Dr. Simon Bates heads Triclinic's Advanced Computational Chemistry Practice.
Triclinic has full solid-state and amorphous materials analysis capabilities which are carried out by our Computational Chemistry Group. For a complete list of our materials characterization capabilities please click here
New ways to obtain a better understanding of your solid materials…
Our focus in the Computational Chemistry Group is the resourceful use of all data skillfully collected on common laboratory instrumentation using minimal material. We accomplish this through real time optimization of instrument configurations, combined with both "off the shelf" and proprietary analytical software. We call this Total Diffraction Analysis TM (TDA).
With these methods we're able to:
- Determine phase purity
- Rapidly classify patterns during screening and development
- Identify hydrates and solvates based on unit cell void spaces
- Model materials in response to stress or commercial processes
- Predict crystal habit
- Differentiate "new peaks" as contaminants or simply symmetry disallowed (non-contaminant) peaks
- Develop Solid Mixture Quantitative Methods
A key component of the Computational Chemistry Group is the expertise required to perform and optimize the TDA data depending on the materials being analyzed and the analytical tools used to collect the data.The application of TDA methods to X-ray powder diffraction and solid state structural characterization in general are described below. Please contact Triclinic Labs directly for in-depth information on these methods.
X-Ray Powder Diffraction (XRPD) is a technique which provides an enormous amount of data regarding the identity and structure (long range and short range order) of a solid state material. In performing the traditional Bragg type of analysis on powder diffraction data where the crystalline peak intensities, positions and widths form the basis of the analysis, much of the available information content of the powder pattern is not utilized. TDA offers Triclinic Scientists a method of extracting that information.
The TDA computational methods can provide unique and critical information related to material behavior and performance such as:
- Long Range and Short Range Order Determination
- Advanced Characterization of Crystalline Phases
- Quantitative Methods for Drug Products
- Pattern Recognition and Cluster analysis: Rapid prototyping of solid form screening data
- Advanced Analysis of Amorphous Materials and Dispersions
- Advanced Analysis of Lyophile Cakes, Formulations, and Drug Products
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Total Diffraction Analysis
The crystalline form of a material is often considered to uniquely determine the material properties. However, away from equilibrium (production processing, dissolution, melting point) the local deviations from the mean crystal structure can significantly alter the expected properties of a crystalline form. Melting points can be lowered, dissolution rates increased and resistance to crystalline form change during processing can be removed. X-ray powder diffraction can provide significantly more information than just a crystalline form fingerprint. At Triclinic Labs, the use of optimized and open design XRPD systems in combination with both “off the shelf” and proprietary software has enabled routine Total Diffraction Analysis while typically using < 10mg of material.
Figure 1: Total Diffraction Analysis: Digital filtering of XRPD data collected from Avicel (MCC) allows the powder pattern to be split into different order length-scales. The longest range order (crystalline) will show up as relatively sharp peaks while the short-range order will contribute a broad diffuse scattering halo. Single point defects represent a local departure from long-range order and as such may appear as a short range order halo. Intermediate length-scale order represents small ensembles of molecules acting coherently within the ensemble but incoherently with respect to the mean sample matrix.
Advanced Analysis of Crystalline Phases
Currently at Triclinic, we have a fully configurable Scintag diffractometer, a state-of-the-art Rigaku SmartLab System, and the in-house technical expertise to run these instruments to collect the optimal data for a wide variety of different sample types and different environmental conditions. These capabilities allow us to extract much more information from a XRPD pattern than simply a finger-print identification.
Indexing and Rietveld Analysis
Indexing is the assignment of Miller indices to each of the measured diffraction peaks within a powder pattern. Although the initial indexing may be performed on the ‘significant peaks’ alone, all the observed diffraction peaks must eventually be assigned an index if the material is a single crystalline phase. The calculation of Miller indices requires a crystal unit cell with known lattice parameters: a, b, c, alpha, beta, gamma. So the process of indexing involves the selection or identification of the crystalline unit cell that allows all the observed diffraction peaks to be assigned Miller indices. As the crystal unit cell tends towards triclinic with more degrees of freedom, the identification of the correct and unique unit cell becomes more difficult and often becomes a random search through many possibilities. Based on many years of experience performing indexing and developing indexing algorithms for in-house powdered patterns, Triclinic has established an indexing process which significantly improves the robustness of indexing results.
Being able to determine a crystalline unit cell allows the identification of a number of important material properties:
- Assurance of crystalline phase purity (which is often unknown during early screening)
- Identification of a crystalline phase as a probable hydrate or solvate based on unit cell void space (unit cell volume is one of the most robust parameters from indexing)
- Knowledge of the unit cell symmetry provides a framework for modeling material response to physical stress such as experienced in a production environment
- Basic habit prediction is possible once the unit cell is known
- Understanding that A “new peak” showing up in the XRPD pattern of a material produced using a commercial process can be a symmetry-disallowed peak that arises because of induced defects rather than being a peak from a contaminant
- Improved knowledge from indexing that can make up for poor-quality data resulting from small sample sizes
- Efficient pattern matching (in screening, for example) based on expected peak positions calculated from the unit cell
- Unit cell parameters form the basis of both Rietveld and full pattern solid mixture quantitative analysis
Rietveld Analysis was initially developed for single crystal structure refinement from Neutron diffraction powder patterns. Since then, the method has been extensively developed into a number of different software packages for not only single crystal structure refinement but also quantitative phase analysis and materials property analysis using both X-ray and Neutron powder diffraction. At Triclinic Labs, Rietveld analysis is one of the more common tools used for rapid semi-quantitative analysis and general material microstructure analysis. One of the perceived limitations of the Rietveld method is the need for single crystal structures for each phase of interest. With many of the new packages it is possible to either use a measured reference pattern, a list of peaks or an ‘effective crystal structure’ in place of the actual crystal structure. The use of a reference pattern limits the use of the Rietveld software to semi-quantitative analysis only (after calibration) but an ‘effective crystal structure’ being built from an indexing solution can be additionally used for material microstructure analysis.
Rietveld analysis provides capabilities that allow:
- Rapid semi-quantitative analysis of crystalline phase composition (no need for standards or calibration if all crystal structures are known)
- A frame-work for a full quantitative method in combination with calibration and validation (a limited number of standards can be used to develop a multicomponent quantitative method over a wide range of compositions – often in combination with chemometrics)
- Micro-structure analysis (crystal size/shape and micro-stress)
- Determination of preferred orientation within a sample
- Change in crystal structure induced by time, temperature, humidity (water content), solvent vapor (solvent content) and physical stress
- Modeling the robustness of a crystalline polymorph to different production steps
Figure 2. Rietveld semi-
quantitative analysis of complex mixed powder patterns enables the extraction of the raw scattering intensity from each component and can handle (for the most part) the effects of changes in micro-structure like preferred orientation. In the two phase binary powder pattern above, Rietveld semi-quantitative refinement of texture parameters and scale factors is performed on only one of the phases; acetaminophen shown in blue. The acetaminophen pattern was built using scratch-mode without an input crystal structure.
For information on solid mixture quantitation please click here.
