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We just had a great 2-day workshop on the Vienna Ab-initio Simulation Package (VASP) organized by the KAUST Research Computing from May 10 to 11, 2016. The workshop featured a combination of lectures and hands-on tutorials by Dr. Martijn Marsman (who is one of the main developers of the VASP) from the VASP team in Vienna. This was not an introductory workshop, it focused more on the advanced features of the VASP, such as the hybrid functionals, linear response, GW, BSE, and ACFDT (RPA). At KAUST, there are three research groups that use the VASP heavily: Computational Physics and Materials Science (CPMS) group, Solar & Photovoltaics Engineering Research Center (SPERC), and KAUST Catalysis Center (KCC). Among these groups, I think we at CPMS use the VASP the most, with 24 seats.

 

Similarly, last year we had a 2-day workshop on VASP and MedeA® modeling suite, from March 11 to 12, 2015. The speakers were Christan Minot (professor of Chemistry at Université Pierre et Marie Curie, Paris VI), Walter Wolf, René Windiks and Alexander Mavromaras from Materials Design, Inc. The first day of the workshop introduced pretty much everything about the fundamentals of the VASP. The second day was focused primarily on the hands-on tutorials with the MedeA® modeling suite and integrated codes such as structure databases, graphical building and analysis tools and the integrated use of solvers such as VASP-TTS, LAMMPS (molecular dynamics), GIBBS (Monte Carlo) and MOPAC. Participants were be able to interact with MedeA on dedicated workstations and worked on explicit application examples with support from Materials Design staff.

 

The Vienna Ab initio Simulation Package (VASP) is a computer program for atomic scale materials modeling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics, from first principles. VASP computes an approximate solution to the many-body Schrödinger equation, either within density functional theory (DFT), solving the Kohn-Sham equations, or within the Hartree-Fock (HF) approximation, solving the Roothaan equations. Hybrid functionals that mix the Hartree-Fock approach with density functional theory are implemented as well. Furthermore, Green’s functions methods (GW quasiparticles, and ACFDT-RPA) and many-body perturbation theory (2nd-order Møller-Plesset) are available in VASP.

Few years ago I switched from SVN (Subversion) to Git and haven’t looked back. Git is a free and open source distributed version control system that is widely used for software development and any other version control tasks. Git is known for its speed, efficiency, reliability, and non-linear development model. Git has become one of the most popular version control systems in use among open-source developers, which makes it a necessary tool for professional programmers, freelance coders, and computational scientists. I have used Git both for my scientific research (Python, Bash, Fortran) and personal (CSS and PHP) scripting purposes. For example, last week this website crashed due to a CSS style sheet problem and thanks to Git I was instantly able to retrieve the previous version of the CSS file.

 

GitHub is the largest Git repository hosting service which provides a web-based graphical interface and desktop app. It is the central hub of collaboration for millions of small and large projects and developers. It offers all of the distributed revision control and source code management functionality of Git as well as adding its own fantastic features. If you use Git, utilizing GitHub is pretty much unavoidable. Although I use mostly command line Git, GitHub’s feature-rich web interface and the Desktop app can make your Git life easier.

 

Below, I list few resources for those who want to start using Git and GitHub.

 

Notable mentions:
  • BitBucket – Another alternative to GitHub
  • Atom – my favorite modern and hackable text editor
  • Gitignore.io  – create useful .gitignore files for your project

Python is a powerful general-purpose, object-oriented language. It is an easy to learn language which is used for pretty much anything (games, web development, applications, data analysis, and academic research). Although most scientists use Fortran or C, I think the current generation is leaning towards using Python.

 

Personally, the best way to learn Python is to start using it for a project or try to solve a problem with it or if you have a code written in some other language try to do it in Python. However, you have to start by learning the grammar (the syntax) and the basics first. There are so many resources around (it can be even hard to decide where to start). Here I list few resources to jump start your programming journey with Python.
  1. Take the Python Class from Codecademy  – basic syntax
  2. Take the Google’s Python Class
  3. Learn Python the Hard Way – a free book with lots of Python concepts
  4. The Python Tutorial
  5. LearnPython.org

 

There are several excellent Python IDEs. Here are the ones I used and liked:
  • Spyder (use it with Anaconda) –  my favorite
    Anaconda is a completely free Python distribution. It includes the most popular Python packages  such as NumPy, Pandas, SciPy, Matplotlib, and IPython. I find these packages to be very useful for analyzing and visualizing our research data.
  • Jupyter
  • PyCharm
  • Emacs

I recently attended the Solar Future 2015 symposium organized by KAUST from November 7 to 11. Solar Future 2015 is KAUST’s scientific and technology symposium on solar energy. This event gathered international experts from the academic and industrial communities to share their vision for the energy sector and their most recent results in the field of solar energy conversion.

