Evidence map›Paper›PMID 40839833›Full record

ArticleNano letters2025

Imaging the Acceptor Wave Function Anisotropy in Silicon.

Manuel Siegl, Julian Zanon, Joseph Sink, Adonai Rodrigues da Cruz, Holly Hedgeland, Neil J Curson, Michael E Flatté, Steven R Schofield

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nano letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Manuel SieglLondon Centre for Nanotechnology, University College London, London WC1H 0AH, U.K.
Julian ZanonDepartment of Applied Physics and Science Education, Eindhoven University of Technology, Eindhoven 5612 AZ, The Netherlands.ORCID 0000-0002-2830-1361
Joseph SinkDepartment of Physics and Astronomy, University of Iowa, Iowa City, Iowa 52242, United States.ORCID 0000-0002-4969-1565
Adonai Rodrigues da CruzDepartment of Physics and Astronomy, University of Iowa, Iowa City, Iowa 52242, United States.ORCID 0000-0001-8719-399X
Holly HedgelandLondon Centre for Nanotechnology, University College London, London WC1H 0AH, U.K.ORCID 0000-0003-3703-7942
Neil J CursonLondon Centre for Nanotechnology, University College London, London WC1H 0AH, U.K.ORCID 0000-0002-5661-0559
Michael E FlattéDepartment of Applied Physics and Science Education, Eindhoven University of Technology, Eindhoven 5612 AZ, The Netherlands.ORCID 0000-0001-5093-1549
Steven R SchofieldLondon Centre for Nanotechnology, University College London, London WC1H 0AH, U.K.ORCID 0000-0002-0727-3015

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present the first scanning tunneling microscopy (STM) image of hydrogenic acceptor wave functions in silicon. These acceptor states appear as square-ring-like features in STM images and originate from near-surface defects introduced by high-energy bismuth implantation into a silicon (001) wafer. Scanning tunneling spectroscopy confirms the formation of a p-type surface. Effective-mass and tight-binding calculations provide an excellent description of the observed square-ring-like features, confirming their acceptor character and attributing their symmetry to the light- and heavy-hole band degeneracy in silicon. A detailed understanding of the energetic and spatial properties of acceptor wave functions in silicon is essential for engineering large-scale acceptor-based quantum devices.

Indexed as

acceptor stateseffective-mass theoryquantum device engineeringscanning tunneling microscopysilicontight binding Green’s functions

Identifiers

PMID40839833
PMCPMC12464996

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.