ORSO file formats & data analysis: simplified model description
Jochen Stahn, Artur Glavic, Paul Scherrer Institut, Switzerland
Brian Maranville, NIST, USA
2022-03-14
simplified model description for .ort files
This is a joint project by the file formats and the data analysis working groups.
Based on slack discussions and online meetings, Artur and Jochen suggest the following approach for a simple and flexible way to define a first step sample model.
This document is not free of uncertainties or contradictions! We will correct this according to the state of the discussion.
All previous suggestions and variants are removed in order to avoid confusion.
aims
- experiment planning
The model might be used to estimate counting times, statistics and experimental
settings already before and during the experiments. - completeness of reflectivity file
The reflectivity file can be related to a sample model without the external connection manufactorers lab journal….). - data analysis
The standadisation allows the analysis software to automatically create a starting model which is not too far from the real one. - indexing of data and analysis
A standadised model might be used for indexing and filing of the data - within the lab or on a more general scale. This might be used to train AI algorithms.
complexity
This langage allows to provide a very simple model description on only 2 lines:
model:
stack: air | Ni 100 | SiO2 0.5 | Si
The key words used in the stack (here air, Ni, SiO2 and Si) either refere to an
external data base (https://slddb.esss.dk/slddb/), a local dictionary or a declaration within the model entry.
More complexity (e.g. magnetic induction, roughness, reduced density, …) can be provided by adding a few more lines.
materials:
Ni:
rel_density: 0.95
Dentailed models for complex samples might reach several tens of lines, thus they are no longer that simple. The idea then is, that recuring fracments (sub-stacks, layers, materials) are defined in detail and strored in a local dictionary or even in the orso data base. The model description in the header then stays simple and easy to use.
structure
The model description has the following structure:
sample:
model:
stack: string mandatory \
sub_stacks: dict optional |
layers: dict optional | hirarchy of keys to define a SLD depth profile
compositions: dict optional |
materials: dict optional /
globals: dict optional \
reference: string optional |
schema: string optional | meta data
origin: string optional /
The information is organised according to YAML rules but for the stack string(s). The reason is to make it simple and less error-prone to enter this information by hand.
stack
The simplified model description is given in one line. This allows for a very compact notation, but restricts the content to the absolute minimum.
Rules:
- According to the first axiom of optics, the beam enters from the left. I.e. the backing medium is the last entry in the `stack.
- Entries in the stack are separated by the pipe symbol
|. - Repeating sub_stacks are marked with
<number> ( ... ). - Each entry has a name and probably an assosiated thickness. These are separated by one or more spaces.
- The default thickness unit is
nm.
(These rules allow to expand the stack string into a YAML compliant sequence)
Examples:
The standard 1000 angstrom Ni film to check the resolution:
stack: air | Ni 100 | SiO2 0.5 | SiA polarising multilayer with 25 repetitions of 70 angstrom Fe and 70 angstrom Si:
stack: air | 25 ( Si 7 | Fe 7 ) | SiNo information about the magnetic induction is given on this level.
A lipid multilayer in a solid-liquid cell:
stack: Si | SiO2 0.5 | lipid_multilayer | waterNo details about the organic film are given on this level. To allow for automated processing, further information must be provided in the
sub_stacksection or in a data base.
sub_stacks
Each substack is made up of one or several layers. It has a unique name which is used to relate the substack to an entry in the stack. The purpose of this dictionary is to enable a simple stack for complicated models and to provide multy-layer building blocks in data bases.
sub_stacks:
<name>:
repititions:
int
optional (default: 1)
defines how often the substack is repeated. A negaive value means an inversion of the order.
stack:
str
optional
Same rules as for the top-level stack apply.
sequence:
list
optional
Instead of an other stack, the layers and their sequence are defined.
Examples:
expansion of the physical (chemical) unit lipid multilayer into a sequence of layers:
sub_stacks: lipid_multilayer: repetitions: 4 stack: head | tail | tail | headthe same layer sequence, but assembled hirarchically stating with chemical units:
sub_stacks: lipid: sequence: - material: headstuff thickness: 0.5 - matrial: tailstuff thickness: 2.2 lipid_inverse: repetitions: -1 stack: lipid lipid_bilayer: stack: lipid | lipid_inverse lipid_multilayer: repetitions: 4 stack: lipid_bilayer
layers
If information about a layer besides its chemical composition (and thus the density form a data base) and its thickness is needed, this has to be defined here. A layer has homogeneous properties. I.e. no density gradients (might be a future option) or separation into sub-layers (that is covered by sub_stack).
layers:
<name>:
Each layer from the layers list has a unique name which
relates it to an entry in one of the stacks.
