You can see the fit coefficients in the Estimate column of the summary. You can also get them with the code
FIT$coefficients
after running the lm() function.
Here is my code:
Temp <- c(10,20,30,40,60,80,100,120,140,160,180,200,220,240,260,280,300)
Cp <- c(0.3,2.4,7.0,3.0,25.1,35.2,43.2,50.0,56.0,61.6,67.0,72.2,77.4,82.8,88.4,94.0,99.7)
plot(Temp, Cp)

FIT <- lm(Cp ~ I(Temp^2) + Temp)
summary(FIT)
#>
#> Call:
#> lm(formula = Cp ~ I(Temp^2) + Temp)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -9.7764 -1.3967 -0.3365 2.5989 4.0562
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) -7.5715948 2.2721831 -3.332 0.00493 **
#> I(Temp^2) -0.0006190 0.0001195 -5.180 0.00014 ***
#> Temp 0.5334586 0.0369039 14.455 8.29e-10 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 3.535 on 14 degrees of freedom
#> Multiple R-squared: 0.9905, Adjusted R-squared: 0.9891
#> F-statistic: 726.1 on 2 and 14 DF, p-value: 7.234e-15
Created on 2019-12-11 by the reprex package (v0.2.1)