Periodic Reporting for period 1 - MAGIMOX (Nanometre scale imaging of magnetic perovskite oxide thin films using scanning transmission electron microscopy)
Reporting period: 2019-04-01 to 2021-03-31
Functional properties in materials are an essential part of modern society, enabling a wide range of computing, information and sensor technologies. An example of functional materials are the magnetic ones, which is today used in several devices like hard drives for storing data, and sensors. In addition, magnetic properties have attracted a great deal of interest for new types of energy efficient device concepts. To improve these devices, and design new ones, there is a need to understand how these materials behave at nanometre length scales, since the interesting physics often arise there. However, there is a lack of experimental techniques for looking at the magnetic properties in these materials, especially at very small length scales. Another important factor is studying these properties across phase transitions. For example, magnetic materials become non-magnetic above certain temperatures, and seeing this change from magnetic to non-magnetic can reveal information about the underlying physical phenomena controlling device performance.
Scanning Transmission Electron Microscopy (STEM) is a powerful imaging technique, which can study materials down to single atoms. However, historically it has mostly been used to study the structure and composition of materials, not their functional properties such as magnetic fields. With recent advances in fast pixelated STEM detectors, it has become possible to directly image the magnetic fields. However, much work remains, both in making this work practically on most STEM instruments, and making the technique work across a range of materials.
MAGIMOX aimed to improve this, by utilizing the STEM in co-junction with the recently developed fast pixelated STEM detectors, to study both the structure and magnetic properties in perovskite oxide thin films. Thus the overall objective was to study these specific materials, however since these detectors were fairly new, a great deal of method and analysis software development was necessary.
Scanning Transmission Electron Microscopy (STEM) is a powerful imaging technique, which can study materials down to single atoms. However, historically it has mostly been used to study the structure and composition of materials, not their functional properties such as magnetic fields. With recent advances in fast pixelated STEM detectors, it has become possible to directly image the magnetic fields. However, much work remains, both in making this work practically on most STEM instruments, and making the technique work across a range of materials.
MAGIMOX aimed to improve this, by utilizing the STEM in co-junction with the recently developed fast pixelated STEM detectors, to study both the structure and magnetic properties in perovskite oxide thin films. Thus the overall objective was to study these specific materials, however since these detectors were fairly new, a great deal of method and analysis software development was necessary.
The work done in this project can be split into three main parts: i) data processing analysis software development, ii) microscope alignment and detector optimization, and iii) material studies. This project only ran for 11 out of the intended 24 months, as the fellow started in an associate professor position on analysis of functional properties using STEM. Thus, much of the work started in MAGIMOX will continue over in this new position.
On the i) method and analysis software development side several improvements were delivered. The major one being optimized big data processing algorithms for studying phase transitions, and improved documentation and examples. All these changes were rolled into the pixStem open source Python library. Other software improvements included the control software for the fast pixelated STEM detector, which was included in the merlin_interface open source software library.
On the ii) instrumentation side, much work was done in optimizing the STEM for magnetic imaging, and calibrating it for doing magnetic measurements. Doing magnetic imaging in the STEM requires the major lens in the system to be turned off, as the sample material resides within the magnetic field of this lens. Turning this lens off greatly affects the electron optics of the system, necessitating a great deal of alignments and optimizations. Routines for doing this were developed and documented.
To facility a more rapid start of part iii) in the project a non-perovskite material, permalloy, was initially used to optimize the instrument. This was due to difficulties in preparing adequate perovskite oxide thin film samples for the STEM. However, this was finally resolved and magnetic perovskite oxide La0.7Sr0.3MnO3 thin films were imaged as a function of applied magnetic field. In addition to the magnetic imaging, another goal of the project was the study of structural phase transitions, through heating materials. Due to the aforementioned sample issues, some of this work was done on other functional oxide materials, where samples were readily available.
The major realization during the project was that separating out the artefacts caused by structural effects were the most crucial factor for achieving robustness of the method, and thus producing reliable observations. Disentanglement of such artefacts were challenging. Although improved data processing techniques helped suppress these effects, the main conclusion was that better experimental methodologies are needed to address this comprehensively and robustly. This is the basis for the fellow's new associate professor position at NTNU, where such experimental methodologies are available.
On the i) method and analysis software development side several improvements were delivered. The major one being optimized big data processing algorithms for studying phase transitions, and improved documentation and examples. All these changes were rolled into the pixStem open source Python library. Other software improvements included the control software for the fast pixelated STEM detector, which was included in the merlin_interface open source software library.
On the ii) instrumentation side, much work was done in optimizing the STEM for magnetic imaging, and calibrating it for doing magnetic measurements. Doing magnetic imaging in the STEM requires the major lens in the system to be turned off, as the sample material resides within the magnetic field of this lens. Turning this lens off greatly affects the electron optics of the system, necessitating a great deal of alignments and optimizations. Routines for doing this were developed and documented.
To facility a more rapid start of part iii) in the project a non-perovskite material, permalloy, was initially used to optimize the instrument. This was due to difficulties in preparing adequate perovskite oxide thin film samples for the STEM. However, this was finally resolved and magnetic perovskite oxide La0.7Sr0.3MnO3 thin films were imaged as a function of applied magnetic field. In addition to the magnetic imaging, another goal of the project was the study of structural phase transitions, through heating materials. Due to the aforementioned sample issues, some of this work was done on other functional oxide materials, where samples were readily available.
The major realization during the project was that separating out the artefacts caused by structural effects were the most crucial factor for achieving robustness of the method, and thus producing reliable observations. Disentanglement of such artefacts were challenging. Although improved data processing techniques helped suppress these effects, the main conclusion was that better experimental methodologies are needed to address this comprehensively and robustly. This is the basis for the fellow's new associate professor position at NTNU, where such experimental methodologies are available.
There are several aspects which extend beyond the state of the art, the biggest being the work on structural phase transitions, which is being written up into a journal publication. This new method enables structural phase transitions to be studied on a wider range of STEMs and over much larger regions than previously possible. Another aspect is the advanced big data processing functionality for the 4D STEM data delivered in i), which previously did not exist for this type of STEM data.
The big picture impact is the open source software contributions, which plays a small part in enabling fully transparent and open data processing. This addresses a big issue in scientific research: non-reproducible science. As more and more research relies on advanced data processing, being able to inspect the source of the data processing software is vital.
The big picture impact is the open source software contributions, which plays a small part in enabling fully transparent and open data processing. This addresses a big issue in scientific research: non-reproducible science. As more and more research relies on advanced data processing, being able to inspect the source of the data processing software is vital.