EFM Evaporators - FOCUS GmbH

2
Precise Real-Time
Flux Control
The EFM evaporators with integrated
flux monitor are ideal for high-purity
evaporation of a wide range of materials
in UHV, ranging from refractory metal
wires and rods to delicate, reactive substances
evaporated from crucibles.
Materials such as Fe, Co, Ni, Pt, Ag, Au, Al,
Mo, Ta, W, and also non-conducting materials
or semiconductors, e.g. silicon, can be evaporated.
Delicate or reactive materials can be
precisely and cleanly deposited.
Using a stainless steel crucible with a nozzle, a
gentle Knudsen evaporation of C 60 and many
other aromatic compounds is achieved with
minimum loss of material. An integral flux
monitor enables reproducible real-time control
of the deposition rate and, once calibrated,
removes the need for a quartz thickness monitor.
The degassing state of the evaporant and
the start of the real flux are also shown more
accurately than by temperature measurement.
The flux is displayed on the control unit and is
also available for computer-controlled evaporation
processes.
A built-in shutter with manual or optional computer
controlled motor activation governs the
deposition time. The desired flux can be monitored
and adjusted with the shutter closed.
The EFM evaporators are designed to effectively
focus the heating power onto the evaporant
with minimum heat dissipation.
To absorb the heat radiation
and maintain an ultra high
vacuum (to below 10 -10 mbar),
the evaporant is completely
surrounded by a water-cooled
shroud.
The rear-loading feature of
the EFM evaporators enables
crucibles to be exchanged
without detaching the EFM
from the vacuum chamber
for deposition of different
materials with identical source
alignment.
Low stray magnetic fields at
the sample enable the evaporator
to be used during RHEED
or LEED analysis.
Example of Ag-induced structural transformation
at 850 K starting at steps of
Si(111)7x7, observed by STM during continuous
in-situ evaporation. (210 x 210 nm 2 ;
the moiré pattern results from interference
of 7x7 structure and data point density)