<span>First we need to find the energy of one photon with a wavelength of 589 nm.
E = hc / wavelength
E = (6.63 x 10^{-34} J s)(3 x 10^8 m/s) / (589 x 10^{-9} m)
E = 3.3769 x 10^{-19} Joules
To find N, the number of photons, we need to divide the total energy by the energy of each photon.
N = 623000 J / 3.3769 x 10^{-19} Joules
N = 1.84 x 10^{24} photons
There are 1.84 x 10^{24} photons in the burst of yellow light.</span>
increase the rate of chemical change.
Explanation:
The reaction of the metal oxide with water to form a base in the presence of a spike in temperature will lead to an increase in the rate of chemical change.
Temperature change has considerable effect on reaction rates.
- Temperature is directly proportional to the average kinetic energy of reacting particles.
- Reaction rates varies directly with a spike in temperature.
- It has been known that for every 10°C rise in temperature, above the room temperature, reaction rates become double or tripled.
- Temperature increases the kinetic energy of each of the reacting particles.
- Many of the reacting particles also acquires an energy greater than or equal to the activation energy of the reaction.
- The frequency of ordinary collisions and effective collisions per unit time increases.
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Answer:
T₂ = 218.75 K
Explanation:
Given data:
Initial volume = 20 L
Initial pressure = 16 atm
Initial temperature = 500 K
Final temperature = ?
Final volume = 35 L
Final pressure = 4 atm
Formula:
P₁V₁/T₁ = P₂V₂/T₂
P₁ = Initial pressure
V₁ = Initial volume
T₁ = Initial temperature
P₂ = Final pressure
V₂ = Final volume
T₂ = Final temperature
by putting values,
P₁V₁/T₁ = P₂V₂/T₂
T₂ = P₂V₂ T₁/ P₁V₁
T₂ = 4 atm × 35 L × 500 K / 16 atm × 20 L
T₂ = 70000 atm .L. K / 320 atm.L
T₂ = 218.75 K
Answer:
thjvfghjjvvjj
Explanation:
Assume that the set of conditionals is true. Use the Law of Syllogism to
write a true conditional.
8. If two numbers are odd, the
answer is that a
even, then the number is divisible by 2.
Enter your answer.
CHECK ANSWER
Answer:
null
Explanation:
the hypothesis is a typical statistical theory which suggest that no statistical relationship and significance exists in a set of a given single observed variable between two sets of the observed data and measured phenomena
