Nikon L200ND motorized optical microscope with laser autofocus
The Nikon L200ND features encoder-feedback motorized stage in X, Y, and Z. A laser autofocus unit using 850 nm light can automatically maintain focus over the sample. The microscope features a high-perfomance camera for high-resolution low-noise imaging.
6-position motorized nosepiece
Reflected light brightfield
Reflected light darkfield
Reflected light polarization/DIC/Normanski
Transmitted light brightfield
1x, NA = 0.03, WD = 3.8 mm, 2.90 um/px, FOV: 14235.2x9466.9 um
2.5x, NA = 0.075, WD = 6.5 mm, 1.15 um/px, FOV: 5620.2x3737.7 um
5x, NA = 0.15, WD = 18 mm, 0.58 um/px, FOV: 2832.0x1883.4 um
20x, NA = 0.45, WD = 4.5 mm, 0.14 um/px, FOV: 708.2x471.0 um
50x, NA = 0.80, WD = 1 mm, 0.06 um/px, FOV: 283.0x188.2 um
100x, NA = 0.90, WD = 1 mm, 0.03 um/px, FOV: 140.7x93.6 um
NA=Numerical Aperture, WD=Working Distance, FOV=Field Of View
Nikon DS-Ri2, F-mount high-performance color camera
Max resolution: 4908 x 3264 pixels (16.25 MP)
6 fps at max resolution
3x3 binning mode resolution: 1636 x 1088 pixels (1.8 MP)
45 fps at 3x3 binning
Stage and focusing unit:
250 mm x 180 mm motorized stage, 2 mm pitch ball screw and 200-step motors
Encoder feedback with 0.1 um linear encoders in X and Y
Reproducibility in X and Y is better than 1 um
Rotatable wafer chuck for up to 200 mm wafers
100 mm x 100 mm glass plate for transmitted light
Motorized Z drive with encoder
Laser autofocus unit with 850 nm laser, offset lens, fast focusing, and adjustable laser power
NIS-A 6D: module for 6D acquisition and image stitching
NIS-A EDF: module for extended depth of focus (Z-stacking)
NIS-A JOBS: programming interface for automated control
NIS-A GA3: General Analysis 3, automated metrology interface
This system is capable of generating a large amount of data. You are welcome to store it on the tool for up to one month, but we don't guarantee it with backups etc. Please think about where you want to transfer your data to, after acquisition. ONLY save data to the D: ("Storage") drive. NEVER on C:.
nd2 - Standard raw format from Nikon. No loss of information. No compression. Full header metadata such as objective used, stage position etc. Recommended for most cases. Downside is that images get large and that only certain applications can open them.
tif - Lossless format that can be opened with most image applications. Most metadata is lost.
jpg, png, etc - Lossy formats that are generally not recommended. Only for non-critical applications. Upside is that they are opened by most image software, and the images are smaller in size.
Image software for nd2 files:
There is a free program from Nikon that you can download and install on your own computer for viewing and converting nd2 files. It is called NIS Elements Viewer. It can be found already installed at the NFL analysis virtual machine (analysis.mc2.chalmers.se) or, even better, it can be downloaded from:
nd2 files in python:
nd2 files can be directly imported to python using for example the pims library. A simple example program for this can be found in the tool documents.
There are several ways of making sure each image is taken in focus. They all have their pros and cons, and are each suitable for different applications:
Static - focus manually on one point and then keep that focus point for all other images.
Pros: fast, not sensitive to sample reflectivity.
Cons: not very precise, doesn't follow sample geometry at all, only suitable for low magnification objectives
Focus Surface - focus manually on a set of points (minimum three) and interpolate/extrapolate focus positions
Pros: fast, not sensitive to sample reflectivity, reasonably precise up to 20x objective
Cons: not precise enough for 50x and 100x objectives. 20x is normally ok
Software autofocus - move the Z a distance up and down and automatically find optimal focus from the images
Pros: easy to setup, on objectives 5x, 20x, 50x, and 100x. Works on most types of patterned samples
Cons: slow, needs patterned sample
Hardware autofocus - PF850 850nm laser height sensor
Pros: very fast, very accurate, works for objectives 5x, 20x, 50x, and 100x
Cons: needs specific configuration for every objective-sample_type combination