Freezing point depression calculator
Predict how far a solution's freezing point falls, in kelvin: 0.5 mol/kg of a non-electrolyte in water, with a Kf of 1.86, gives a drop of 0.93 K, and a strong 1:1 electrolyte at the same molality doubles it to 1.86 K. Free in your browser.
- Free
- Runs in your browser
- No sign-up
- Your data stays on your device
Run — free
Worked example
- Molality
- 0.5
- Cryoscopic
- 1.86
- Current (A)
- 1
- Delta tf
- 0.93 K
- Precision
- 10
This freezing point depression calculator returns the colligative drop ΔTf of the freezing temperature from solution molality m, the solvent cryoscopic constant Kf, and the van 't Hoff factor i using the closed form ΔTf equals i times Kf times m. Freezing-point depression is the colligative lowering of the freezing temperature of a solution relative to the pure solvent when a non-volatile solute reduces solvent chemical potential in the liquid phase. The linear ideal-dilute identity multiplies the particle factor, the solvent constant, and the molal concentration so students and lab workflows can predict how far the freezing point falls without reopening a full thermodynamics package. Typical textbook checks include water-like data with m equals 0.5 mol/kg, Kf equals 1.86 K·kg/mol, and i equals 1 yielding ΔTf equals 0.93 K, and the same molality and Kf with i equals 2 for a strong 1:1 electrolyte yielding ΔTf equals 1.86 K. The engine uses only finite arithmetic with no network calls, no sampling, and no date-dependent shortcuts.
What the freezing-point drop tells you
Freezing-point depression ΔTf is the positive temperature drop of the freezing point of a solution relative to the pure solvent for an ideal dilute solution of a non-volatile solute. The standard linear relation is ΔTf equals i times Kf times m, where m is molality in moles of solute per kilogram of solvent, Kf is the solvent cryoscopic constant in K·kg/mol (numerically equal to °C·kg/mol for a temperature difference), and i is the van 't Hoff factor that counts the effective particles produced per formula unit.
Ideal non-electrolytes use i equals one; strong electrolytes approach the stoichiometric ion count in the dilute limit, while weak electrolytes use an effective i between one and that count. Zero molality or zero particle factor is allowed and simply yields a zero depression.
Where freezing-point depression fits in study, lab, and software
Students meet freezing-point depression when a textbook introduces colligative properties after molality, when a lab report asks for the expected temperature drop of an antifreeze or salt solution, or when a contest problem gives m, Kf, and i and asks for ΔTf instead of the solvent constant. Teachers can pre-generate answer keys for modest molalities and integer van 't Hoff factors without trusting opaque calculator apps that silently switch units or drop the particle factor.
Developers call the same contract from scripts to seed deterministic test vectors for chemistry education products, to normalize user-entered colligative inputs before plotting freezing curves, or to satisfy programming-challenge statements that demand ΔTf rather than a hand-waved estimate. Process and quality workflows sometimes need a fast offline source of freezing-point drops so dilute-solution checks can be validated without reopening a full thermodynamics package.
Product and tutoring tools use the product when a learner types molality, Kf, and i and the UI must show a clean kelvin depression with a formula echo.
What you can do with it
Homework and lab ΔTf checks
Predict freezing-point depression from molality, solvent Kf, and van 't Hoff factor before writing lab reports or checking textbook answers.
Tutoring and chemistry software
Normalize user-entered m, Kf, and i into a stable freezing-point depression for interactive lessons and solution calculators.
FAQ
What does the freezing point depression calculator cost?
It is free in your browser on this page.
What formula does this tool use?
ΔTf = i · Kf · m, where m is molality (mol/kg), Kf is the cryoscopic constant (K·kg/mol), and i is the van 't Hoff factor.
What happens if molality, Kf, or i is negative?
Freezing-point depression from molality requires non-negative molality, cryoscopic constant, and van 't Hoff factor.
Is the result in K or °C?
The depression is returned in K. For a temperature-difference basis the numeric value matches °C, so 0.93 K is the same figure as 0.93 °C of depression.
Does this tool look up Kf for common solvents?
No. You supply molality, Kf, and i. The calculator only multiplies the colligative identity and returns ΔTf.
Related tools
For developers — API access
Everything on this page is available programmatically. This section is for teams who want to wire it into their own systems; everyone else can just use the tool above.
API endpoint
Prefer to automate it? One authenticated POST creates the task; the result comes back by webhook or a signed link. The same capability also runs here on the web, by email and from Telegram — and soon from our app too.
