Part A How much voltage must be used to accelerate a proton (radius 1.2 ×10−15m) so that it has sufficient energy to just penetrate a silicon nucleus? A silicon nucleus has a charge of +14e, and its radius is about 3.6 ×10−15m. Assume the potential is that for point charges.

Answers

Answer 1
Answer:

Answer:

Step-by-step explanation:

Qp = charge on proton = 1.6 x 10-19 C

Qs = charge on silicon = 14 x 1.6 x 10-19 C

rf = final distance from nucleus = ∞

ri = initial distance from nucleus = (3.6 x 10-15 + 1.2 x 10-15 ) = 4.8 x 10-15 m

initial Potential energy is given as

Ui = k Qp Qs / ri = (9 x 109) (1.6 x 10-19 ) (14 x 1.6 x 10-19 ) / (4.8 x 10-15 ) = 6.72 x 10-13 J

final Potential energy is given as

Uf = k Qp Qs / rf = (9 x 109) (1.6 x 10-19 ) (14 x 1.6 x 10-19 ) / (∞) = 0 J

Change in Potential energy = ΔU = Ui - Uf = 6.72 x 10-13 - 0 = 6.72 x 10-13 J

Let the Voltage through which proton is accelerated = V

Energy gained due to potential difference = Qp V

Using conservation of energy

Qp V = 6.72 x 10-13

(1.6 x 10-19 ) V = 6.72 x 10-13

V = 4.2 x 106 volts


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The distance a vehicle travels can be found by using the formula d = rt, where d is the total distance traveled, r is the rate of speed, and t is the amount of time spent traveling. Grace drives her truck a distance of 80 miles at a steady speed of 50 miles per hour. To the nearest hour, how many hours does she spend driving?

I need help with this ^

Answers

Answer:

31

Step-by-step explanation:

5z-25=180

5z=180-25

5z=155

z=31

Answer: Im pretty sure its 155

Step-by-step explanation:

What is the greatest common factor shared by 70 and 15?
Answer here
SUBMIT

Answers

The answer is 5
Step by step explaination

Answer:

The greatest common factor of 70 and 15 is 5.

Step-by-step explanation:

First, list the prime factors for each individual number

Next, circle each common prime factor. This means that you must find the prime factors that are the same as each other. For example, if it's 1 3 4 and 2 3 5, the common prime factor would be 3.

Finally, you must multiply all of the common prime factors. Your answer will be the greatest common factor!

So, the greatest common factor of 70 and 15 is 5.

A new drug to treat psoriasis has been developed and is in clinical testing. Assume that those individuals given the drug are examined before receiving the treatment and then again after receiving the treatment to determine if there was a change in their symptom status. If the initial results showed that 2.0% of individuals entered the study in remission, 77.0% of individuals entered the study with mild symptoms, 16.0% of individuals entered the study with moderate symptoms, and 5.0% entered the study with severe symptoms calculate and interpret a chi-squared test to determine if the drug was effective treating psoriasis given the information below from the final examination.

Answers

Answer:

Step-by-step explanation:

Solution:-

State the hypotheses. The first step is to state the null hypothesis and an alternative hypothesis.

Null hypothesis: The distribution of severity of psoriasis cases at the end and prior are same.

Alternative hypothesis: The distribution of severity of psoriasis cases at the end and prior are different.

Formulate an analysis plan. For this analysis, the significance level is 0.05. Using sample data, we will conduct a chi-square goodness of fit test of the null hypothesis.

Analyze sample data. Applying the chi-square goodness of fit test to sample data, we compute the degrees of freedom, the expected frequency counts, and the chi-square test statistic. Based on the chi-square statistic and the degrees of freedom, we determine the P-value.

DF = k - 1 = 4 - 1

D.F = 3

(Ei) = n * pi

Category            observed Num      expected num      [(Or,c -Er,c)²/Er,c]

Remission             380                         20                           6480

Mild

symptoms               520                         770                       81.16883117

Moderate

symptoms                 95                         160                         24.40625

Severe

symptom                  5                             50                          40.5

Sum                          1000                       1000                       6628.075081

Χ2 = Σ [ (Oi - Ei)2 / Ei ]

Χ2 = 6628.08

Χ2Critical = 7.81

where DF is the degrees of freedom, k is the number of levels of the categorical variable, n is the number of observations in the sample, Ei is the expected frequency count for level i, Oi is the observed frequency count for level i, and Χ2 is the chi-square test statistic.