Layers defined in a sub_stack list are only used once
and do not require naming.
thickness:
This overwrites the thickness given in the stack
roughness:
material:
Either a name of a material or dictionary with
material parameters. See below.
composition:
series of <material>: <rel_density> pairs
materialexamples:
simple case, reference to the
materialslist or a data baselayers: iron: material: Fea bit more detailed, therefor no internal reference
layers: iron: material: {formula: Fe, magnetic_moment: 2.4, mass_density: 6.8}reduced density (voids, coverage, …)
layers: nickel: composition: Ni: 0.95 thickness: 7.5
composits
A composit behaves like a material, but is made up from (on or) several materials with respective relative densities. It enables an easy way to define mixtures (solvents, interdiffusion, absorption).
compositis:
<name>:
<material 1>: <rel. density 1>
<material 2>: <rel. density 2>
Example:
composits: solvent: cyclohexane: 0.6 toluene: 0.4
materials
Each material has a unique name which relates it to an layer.composition entry or referenced in a stack.
materials:
<name>:
formula:
sld:
The scattering length density for the radiation that was
used in this experiment.
(neutron or x-ray for given energy)
mass_density:
number_density:
magnetic_moment:
rel_density:
The density is taken from tabulated bulk values and
multiplied with this parameter (on top of the other
densities!).
deuteration:
For materials containing hydrogen this parameter allows
to tune the deuteration level while keeping the number
density constant.
Details have to be figured out....
Examples:
magnetic moment for iron
materials: Fe: magnetic_moment: 2.2clear names for solvents where the formula might be ambiguous:
materials: cyclohexane formula: C6H12 mass_density: 0.778 toluene formula: C7H8 mass_density: 0.87
globals
The globals section allows to (re-)define model parameters or units which apply to the full stack and if applicable also to the following sections sub_stacks, layers and materials.
Unless overwritten, the following default values are used:
globals:
length_unit: nm
mass_density_unit: g/cm^3
number_density_unit: 1/nm^3
sld_unit: 1/angstrom^2
magnetic_moment_unit: muB
roughness: 0.5
reference
A string defining the model language and version to be used to interpret the data.
Example:
reference: ORSO model language | 1.0 | https://www.reflectometry.org/projects/simple_model
schema:
schema: <URL>
origin
A string to declare where the model parameters come from.
Example:
origin: thicknesses based on XR mesurements, nominal compositions
examples
sample:
model:
origin: guess based on preparation
stack: air | 10 ( Si 7 | Fe 7 ) | Si
extended version (with more information) on the level of the starting model for data analysis:
sample:
model:
origin: guess based on preparation / XRR
stack: air | 10 ( Si 70 | Fe 70 ) | Si
materials:
Fe
magnetic_moment: 2.2
sld: 5.02e-6
Si
formula: SiN0.01
rel_density: 0.95
globals:
length_unit: angstrom
m_moment_unit: muB
roughness: 5
sld_unit: 1/angstrom^2
reference: ORSO model language | 1.0 | http://bla.bli
or a quite complicated model to illustrate what is possible:
sample:
model:
origin: guess by J. Stahn
stack: substrate | film | water
sub_stacks:
substrate:
sequence:
- material: Si
sigma: 2
- material: SiO2
thickness: 5
sigma: 3
film:
repetitions: 5
stack: head_group 4 | tail | tail | head_group 4
layers:
tail
material: tailstuff
thickness: 22.
compoisits:
water:
H2O: 0.3
D2O: 0.7
materials:
head_group:
sld: 0.2e6
tailstuff:
formula: CH2
mass_density: 1.2
SiO2:
formula: SiO2
Si:
formula: Si
globals:
sigma: {magnitude: 5, unit: angstrom}
length_units: angstrom
mass_density_units: g/cm^3
sld_unit: 1/angstrom^2
reference: ORSO model language | 1.0 | https://www.reflectometry.org/projects/simple_model
Here film referes to a stack with 5 repetitions of some organic bilayer, which in turn consists of 4 sublayers. These are defined either again as layer (here for the tails) or directly with a thickness and a material. The materials section allows to define the materials used above. When missing, the name is taken as the chemical formula (e.g. Si or SiO2) or as a pre-defined material (water, air) and the corresponding values are taken from a data base.
These examples show how a model might be declared. There are various ways to do so for exactely the same model, and the choice depends mainly on the human readability and on logical units (like POPC). For automated writing (e.g. as an output from the data analysis software), we will have to find a reasonable and programmable approach….
Implementation and examples
The model desciption has been implemented as a .ort header item in a Pull Request to the orsopy package with options to resolve layers for software to easily build a model system from the specification. Header examples and some automatic plotting scripts are included, too. See the Pull Request for more details.