MISSION: Psi-k is a Europe-based, worldwide network of researchers working on the advancement of first-principles computational materials science. Its mission is to develop fundamental theory, algorithms, and computer codes in order to understand, predict, and design materials properties and functions. Theoretical condensed matter physics, quantum chemistry, thermodynamics, and statistical mechanics form its scientific core. Applications encompass inorganic, organic and bio-materials, and cover a whole range of diverse scientific, engineering, and industrial endeavours. Key activities of Psi-k are the organization of conferences, workshops, tutorials and training schools as well as the dissemination of scientific thinking in society.
In addition, Psi-k produces a regular newsletter with extensive scientific highlights, and allows researchers to advertise job openings, events, and other topics of mutual interest through its 5000+ members mailing list.
This new website — introduced in 2015 to replace a venerable old site that provided sterling service over many years — offers a much more flexible modern design and functionality and it is to be hoped that it will provide even more stimulus for collaboration and cooperation amongst its members. Instructions regarding how to use it are here.
The Workshop “Theoretical methods in molecular spintronics (TMSpin) was held at the Materials Physics Center of the University of the Basque Country in Donostia-San Sebastian from the 17th to the 20th of September 2018. This workshop welcomed 31 invited speakers and several postgraduate students presenting posters. The event was co-sponsored by Psi-k and the Donostia International Physics Centre (DIPC- http://dipc.ehu.es/).
Molecular spintronics is the study of spin-related phenomena in molecules and atoms and their possible applications for the next generation of data storage and processing devices as well as for the implementation of quantum computers. Electronic structure theory has played a prominent role in molecular spintronics. The comparison of theory and experiments has demonstrated the importance of first-principles calculations, which go beyond model representations of molecular devices as simple “quantum dots” or effective spin Hamiltonians. Nonetheless, standard electronic structure methods based on Density Functional Theory often fail in describing molecular spintronic systems even at a qualitative level. This is because most magnetic phenomena are manifestations of correlation effects, which become extreme at the single molecule scale and which are not captured by standard implementations and approximations of DFT. The goal of TMSpin was to address the question:
“What electronic structure theory to use for molecular spintronics?”
The workshops gathered theoretical physicists and quantum chemists with different areas of expertise. On the one hand there were those researchers that have provided important contributions to the advancement of molecular spintronics since its inception. They were asked to give an overview about the field and moreover to highlight the open questions that to date cannot yet be addressed by theory. On the other hand, the workshop gathered some of the leading researchers in theory and code development, who presented the most recent fundamental and numerical advancements for a number of methods. The organizers promoted an intense discussion to understand whether such methods can be already employed in molecular spintronics. Continue reading Workshop Report: “Theoretical methods in molecular spintronics” (TMSpin)→
Title: Improving the accuracy of ab-initio predictions for materials Location: CECAM-FR-MOSER Webpage with list of participants, schedule and slides of presentations:http://www.cecam.org/workshop-0-1643.html Dates: September 17, 2018 to September 20, 2018 Organizers:Dario Alfè, Michele Casula, David Ceperley, Carlo Pierleoni
State of the art
Improving the accuracy of ab-initio methods for materials means to devise a global strategy which integrates several approaches to provide a robust, controlled and reasonably fast methodology to predict properties of materials from first principle. Kohn-Sham DFT is the present workhorse in the field but its phenomenological character, induced by the approximations in the exchange-correlation functional, limit its transferability and reliability.
A change of paradigm is required to bring the ab-initio methods to a predictive level. The accuracy of XC functional in DFT should be assessed against more fundamental theories and not, as it is often done today, against experiments. This is because the comparison with experiments is often indirect and could be misleading. The emerging more fundamental method for materials is Quantum Monte Carlo because of: 1) its favourable scaling with system size with respect to other Quantum Chemistry methods; 2) its variational character which defines an accuracy scale and allows to progressively improve the results. However QMC being much more demanding in terms of computer resources, and intricate than DFT, a combined approach is still desirable where QMC is used to benchmark DFT approximations for specific systems before performing the production study by DFT.
A different aspect of accuracy is related to size effects: often relevant phenomena occurs at length and time scales beyond the one approachable by first-principle methods. In these cases effective force fields methods can be employed. Machine Learning methods can be used to extract those force fields from training sets provided by ab-initio calculations. Presently DFT-based training sets are used. Improving their accuracy will improve the ultimate accuracy at all scales.
This change of paradigm requires building a community of people with different expertises working in an integrated fashion. This has been the main aim of the workshop.
The following is a partial list of the topics discussed at the workshop, and of their importance to develop the field of computational materials science from first principles.
