Answer:
0.00735°C
Explanation:
By seeing the question, we can see the elevation in boiling point with addition of BaCl₂ in water
⠀
⠀
⠀
<u>The</u><u> </u><u>elevation</u><u> </u><u>in</u><u> </u><u>boiling</u><u> </u><u>point</u><u> </u><u>is</u><u> </u><u>a</u><u> </u><u>phenomenon</u><u> </u><u>in</u><u> </u><u>which</u><u> </u><u>there</u><u> </u><u>is</u><u> </u><u>increase</u><u> </u><u>in</u><u> </u><u>boiling</u><u> </u><u>point</u><u> </u><u>in</u><u> </u><u>solution</u><u>,</u><u> </u><u>when</u><u> </u><u>the</u><u> </u><u>particular</u><u> </u><u>type</u><u> </u><u>of</u><u> </u><u>solute</u><u> </u><u>is</u><u> </u><u>added</u><u> </u><u>to</u><u> </u><u>pure</u><u> </u><u>solvent</u><u>.</u>
⠀
⠀
⠀
⠀
Where 'i' is van't hoff factor which represents the ratio of observed osmotic pressure and the value to be expected.
and 'i' is 3 (as given in the question)
⠀
'Kb' is molal boiling point constant. And it's value is 0.51°C/mol(given in question)
⠀
'm' represent the molality of solution. Molatity is no. of moles of solution present in 1kg of solution.
⠀
⠀
<u>To</u><u> </u><u>find</u><u> </u><u>molality</u><u>,</u><u> </u><u>we</u><u> </u><u>have</u><u> </u><u>to</u><u> </u><u>divide</u><u> </u><u>no</u><u>.</u><u> </u><u>of</u><u> </u><u>moles</u><u> </u><u>of</u><u> </u><u>solute</u><u> </u><u>by</u><u> </u><u>weight</u><u> </u><u>of</u><u> </u><u>solution</u>
⠀
While first we need to no. of moles
⠀
⠀
<u>Now</u><u>,</u><u> </u><u>we</u><u> </u><u>will</u><u> </u><u>find</u><u> </u><u>molality</u>
⠀
⠀
⠀
⠀
⠀
⠀
⠀
<u>Henceforth</u><u>,</u><u> </u><u>the</u><u> </u><u>change</u><u> </u><u>in</u><u> </u><u>boiling</u><u> </u><u>point</u><u> </u><u>is</u><u> </u><u>0</u><u>.</u><u>0</u><u>0</u><u>7</u><u>3</u><u>5</u><u>°</u><u>C</u><u>.</u>
Answer:
because it could self drive
Explanation:
idrk but thats my answer
Answer:
its yellow
Explanation:
it's a constant law .... much explanation
from 0 to 9
we have
black .o
brown 1
red 2
orange 3
yellow 4
green 5
blue 6
violet 7
grey 8
white 9
Answer: This historical data could have helped with the development of Tokyo’s new flood protection system:
historical frequency of flooding
amount of flooding during each storm
computer models forecasting the worst possible flooding
Explanation:
The frequency of flooding can help Tokyo measure when the next flood will be.
The amount of flooding can help Tokyo determine how much water will come during the flood.
And computer models forecasting the worst possible flood can help reach out to people and tell whether they need to evacuate or what they should plan for.