The P-value is the probability that a chi-square statistic having 3 degrees of freedom is more extreme than 6628.08.

We use the Chi-Square Distribution Calculator to find P(Χ2 > 19.58) =less than 0.000001

Interpret results. Since the P-value (almost 0) is less than the significance level (0.05), we cannot accept the null hypothesis.

We reject H0, because 6628.08 is greater than 7.81. We have statistically significant evidence at alpha equals to 0.05 level to show that distribution of severity of psoriasis cases at the end of the clinical trial for the sample is different from the distribution of the severity of psoriasis cases prior to the administration of the drug suggesting the drug is effective.

Final answer:

The chi-square test is a statistical method that determines if there's a significant difference between observed and expected frequencies in different categories, such as symptom status in this clinical trial. Without post-treatment numbers, we can't run the exact test. However, if the test statistic exceeded the critical value, we could conclude that the drug significantly affected symptom statuses.

Explanation:

This question pertains to the use of a chi-squared test, which is a statistical method used to determine if there's a significant difference between observed frequencies and expected frequencies in one or more categories. For this case, the categories are the symptom statuses (remission, mild, moderate, and severe).

To conduct a chi-square test, you first need to know the observed frequencies (the initial percentages given in the question) and the expected frequencies (the percentages after treatment). As the question doesn't provide the numbers after treatment, I can't perform the exact chi-square test.

If the post-treatment numbers were provided, you would compare them to the pre-treatment numbers using the chi-squared formula, which involves summing the squared difference between observed and expected frequencies, divided by expected frequency, for all categories. The result is a chi-square test statistic, which you would then compare to a critical value associated with a chosen significance level (commonly 0.05) to determine if the treatment has a statistically significant effect.

To interpret a chi-square test statistic, if the calculated test statistic is larger than the critical value, it suggests that the drug made a significant difference in the distribution of symptom statuses. If not, we can't conclude the drug was effective.

Learn more about Chi-square test here:

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It is important that face masks used by firefighters be able to withstand high temperatures because firefighters commonly work in temperatures of 200-500 degrees. In a test of one type of mask, 24 of 55 were found to have their lenses pop out at 325 degrees. Construct and interpret a 93% confidence interval for the true proportion of masks of this type whose lenses would pop out at 325 degrees.

Answers

Answer:

The 93% confidence interval for the true proportion of masks of this type whose lenses would pop out at 325 degrees is (0.3154, 0.5574). This means that we are 93% sure that the true proportion of masks of this type whose lenses would pop out at 325 degrees is (0.3154, 0.5574).

Step-by-step explanation:

In a sample with a number n of people surveyed with a probability of a success of \pi, and a confidence level of 1-\alpha, we have the following confidence interval of proportions.

\pi \pm z\sqrt{(\pi(1-\pi))/(n)}

In which

z is the zscore that has a pvalue of 1 - (\alpha)/(2).

For this problem, we have that:

n = 55, \pi = (24)/(55) = 0.4364

93% confidence level

So \alpha = 0.07, z is the value of Z that has a pvalue of 1 - (0.07)/(2) = 0.965, so Z = 1.81.

The lower limit of this interval is:

\pi - z\sqrt{(\pi(1-\pi))/(n)} = 0.4364 - 1.81\sqrt{(0.4364*0.5636)/(55)} = 0.3154

The upper limit of this interval is:

\pi + z\sqrt{(\pi(1-\pi))/(n)} = 0.4364 + 1.81\sqrt{(0.4364*0.5636)/(55)} = 0.5574

The 93% confidence interval for the true proportion of masks of this type whose lenses would pop out at 325 degrees is (0.3154, 0.5574). This means that we are 93% sure that the true proportion of masks of this type whose lenses would pop out at 325 degrees is (0.3154, 0.5574).

A manufacturer uses 34 yard of fabric in each skirt.How many yards of fabric will the manufacturer use in 4 skirts? in 7 skirts? in 9 skirts?

Answers

Answer:

She would use 136 yards in 4 skirts, 238 yards in 7 skirts, and 306 yards in 9 skirts. Hope this helps

Step-by-step explanation:

19) Solve the system,
*****
x + 3y - 5
-2x + 2y = 14

Answers

Answer:

y = 3

x = -4

Step-by-step explanation:

Hopefully the first equation is x + 3y = 5

x = 5 - 3y

Plug in:

-2(5 - 3y) + 2y = 14

-10 + 6y + 2y = 14

8y = 24

y = 3

x = -4