Three days with keynote presentations and networking opportunities made this symposium an exclusive event with worldwide impact. About twenty institutions from Europe, USA, and Asia were represented, including US national laboratories (NREL, LANL), and universities (including Stanford, Princeton, EPFL), with core competencies in energy and solar photovoltaics (PV). For the first time in this series of symposia, Solar Future 2015 combined both emerging and mature technologies to pave the way towards the future of solar energy, at high efficiency and low cost.

 

One of my current projects deals with first-principles investigations of hybrid organic-inorganic perovskite solar cells, thus the most interesting talks for me were related to this rapidly emerging field. Dr. Leijtens Tomas from Stanford University gave a talk titled “Towards Stable & Efficient Hybrid Tandem Solar Cells Using Metal Halide Perovskites” where he highlighted recent developments in understanding and overcoming stability concerns of metal halide perovskite solar cells. Also, Dr. Sam Stranks from MIT talked about “The Photophysics of Perovskites Solar Cells” and provided useful insight towards the optoelectronic behavior of these materials and their operation, including charge carrier diffusion and recombination mechanisms, as well as ion migration and its potential impact on device performance and hysteresis.

I have just returned from attending the Ψk-2015 Conference and it was a blast. Every five years this conference brings together the global community that is active in the science of electronic structure and properties of condensed matter. The conference covers both the fundamental and theoretical aspects of electronic structure calculations, computational methods and tools. The application areas of electronic property calculations range from condensed matter and materials physics to nanoscience, the design and discovery of novel materials, their properties, and their performance in devices. The Ψk-2015 conference took place in San Sebastian, Spain, from September 6 to 10.  The conference program was structured around plenary sessions, symposia and topical sessions. There were around 30 symposia with 160 invited speakers and more than 1200 participants.

 

Following were my focus sessions:

  • Hybrid Photovoltaic Materials
  • Transport Properties
  • Materials Design
  • Modeling of Defect Levels
  • GW and BSE
  • Novel 2D Materials and Heterostructures
  • Machine Learning Methods in Materials Modeling
  • Spin-Orbit Coupling Effects in First-Principles Quantum Transport

 

My contribution was about our recent work Mechanism of H2O induced conductance changes in AuCl4 functionalized CNTs”. The plenary sessions by Prof. Giulia Galli (U. Chicago), Prof. Georg Kresse (U. Vienna), and Prof. Steve Louie (UC Berkeley) were really motivating, interesting, and full of new insights. Here are some additional talks which I noted down as very useful for my research interests:

  • Dr. Kristin Persson: The Materials Project: Accelerated Materials Design in the Information Age
  • Dr. Andrew M. Rappe: Shift Current and Ferroelectric Domain Walls in Organometal Halide Perovskites
  • Dr. Boris Kozinsky: Design and screening of ionic and electronic conductors for energy application
  • Dr. Chris Wolverton: Materials Genome Approach to Computational Design of Thermoelectrics
  • Dr. Heather Kulik: Challenges and advances for accurate large-scale electronic structure and dynamics
  • Dr. Jeffrey  Neaton: Tunneling and Diffusive Charge Transport at the Nanoscale from First Principles
  • Dr. Marco Bernardi: Ultrafast Hot Carrier Dynamics in Materials from Ab Initio Calculations
  • Dr. Colin Van Dyck: Molecular Rectifiers: A new design based on asymmetric anchoring moieties
  • Dr. Giovanni Vignale: Time-dependent thermoelectric transport at the nanoscale
  • Dr. Daniel Berger: The QM/MM embedded cluster approach: exploiting locality effectively
  • Dr. Oleg Prezhdo: Excited State Dynamics in Nanoscale Materials: A Time-Domain Ab Initio Perspective
  • Dr. Berend Smit: The Nanoporous Materials Genome in Action
  • Dr. Mei-Yin Chou: Interplay of Charge and Lattice Distortion in Transition Metal Dichalcogenides
  • Dr. Annabella Selloni: Electrons and holes at the TiO2 – water interface
  • Dr. Robert DiStasio: The Microscopic Structure and Local Environment of Liquid Water
Interestingly, I got the impression that the next Ψk-2020 will have more sessions related to Data Mining and Machine Learning as essential tools for the next-generation Materials Design and Modeling.

I enjoyed Dr. Kristin Persson’s talk on The Materials Project: Accelerated Materials Design in the Information Age at Psi-k 2015 Conference. As she said: “The Materials Project – part of the broader Materials Genome Initiative – is an effort to compute the properties of all known inorganic materials and beyond, and offer that data to the community together with online analysis and design algorithms. The current release contains data derived from density functional theory calculations for over 60,000 materials, each with searchable associated properties such as relaxed structure, electronic state, energy storage capability, aqueous and solid stability, and more.”