1) Importance of computational benchmarks to assess the accuracy of different methods and to feed the machine learning and neural network schemes with reliable data;
2) Need of a common database, and need to develop a common language across different codes and different computational approaches;
3) Interesting capabilities for neural network methods to develop new correlated wave functions;
4) Cross-fertilizing combination of computational schemes in a multi-scale environment: from the elemental interactions described at very high-level by expensive approaches to the generation of effective potentials, keeping the accuracy of high-level methods but at much lower cost.
5) Recent progress in quantum Monte Carlo to further improve the accuracy of the calculations by taking alternative routes: transcorrelated Hamiltonians, multideterminantal expansions, pfaffian wave functions. Limitations:
Lack of a common environment where to develop multi-scale approaches for the prediction of material properties. This workshop is one of the first attempts where such needs have been discussed, and possible solutions explored. Open questions:
How to make the codes ready for the next high performance computing (HPC) generation? A fundamental limitation to the future expansion of HPC is the need to reduce energy cost per unit of computation, which requires new technologies. Some of these new technologies are based on accelerators, such as GPU’s, which require in many case a complete rewriting of legacy scientific codes. This is a serious problem for the scientific community, requiring open and frank discussions, including a re-think of work recognition of computer code development as a major scientific endeavour.
How to develop a meaningful materials science database (which gathers both experimental and theoretical results)?
How to develop a common platform to merge different methods in a multi-scale spirit?
The community of computational material science has increased in size tremendously in the past few decades. The drive for this expansion has been the development of ever more friendly computer codes, mainly based on density functional theory (DFT). Indeed, web of science is now reporting tens of thousands of papers per year based on DFT. By contrast, the quantum Monte Carlo (QMC) method, normally much more accurate than DFT, is only published in the hundreds/year, because of its much higher cost and also because of the intricacies of the method that make it more difficult to use. The number of workshops on QMC and the number of schools in which QMC is taught are also only a fraction compared to those on DFT. We believe that the community is now at a turning point where the extra accuracy offered by QMC is not only desirable, but also very much needed if serious progress is to be achieved in the computational design of new materials with bespoke properties. Only a few QMC codes (not even a handful) are currently supported through serious effort, and the community desperately need more formal recognition for code development in order to attract the best people to this endeavour. We are particularly focussing on QMC because we believe that it is the natural method capable of exploiting to the full the forecasted expansion in computer power in the next 10-20 years, but this is also a crucial point in time for this expansion, where new architectures require a complete re-thinking of computational approaches. A series of CECAM workshop may help to draw attention to these points.
Typical funding channels for the activities discussed at the meeting could be the Psi-k community and national funding schemes. In addition, since the ultimate goal of these activities will be to be able to design new materials entirely from first principles, it should be possible to target and persuade specific industries involved in the synthesis of new materials, including for example energy materials such as new batteries and new hydrogen storage materials. Industry funding could be targeted by offering to industry members of staff limited number of spaces to the workshops and requesting a registration fee.
Will these developments bring societal benefits?
The potential benefits of developing and handling computational tools able to predict material properties with a high level of reliability are numerous and of tremendous societal impact. During our workshop, a clearcut example was given by Xenophon Krokidis, who talked about the development of Scienomics, a software used to design and test new compounds in silico. This would allow a company to accelerate the R&D stage of its projects, cut ressources spent for checking the functionalities of a given material, and significantly shorten the “trial and error” time. The budget and time reductions yielded by the usage of a reliable material science software in the R&D is estimated to be of one order of magnitude, according to Krokidis’s experience. This is a huge amount.
Thus, the efforts of bringing together the three different communities (ab initio quantum Monte Carlo, density functional theory, and machine learning) is definitely worth, in the perspective of improving the accuracy of ab initio predictions for materials.
The Department of Chemistry and the Thomas Young Centre at Imperial College London and the Computational Materials Science Group of the Science and Technology Facilities Council (STFC), in collaboration with the Theoretical Chemistry Group of the University of Torino, organised the 2018 MSSC Summer School on the “ab initio modelling of crystalline and defective solids with the CRYSTAL code”.
CRYSTAL is a general-purpose program for the study of periodic solids. It uses a local basis set comprised of Gaussian type functions and can be used to perform calculations at the Hartree-Fock, density functional or global and range-separated hybrid functionals (e.g. B3LYP, HSE06), double hybrid levels of theory. Analytical first derivatives with respect to the nuclear coordinates and cell parameters and analytical derivatives, up to fourth order, with respect to an applied electric field (CPHF/CPKS) are available.
The school provided an overview of the underlying theory and fundamental issues affecting use of the code, with particular emphasis on practical issues in obtaining reliable data efficiently using modern computer hardware. The capabilities of CRYSTAL was illustrated with hands-on tutorials organized in the afternoon sessions.