Call it from your stack
curl -X POST https://api.kit.forhosting.com/chem/freezing-point-depression-molality \
-H "Authorization: Bearer $KIT_KEY" \
-H "Content-Type: application/json" \
-d '{"molality":0.5,"kf":1.86,"i":1}'const res = await fetch("https://api.kit.forhosting.com/chem/freezing-point-depression-molality", {
method: "POST",
headers: {
"Authorization": `Bearer ${process.env.KIT_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
"molality": 0.5,
"kf": 1.86,
"i": 1
})
});
const { task_id } = await res.json();import os, requests
res = requests.post(
"https://api.kit.forhosting.com/chem/freezing-point-depression-molality",
headers={"Authorization": f"Bearer {os.environ['KIT_KEY']}"},
json={
"molality": 0.5,
"kf": 1.86,
"i": 1
},
)
task_id = res.json()["task_id"]<?php
$res = file_get_contents("https://api.kit.forhosting.com/chem/freezing-point-depression-molality", false, stream_context_create([
"http" => [
"method" => "POST",
"header" => "Authorization: Bearer " . getenv("KIT_KEY") . "\r\nContent-Type: application/json",
"content" => '{"molality":0.5,"kf":1.86,"i":1}',
],
]));
$task = json_decode($res, true);body := bytes.NewBufferString(`{"molality":0.5,"kf":1.86,"i":1}`)
req, _ := http.NewRequest("POST", "https://api.kit.forhosting.com/chem/freezing-point-depression-molality", body)
req.Header.Set("Authorization", "Bearer "+os.Getenv("KIT_KEY"))
req.Header.Set("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)Example request
{
"molality": 0.5,
"kf": 1.86,
"i": 1
}Example response
{
"task_id": "tsk_a1b2c3d4e5f6a1b2c3d4e5f6",
"type": "chem.freezing_point_depression_molality",
"status": "queued",
"_links": {
"result": "/tasks/tsk_…/result"
}
}The API is asynchronous: the call returns a task_id immediately and the result arrives by webhook. Polling is capped at 1 req/s per task.
Pricing
Published price — no tokens, no invented credits. A failed task is never charged.
Limits
max_abs_value | 1000000000000000 |
Errors
| HTTP | Code | Meaning |
|---|---|---|
401 | unauthorized | Missing or invalid API key. |
402 | insufficient_balance | Your balance doesn't cover the task price. |
404 | unknown_type | That task type doesn't exist. |
429 | rate_limited | Too many requests. Use the webhook instead of polling. |
Technical notes
What freezing-point depression means and what the response contains
This calculator returns the normalized molality, kf, and i values, the freezing-point depression delta_tf rounded to the requested precision, the precision used, the method tag freezing_point_depression_molality, a short formula reminder, and the unit string K. There is no approximate CAS path and no random sampling: the engine either multiplies three finite non-negative scalars inside the supported magnitude range or rejects the input with invalid_input. Rejected cases include missing molality, kf, or i, non-finite values, magnitudes above the documented ceiling, and any negative molality, cryoscopic constant, or van 't Hoff factor, because those signs are non-physical for this colligative product.
How molality, the cryoscopic constant, and the van 't Hoff factor are read
Optional leading plus signs and scientific notation on numeric strings are allowed when they parse as finite decimals; embedded spaces, hex prefixes, and non-numeric tokens are rejected with a clear message so a bad cell does not become a wrong temperature drop. The cryoscopic constant and van 't Hoff factor are likewise rejected when negative so the engine never returns a non-physical negative depression from inverted solvent or particle data. The preferred fields are molality for m, kf for the cryoscopic constant, and i for the van 't Hoff factor, but aliases m, b, and molal for molality, Kf, cryoscopic_constant, and cryoscopic for the constant, and van_t_hoff, vant_hoff, van_hoff, and factor for i are accepted so spreadsheets, query strings, and typed forms can reuse the same contract. Molality must not be negative: a negative molal concentration is rejected with invalid_input because the colligative product assumes non-negative m. An optional precision field, with aliases decimals and dp, chooses how many decimal places to expose for molality, kf, i, and delta_tf, defaulting to ten and capped at fifteen so JSON goldens stay stable. Pair the free browser run on this page with the priced API when you need the identical mathematical result inside an automated pipeline without re-implementing ΔTf equals i Kf m yourself.
Where freezing-point depression fits in study, lab, and software
On this page the work runs entirely in your browser; through the API each successful lookup costs $0.002, failed validation is not charged, and nothing is stored after the response returns. That split — free interactive exploration and a priced, identical API — matches the rest of the KIT tier-A catalog and lets you move from a classroom demo to an automated pipeline without changing the mathematical result. Pair it with the cryoscopic-constant recovery tool when you need the inverse rearrangement, with boiling-point elevation tools for the elevation analog, and with other chem endpoints when you are building a small lab of free, deterministic colligative helpers.
Integration use cases
Deterministic test fixtures
Generate reproducible delta_tf values for unit tests, property checks, and CI assertions on colligative products.