 

I knew about the Materials Project back in 2012. During my Ph.D. study I had to spend several weeks to calculate and estimate the stable phase diagrams of complex oxides such as InGaZnO4 by writing my own code with MATLAB but thanks to the Materials Project nowadays one can do it in a very short time. This already shows why I am a big fan of the Materials Project.

Dr. Kristin Persson and Prof. Gerbrand Ceder have put tremendous effort into this project. Also, I think the primary engines powering the Materials Project are made possible by Dr. Shyue Ping Ong (Pymatgen, Custodian) and Dr. Anubhav Jain (FireWorks). I find the Pymatgen, Custodian, and Fireworks to be a mixture of smart, creative, and productive tools suitable for any computational materials scientist out there (including myself, as evidenced by my research theme). I believe the Materials Project will benefit greatly from the advancement of Big Data and Machine Learning.

I had the privilege to attend a workshop about our new high-performance supercomputer Shaheen-II at KAUST.
In May 2015, KAUST acquired and installed a new Cray XC40 supercomputer: Shaheen II. This machine delivers 25 times the sustained computing capability of KAUST’s current system (Shaheen I, IBM BG/P). Shaheen II, with a theoretical peak performance of 7.2 PFLOP/s, is composed of 6,174 dual sockets compute nodes based on 16 cores Intel Haswell processors running at 2.3GHz representing a total of 197,568 cores. The processors are tightly integrated with a richly layered memory hierarchy and dragonfly interconnection network with a total storage space in the parallel file system of 17 PB. The homogenous design of Shaheen II Cray XC40 with only Haswell makes it suitable for most, if not all, of KAUST applications.
The workshop was targeted to any potential Shaheen II users looking forward to port and run their codes in the new system.

It is not easy for Scientists to identify the transferable skills that they have acquired during their academic journey because some “soft skills” are obvious but some are hard to spot.
Here is a good list of transferable skills that most PhDs are equipped with (at least I believe I have them).
Analysis & Problem-Solving
  • Define a problem and identify possible causes
  • Comprehend large amounts of information
  • Form and defend independent conclusions
  • Design an experiment, plan, or model that defines a problem, tests potential resolutions and implements a solution
Interpersonal & Leadership Skills
  • Facilitate group discussions or conduct meetings
  • Motivate others to complete projects (group or individual)
  • Respond appropriately to positive or negative feedback
  • Effectively mentor subordinates and/or peers
  • Collaborate on projects
  • Teach skills or concepts to others
  • Navigate complex bureaucratic environments
Project Management & Organization
  • Manage a project or projects from beginning to end
  • Identify goals and/or tasks to be accomplished and a realistic timeline for completion
  • Prioritize tasks while anticipating potential problems
  • Maintain flexibility in the face of changing circumstances
Research & Information Management
  • Identify sources of information applicable to a given problem
  • Understand and synthesize large quantities of data
  • Design and analyze surveys
  • Develop organizing principles to effectively sort and evaluate data
Self-Management & Work Habits
  • Work effectively under pressure and to meet deadlines
  • Comprehend new material and subject matter quickly
  • Work effectively with limited supervision
Written & Oral Communication
  • Prepare concise and logically-written materials
  • Organize and communicate ideas effectively in oral presentations to small and large groups
  • Write at all levels — brief abstract to book-length manuscript
  • Debate issues in a collegial manner and participate in group discussions
  • Use logical argument to persuade others
  • Explain complex or difficult concepts in basic terms and language
  • Write effective grant proposals

I attended an intensive Quantum ESPRESSO hands-on tutorial/training between January 17 and 21 in ICTP Trieste, Italy. This was part of the 15thInternational Workshop on Computational Physics and Materials Science: Total Energy and Force Methods  (January 13-15, 2011). The workshop was mainly devoted to recent advances in computational condensed matter physics and materials science, based on realistic calculations of the electronic structure of complex systems.
I was awarded a competitive travel grant from the Materials Computation Center at the University of Illinois at Urbana-Champaign to attend this workshop. The workshop presentations covered a number of theories and methods, such as Density-Functional Theory, Ab-initio Molecular Dynamics, and electronic transport. In particular, I benefitted tremendously from the Quantum ESPRESSO hands-on training.
Quantum ESPRESSO is an integrated suite of Open-Source computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. Here are some of the things that Quantum ESPRESSO can do:
  • Ground-state calculations
  • Structural Optimization
  • Transition states and minimum energy paths (NEB etc)
  • Ab-initio molecular dynamics (CPMD, BOMD)
  • Response properties (DFPT)
  • Spectroscopic properties
  • Quantum Transport (Ballistic, Coherent etc)