All information about the school can be found on this website:
The Department of Chemistry and the Thomas Young Centre at Imperial College London and the Computational Materials Science Group of the Science and Technology Facilities Council (STFC), in collaboration with the Theoretical Chemistry Group of the University of Torino, organised the 2017 MSSC Summer School on the “ab initio modelling of crystalline and defective solids with the CRYSTAL code”.
The school provided an overview of the underlying theory and fundamental issues affecting use of the CRYSTAL code, with particular emphasis on practical issues in obtaining reliable data efficiently using modern computer hardware.
The capabilities of CRYSTAL was illustrated with hands-on tutorials organized in the afternoon sessions.
All information about the school can be found on this website:
Hotel Jäger von Fall, Lenggries, Bavaria, Germany
Organizers: Harald Oberhofer, Johannes Margraf
Multi-scale simulation approaches rely on a hierarchy of increasingly accurate and highly resolved methods to capture the different time- and length-scales relevant to a process of
interest. Traditionally, this might involve coupling classical molecular dynamics with electronic structure calculations (QM/MM), or embedding a quantum mechanical system in a point charge
or continuum environment. In this context, the models comprising the individual layers of the multi-scale hierarchy are often unrelated. For instance, the empirical potential and DFT method in a QM/MM simulation are independently defined at the beginning of the simulation. Enormous advances in electronic structure algorithms and hardware now allow first principles calculations to be carried out on a truly massive scale. This leads to a novel perspective of multi-scale models: electronic structure data can be generated with high enough quality and quantity to allow the application of coarse graining and machine learning techniques. Instead of defining
separate physical models at different scales, the electronic structure method directly informs the next layer of the multi-scale hierarchy. The goal of this workshop was to bridge the gap between
traditional, layered multi-scale techniques and the more direct coarse graining and machine learning approaches to the simulation of extended systems, thereby bringing together researchers working on QM/MM or other embedding techniques with those who apply coarse graining and interpolation to electronic structure data in different contexts (e.g. potential energy surfaces, electronic properties, charge transport, rate constants in catalysis) and with different methods (neural networks, Gaussian process regression, kernel ridge regression, splining, etc).
Organisers: Michele Ceriotti, Tom Markland, Jeremy Richardson and Mariana Rossi
Dates: 25 -29 June, 2018
We convened a School on Path Integral Quantum Mechanics at the CECAM headquarters in Lausanne, Switzerland. The school gathered together 17 speakers (11 invited and 6 contributed) and 46 participants affiliated with 15 different countries. We
received a total of 85 applications to attend the school and unfortunately could not accept more participants due to space constraints in the lecture room. This amount of applications, only two years after we had the last school on the same topic, underlines
the growth of the community performing research on the theory and practice of Path Integral (PI) techniques for the atomic-scale modelling of the quantum behavior of materials and molecules.
As in the last school, we explicitly asked the speakers to prepare pedagogic talks aimed at introducing the participants to the methods and simulation techniques to treat imaginary and real time path integrals, for both adiabatic and non-adiabatic dynamics.
Invited and contributed speakers were encouraged to give lectures that explained the methods in great detail, so that the students could benefit the most from the school, even if this was their first contact with path integral methods.
July, 11-13th 2018, Graz University of Technology, Petersgasse 16, 8010 Graz, Austria
In the second week of July, the workshop Interfacing Machine Learning and Experimental Methods for Surface Structures (IMPRESS) was held at the TU Graz. The advent of machine learning methods has drastically changed the way structure determination is performed, since it facilitates the rational design of (new) experiments and the analysis of large amounts of data. The target of the workshop was to bring experimentalists and theorists together, so that both can learn and benefit from each other’s expertise. About 50 scientists from Asia, America, and Europe followed the call, making the workshop, which was sponsored by CECAM and the Psi-k, a great success.
The participants gathered at the Insitute of Solid State Physikcs for morning coffee at 9am on every morning of the event. On Wednesday (Juny 11), Oliver Hofmann from TU Graz welcomed everyone and introduced the daily format of interchanging invited talk, contributed talk and discussion sessions.
After Alexander Hinderhofer (Univ. Tübingen) opened the event with a talk on monitoring growth of thin films experimentally, Chiara Panosetti (TU Munich) and Katrin Forster-Tonigold presented „tradiational“ approaches to computationally find surface or interface geometries. After the coffe break, Milica Torodović (Aalto) and Andreas Jeindl (TU Graz) introduced their respective machine learning approaches for surface structure search.
Conversations continued over lunch and through the 2h discussion session. The last session of Wednesday addressed kinetics at the interface: Peter Zeppenfeld (JKU Linz) discussed thermodynamics and the importance of transition states for the dynamics of polymorph formation. Afterwards, Daniel Packwood (Kyoto University) introduced an Bayes‘ Learning approach to obtain the parameters necessary for kinetic Monte-Carlo simulation. The last talk of that day was given by Roland Resel (TU Graz), who presented x-ray diffraction results to follow the polymorphism of thin films experimentally. The programme ended with a busy poster session, where diverse new structure search techniques were discussed over wine, beer, and local pastries.
