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Sandbox Physics

E45 · In-situ electron microscopy

In-situ TEM: Stimulus or Beam?

In an in-situ TEM experiment, is the beam observing the response or helping drive it? It can be doing both. Electrons can change a thermal reaction, push a charged object or soften a loaded specimen. More counts make the motion easier to measure, but do not establish its cause. Compare controlled runs at different doses; fitting and drift correction cannot remove a response the beam itself created.

Apply electrical bias, mechanical load or heat. Track markers or conversion in recorded count images, then test whether the inferred material response is changed by the imaging beam.

Interactive modelIn-situ TEM: Stimulus or Beam?
Count-derived response—\text{—}
Parameter error against known input—\text{—}
Beam perturbation audit—\text{—}
Mean counts per sampled pixel—\text{—}
More measurements and target
Inferred coefficient, modulus or thermal rate—\text{—}
Fitted response time—\text{—}
Known beam-off response—\text{—}
Model selected-channel transmission—\text{—}
Selected exposure midpoint—\text{—}
Exposure duration—\text{—}
Total incident areal dose—\text{—}
Usable sampled frames—\text{—}
Experiment target—\text{—}

Physics tutorial

In-situ TEM: Stimulus or Beam?

BackgroundA TEM can film a specimen while a holder heats it, applies bias or pulls it. The imaging beam also acts on the specimen. Start with bias: two dark markers let you measure displacement while removing their shared drift. Then compare the same measurement at a higher dose.

Why it mattersFor bias and load, recover the response coefficient or modulus within 15 percent of the known input, with beam perturbation at most 8 percent. Use the exposure-integrated fit, at least 20 resolved frames and 8 mean counts per pixel. In the thermal preset, the separate target remains a rate within 10 percent, at least 35 percent intrinsic conversion and an intrinsic rate times frame interval at most 0.2.

Start with the essentials

Focus question
In an in-situ TEM experiment, is the beam observing the response or helping drive it?
One-sentence intuition
A beam can make a response easier to measure and change that response at the same time.

Core mathematical model

Bias displaces a tethered marker

γx˙+kx=qV/g+Fb(t)x∞,0/V=q/(gk)\begin{aligned}\gamma\dot x+kx&=qV/g+F_b(t)\\x_{\infty,0}/V&=q/(gk)\end{aligned}

The field is uniform between electrodes. Stiffness, charge and gap are known inputs. The beam contributes an assigned force during illumination; it is not inferred from the displacement alone.

Load stretches a viscoelastic specimen

ηε˙+E(D)ε=σE(D)=E0/(1+αD)ε^=(x^R−x^L)/L0−1\begin{aligned}\eta\dot\varepsilon+E(D)\varepsilon&=\sigma\\E(D)&=E_0/(1+\alpha D)\\\widehat\varepsilon&=(\widehat x_R-\widehat x_L)/L_0-1\end{aligned}

The spring and dashpot act in parallel. The specimen has a fixed viscosity and an assigned dose-dependent modulus. Marker separation removes common translation. The model is limited to strains no larger than 20 percent.

Fit the recorded exposure, not its midpoint

r‾=A[1−e−t0/ττΔt(1−e−Δt/τ)]\overline r=A\left[1-e^{-t_0/\tau}\frac{\tau}{\Delta t}\left(1-e^{-\Delta t/\tau}\right)\right]

Marker positions are fitted from counted profiles with a known point-spread width and flat-field level. Their displacement or strain is fitted to this exposure mean. The inferred voltage coefficient or modulus also uses the applied drive. A changing modulus makes this a constant-parameter approximation.

Thermal and beam contributions to the hazard

kT=k∗e−EakB(1/T−1/T∗)H(t)=kTt+σD(t)\begin{aligned}k_T&=k_*e^{-\frac{E_a}{k_B}(1/T-1/T_*)}\\H(t)&=k_Tt+\sigma D(t)\end{aligned}

The conversion follows a prescribed first-order law. It does not model nucleation or describe a specific material.

Conversion measured from counts

u^=1−N‾/NflatCNflat=ηJp2Δt T\begin{aligned}\widehat u&=\frac{1-\overline N/N_{\rm flat}}{C}\\N_{\rm flat}&=\eta Jp^2\Delta t\,\mathcal T\end{aligned}

The flat-field level and the contrast are known calibrations, and the fraction is computed from the recorded counts themselves.

Fitting a rate to finite exposures

u‾(k)=1−e−kt01−e−kΔtkΔtu(t)=1−e−H(t)\begin{aligned}\overline u(k)&=1-e^{-kt_0}\frac{1-e^{-k\Delta t}}{k\Delta t}\\u(t)&=1-e^{-H(t)}\end{aligned}

Each frame averages the conversion over its exposure, and the fit matches one constant apparent rate to those averages. A good fit does not prove that heat caused the change.

Common difficulties

A good fit does not identify the cause

Typical misconceptionIf the curve fits the frames, its coefficient is the material property without the beam.

Better mental modelThe fit sees the recorded response. The beam-off reference and perturbation audit are separate calculations from known inputs. They are available in this teaching model; a real experiment needs dose controls and independent calibration. The electrical and softening laws here illustrate the ambiguity and do not represent a calibrated material.

Run the experiment

  1. 01

    Bias and count-derived drift correction

    Drag the gold handle or change the voltage. Switch drift correction off in the advanced controls, then inspect the same stored sequence.

    What to observe: The stationary marker estimates translation from the image. Correcting it leaves the moving marker’s displacement; changing processing settings does not acquire new counts.
  2. 02

    Distinguish load from beam softening

    Compare Load with The beam softens the specimen. Look at the counted marker separation and the inferred modulus.

    What to observe: The brighter sequence has more counts and more strain. Attributing all that strain to the applied stress underestimates the initial modulus.
  3. 03

    Test each limit

    Choose Too few electrons to track, then Heat. In the thermal branch, adjust temperature, flux and cadence and inspect the count-derived rate.

    What to observe: Unresolved marker profiles cannot give a material coefficient. The thermal branch instead measures conversion, with its own drift calibration and target.
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