Additive Manufacturing in Atomic Layer Processing Mode

Kundrata I, Barr M, Tymek S, Döhler D, Hudec B, Brüner P, Vanko G, Precner M, Yokosawa T, Spiecker E, Plakhotnyuk M, Fröhlich K, Bachmann J (2022)


Publication Type: Journal article

Publication year: 2022

Journal

DOI: 10.1002/smtd.202101546

Abstract

Additive manufacturing (3D printing) has not been applicable to micro- and nanoscale engineering due to the limited resolution. Atomic layer deposition (ALD) is a technique for coating large areas with atomic thickness resolution based on tailored surface chemical reactions. Thus, combining the principles of additive manufacturing with ALD could open up a completely new field of manufacturing. Indeed, it is shown that a spatially localized delivery of ALD precursors can generate materials patterns. In this “atomic-layer additive manufacturing” (ALAM), the vertical resolution of the solid structure deposited is about 0.1 nm, whereas the lateral resolution is defined by the microfluidic gas delivery. The ALAM principle is demonstrated by generating lines and patterns of pure, crystalline TiO2 and Pt on planar substrates and conformal coatings of 3D nanostructures. The functional quality of ALAM patterns is exemplified with temperature sensors, which achieve a performance similar to the industry standard. This general method of multimaterial direct patterning is much simpler than standard multistep lithographic microfabrication. It offers process flexibility, saves processing time, investment, materials, waste, and energy. It is envisioned that together with etching, doping, and cleaning performed in a similar local manner, ALAM will create the “atomic-layer advanced manufacturing” family of techniques.

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How to cite

APA:

Kundrata, I., Barr, M., Tymek, S., Döhler, D., Hudec, B., Brüner, P.,... Bachmann, J. (2022). Additive Manufacturing in Atomic Layer Processing Mode. Small Methods. https://doi.org/10.1002/smtd.202101546

MLA:

Kundrata, Ivan, et al. "Additive Manufacturing in Atomic Layer Processing Mode." Small Methods (2022).

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