The NCD-SWEET beamline aims to face a new challenging project at the ALBA Synchrotron light source: X-ray diffraction during ultrafast growth of high temperature superconductors. In collaboration with the Superconducting Materials and Large Scale Nanostructures (SUMAN) Group at ICMAB.
The project duration is two years with possibilities of extension. Candidates should send their CV and reference letters to: hr_suman@icmab.es. The recruitment process will be closed when a suitable candidate is found. Incorporation will be in less than 2 months after candidate selection. Salary will be commensurate with qualifications and experience.
The project aims to automate a new XRD in-situ installation to be built at the NCD-SWEET beamline of ALBA light source (Cerdanyola del Valles, Barcelona) and develop routines for image data query/retrieve/storage/analysis. The installation will monitor ultrafast (~100 ms/frame) crystallization processes during fast heating ramps with a fast 2D XRD image detector. The system will be also equipped with a residual gas analysis mass spectrometer and an in-situ conductivity measurement. The samples to be analysed are high temperature superconducting films for the energy transition, though the installation should be open to other materials. The project will also explore the in-situ growth of combinatorial samples with compositional gradients for their evaluation using machine learning algorithms. Therefore, large amounts of data will have to be managed.
The research work will be developed at the ALBA premises and the successful candidate will become a beamline support engineer. They will collaborate with the control group of the ALBA Computing Division in the activities related to control, software development and automation of beamline instrumentation and procedures specially related to this project. Salary will be negotiated according to the experience of the candidate.
The project aims to engage a talented engineer with experience in software development and image data management, with high skills in python programing and equipment automation. Interest in machine learning algorithms is welcome. He/she will be the Image Data and Automation Manager.
Experienced engineer with a degree in computer science, telecommunications, image big data analysis or equivalent.
The project consists of designing, building, commissioning and exploiting a new experimental set up devoted to fast thin film growth while acquiring simultaneously diffraction data. It will operate at the NCD-SWEET beamline of ALBA light source (Cerdanyola del Valles, Barcelona). The installation should enable to evaluate ultrafast (~100 ms/frame) crystallization processes during heating ramps of few degrees per second under controlled and reduced atmospheres with a fast 2D XRD detector in a 3 axis goniometer equipped with an XZ stage. The system will be also equipped with a residual gas analysis mass spectrometer and an in-situ conductivity measurement. The samples to be analysed are high temperature superconducting films deposited by chemical solution deposition and grown through the high throughput Transient Liquid Assisted Growth (TLAG) process [1] for the energy transition, though the installation should be open to other materials interests. The project will also explore the in-situ growth combinatorial experiments with compositional gradients deposited by inkjet printing [2], for their evaluation using machine learning algorithms.
The research work will be carried out at Alba premises and the successful candidate will become a beamline researcher of NCD-SWEET beamline. They will also participate in the activities of maintenance and upgrade of the beamline instrumentation and will have access to additional in-house beam time allocated to the project described above.
The project aims to engage a skilled researcher with experience in synchrotron hard X-ray diffraction and/or surfaces scattering (GIWAXS) with interest in in-situ fast acquisition processes and evaluation of combinatorial samples. They will be the Experiment Operator.
[1] Nature Communications, 11, 344 (2020) (doi.org/10.1038/s41467-019-13791-1)
[2] ACS Appl. Mater. Interfaces 2021, 13, 9101−9112 (doi/10.1021/acsami.0c18014)
Experienced researcher with PhD in chemistry, material science or physics.
Prof. Teresa Puig
Institut de Ciència de Materials de Barcelona, CSIC
Campus UAB, Bellaterra, Spain
teresa.puig@icmab.es
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