Soft Electrostatic RAFA Lens’s Electron Beam Imaging and Diagnosis of Individual Atoms In 3D Specimen – A Proposal
Bibliographic record
Abstract
The ultimate goal of quantitative high resolution electron microscopy is to determine the type of atom at a specific site regardless if it’s a three dimensional amorphous or crystalline material. The proposal herein describes an imaging and diagnostic method that may be able to achieve this capability. Current imaging systems have excellent lateral resolution but lack resolution along the pathlength of the beam due to the lack of an angle to focus the beam plaguing current refractive, deflective and reflective lenses. Apertured blocked beams have the problem of removing most of the beam’s intensity. The reflective advanced focusing aperture (RAFA) lens corrects these problems while maintaining ∼100% of the beam intensity currently being demonstrated using acoustic and laser beams easily implemented since they reflect off a solid surface independent of the beam’s wavelength obeying Snell’s Law so a laser beam focuses to the same far probe position as the acoustic beam enabling new medical treatment modalities [1]. Electron and ion beams are more challenging as their reflective surface requires an electrostatic potential (Fig. 1), which is highly sensitive to fringing fields within the lens’s environment. The proposed application of the electrostatic RAFA lens avoids fringing fields by replacing the reflective surface of Rose’s imaging system placed outside of the electron microscope’s column (Fig. 2) using a magnetic prism deflecting the electron beam towards the reflective electrostatic RAFA lens, which focuses the beam back into the electron microscope’s column [2]. The focused probe intensity within the specimen when apertured enables collection of elastically and inelastically scattered electrons for imaging by a camera and being diagnosed by EELS with no contributions from above or the sides of the probe position (Fig. 3) If collection of the intensity is performed in the Fraunhofer plane, scanning of the beam through the specimen can occur without the aperture having to move. Simultaneous quantitative imaging is accomplished by first collecting intensity from the bottom surface of the specimen and then moving progressively upwards into the specimen. Spherical aberration is compensated by the design of the reflective surface of the RAFA lens and focusing the electron probe/virtual source on the optic axis and chromatic aberration is compensated by using a soft electrostatic surface that varies its potential depending on the acceleration voltage noise and perhaps even the thermal magnetic field noise, both to be presented. A singularity exists at the center of the RAFA lens that shouldn’t be a problem. RAFA lens and mirror are made small (∼10 microns) and thin (∼10 microns) using Focused Ion Beam (FIB) having an aperture hole size of ∼100s microns. Dimensions are flexible. Electrostatic repulsive force of surfaces is same as electron beam’s acceleration voltage. Electron beam deflection from column using a prism lens towards the RAFA lens where it is focused back for re-insertion into the column. Diffuse elastic and inelastically scattered electrons from focused probe/virtual source positions are used to form 3D STEM image and identify elemental compositions and other properties using EELS. In diffraction mode, Fraunhofer imaging, the aperture does not need to move when 3D rastering the beam through the specimen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".