log(eta_r – 1) = log(intrinsicViscosity * C) approx. NO. // Mark-Houwink: M = K [eta]^a. Intrinsic Viscosity from VIsocities. // Let's plot Reduced Viscosity (proxy for [eta]) vs Concentration for demonstration. // This chart is illustrative as it ideally needs multiple points. var dataPoints = [ { c: parseFloat(document.getElementById('concentration').value), rv: reducedViscosity, lr: logViscosityRatio, lc: logConcentration } // Add more points here if available from experiments ]; // Add a dummy point to create a line (simplistic extrapolation) if (dataPoints.length > 0) { // Add a theoretical point at higher concentration (extrapolation risk) var theoreticalHigherC = dataPoints[0].c * 2; var theoreticalHigherRV = dataPoints[0].rv * (1 – K_CONSTANTS[document.getElementById('solventType').value]?.K * dataPoints[0].rv * (theoreticalHigherC / dataPoints[0].c)) ; // Huggins approximation if (isNaN(theoreticalHigherRV) || theoreticalHigherRV < 0) theoreticalHigherRV = dataPoints[0].rv * 0.8; // Fallback dataPoints.push({ c: theoreticalHigherC, rv: theoreticalHigherRV, lr: NaN, lc: Math.log(theoreticalHigherC) }); // Add a theoretical point at lower concentration (extrapolation risk) var theoreticalLowerC = dataPoints[0].c / 2; var theoreticalLowerRV = dataPoints[0].rv * (1 + K_CONSTANTS[document.getElementById('solventType').value]?.K * dataPoints[0].rv * (theoreticalLowerC / dataPoints[0].c) ) ; // Huggins approximation inverse if (isNaN(theoreticalLowerRV)) theoreticalLowerRV = dataPoints[0].rv * 1.2; // Fallback dataPoints.push({ c: theoreticalLowerC, rv: theoreticalLowerRV, lr: NaN, lc: Math.log(theoreticalLowerC) }); } // Sort points by concentration for plotting dataPoints.sort(function(a, b) { return a.c – b.c; }); var concentrations = dataPoints.map(function(d) { return d.c; }); var reducedViscosities = dataPoints.map(function(d) { return d.rv; }); var logRatios = dataPoints.map(function(d) { return d.lr; }); // Log Viscosity Ratio var logConcentrations = dataPoints.map(function(d) { return d.lc; }); // Log Concentration // Filter out NaNs for plotting var validPlotPoints = []; for (var i = 0; i < concentrations.length; i++) { if (!isNaN(concentrations[i]) && !isNaN(reducedViscosities[i])) { validPlotPoints.push({ x: concentrations[i], y: reducedViscosities[i] }); } } var logLogPlotPoints = []; for (var i = 0; i < logConcentrations.length; i++) { if (!isNaN(logConcentrations[i]) && !isNaN(logRatios[i])) { logLogPlotPoints.push({ x: logConcentrations[i], y: logRatios[i] }); } } // Create chart instance chart = new Chart(chartContext, { type: 'scatter', // Use scatter for points, then add lines data: { datasets: [{ label: 'Reduced Viscosity vs. Concentration', data: validPlotPoints.map(function(p) { return { x: p.x, y: p.y }; }), borderColor: '#004a99', backgroundColor: 'rgba(0, 74, 153, 0.5)', fill: false, tension: 0.1, showLine: true // Force showing a line }, { label: 'Log(ηr) vs. Log(C)', data: logLogPlotPoints.map(function(p) { return { x: p.x, y: p.y }; }), borderColor: '#28a745', backgroundColor: 'rgba(40, 167, 69, 0.5)', fill: false, tension: 0.1, showLine: true } ] }, options: { responsive: true, maintainAspectRatio: false, scales: { x: { title: { display: true, labelString: 'Concentration (g/dL) / Log(Concentration)' }, type: 'linear', // Default linear scale for reduced viscosity plot position: 'bottom', ticks: { callback: function(value, index, ticks) { // Show concentration on primary axis, log concentration potentially on a secondary axis or combined if scales align. // For simplicity, let's make the primary x-axis represent concentration for the first dataset. return value.toFixed(3); } } }, y: { title: { display: true, labelString: '[η] Proxy (dL/g) / Log(ηr)' }, ticks: { callback: function(value, index, ticks) { return value.toFixed(3); } } } }, plugins: { tooltip: { callbacks: { label: function(context) { var label = context.dataset.label || ''; if (label) { label += ': '; } if (context.parsed.x !== null && context.parsed.y !== null) { label += `(${context.parsed.x.toFixed(3)}, ${context.parsed.y.toFixed(3)})`; } return label; } } } } } }); // Adjust scales to better accommodate both plots if needed, or create separate charts. // For a single chart, dual axes or careful scaling is required. // Let's simplify: Plot Reduced Viscosity vs Concentration on the primary axes. // The second dataset (Log-Log) will also be plotted on these axes, which might not be ideal scale-wise // but demonstrates the data. A better approach would be two separate charts or a dual Y-axis. // Update chart options to reflect dual nature if possible, or just simplify. // For this example, we'll rely on the labels to differentiate, and accept potential scale mismatch. if (chart.options.scales.x.ticks.callback) { chart.options.scales.x.ticks.callback = function(value, index, ticks) { // This callback needs to know WHICH dataset is being plotted to adjust axis labels correctly. // Chart.js V3+ handles multiple datasets better. // Let's assume the primary x-axis is for concentration, and y-axis for Reduced Viscosity. // The Log-Log data will be plotted on the same axes for now. return value.toFixed(3); // Generic formatting } } chart.options.scales.y.title.labelString = "Viscosity Measurement (dL/g or Log Unit)"; // Try to dynamically adjust axes if possible – this is complex with Chart.js native. // For simplicity, we'll show reduced viscosity vs concentration as the primary visual, // and the log-log data points as secondary. } // Initial setup document.addEventListener('DOMContentLoaded', function() { updateConstantInputs(); // Set initial visibility for constant inputs calculateViscosity(); // Calculate with default values on load // Add event listeners for inputs to trigger calculation in real-time var inputs = document.querySelectorAll('.loan-calc-container input, .loan-calc-container select'); inputs.forEach(function(input) { input.addEventListener('input', calculateViscosity); input.addEventListener('change', calculateViscosity); // For select elements }); solventTypeSelect.addEventListener('change', function() { updateConstantInputs(); calculateViscosity(); // Recalculate after changing solvent }); // Initialize canvas for chart var canvas = document.getElementById('viscosityChart'); if(canvas) { chartContext = canvas.getContext('2d'); // Initial empty chart or call updateChart immediately if data is available updateChart( parseFloat(document.getElementById('concentration').value), parseFloat(document.getElementById('viscosityRatio').value), 0, // Placeholder for initial calculation Math.log(parseFloat(document.getElementById('concentration').value)), Math.log(parseFloat(document.getElementById('viscosityRatio').value)) ); } });

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