On Thursday (July 12) the invited talks focused on interfaces and boundaries with Torsten Fritz (Univ. Jena), Tim Frolov (LLNW) and Antti Karttunen (Aalto). The topic continued in the contributed session, with, Julian Pilz (TU Graz) presenting experimental challenges in substrate and parameter control, and Benedikt Hartl (TU Vienna) providing an overview over the problems at interfaces under electrochemical control. After another intense 2h discussion session, three more invited talks highlighted the challenge of structure-to-structure relationships, with experimental viewpoints presented by Daniel Wegner (The Netherlands) and Takanori Fukushima (Tokio Institute of Technology) and the computational counterpart by Talat Rahman (Univ. Florida). In the evening, the workshop participants met for the conference dinner at the Hotel Weitzer, where local Austrian food was served.
The closing invited talk of the workshop on Friday, July 13, was given by Bernd Meyer (FAU Erlangen-Nürnberg) with recent advances in methodology to predict the structure at solid/liquid interfaces. After another round of discussion sessions, the workshop was closed with contributed talks by Turner and Hinuma. The workshop was closed closed at midday by Milica Todorović with a summary oft he topics discussed and the topics still open.
Financial support from Psi-K and CECAM allowed us to bring together almost 50 participants from three continents (Europe, North Amerika, and Asia). It enabled us to keep the event free of registration costs to encourage the participation of younger researchers.
Despite the recent breathtaking advances in both computational and experimental methods, there is still a notable lack of understanding what the respecitvie communities can do for each other. Each day, the participants gathered in a large meeting room to brainstorm and exchange ideas, concepts, and problems. The panel at each table was hosted by an invited speaker on a key topic of their own choice: these were advertised in advance to allow participants to join several panels. Fresh fruit, coffee and sweets were served throughout. All participants contributed thoughts and conclusions to the online questionnaire tool (Presemo) for each discussion table.
The online tool allowed us to summarise the conclusion from the discussion sessions. One of the main outcomes was, perhaps, that machine learning has contributed a lot to copmutational methods, but has not fully arrived at experimental tools, where it would have the potential to speed up, and better plan, measurement campaings. A further concern raised multiple times throughout the discussions was whether – or to what extend – machine learning is merely a correlation analysis, or can provided true scientific insight.
October 8, 2018 to October 12, 2018
Location: CECAM-HQ-EPFL, Lausanne.
The aim of the school was to give a deep introduction on the theoretical and practical aspects of the electronic excitations, which are probed by experimental techniques such as optical absorption, EELS and photo-emission (direct or inverse). From the theory point of view, excitations and excited state properties are out of the reach of density-functional theory (DFT), which is a ground-state theory. In the last thirty years, other ab-initio theories and frameworks, which are able to describe electronic excitations and spectroscopy, have become more and more used: time-dependent density-functional theory (TDDFT) and many-body perturbation theory (MBPT) or Green’s function theory (GW approximation and Bethe-Salpeter equation BSE). In fact, computational solutions and codes have been developed in order to implement these theories and to provide tools to calculate excited state properties. The present school focused on these points, covering theoretical, practical, and also numerical aspects of TDDFT and MBPT, non-linear reponse and real-time spectroscopies. Finally, a large part of the school was devoted to the codes implementing such theories (ABINIT, 2Light, Lumen, DP, EXC).
The 23rd ETSF Workshop on Electronic Excitations Interdisciplinary views on quantum many-body theory
The University of Milan, Italy, September 10 – 14, 2018
The 2018 edition of the European Theoretical Spectroscopy Facility (ETSF) Workshop on Electronic Excitations has been dedicated at fostering the cross-fertilization between different approaches to many-body phenomena, transcending the traditional barriers between disciplines. The workshop therefore brought together experts facing similar problems from different perspectives, for different applications, and often with a different language. Besides discussing application of many-body theories to excitations in condensed matter, i.e. the traditional field of expertise of ETSF, topics covered by the workshop included nuclear physics, quantum chemistry, ultrafast excitation dynamics, quantum transport, topological insulators and novel algorithmic approaches to many-body problems inspired by machine learning and data science.
Many of you will have heard by now the tragic news that our dearest friend and colleague Alessandro De Vita passed away on Tuesday afternoon. Sandro was killed in a motorbike accident while going to the airport. Commuting between Trieste and London, two most beloved cities for him, was part of his life – a life that he lived so fully.
We have received an outpouring of grief in the last two days that is a testament to how much loved he was, and how strong was his impact in the life of the people that met him – his sharp intelligence, his infinite knowledge, his surprising imagination, his unbridled talk, his mischievous and deeply generous spirit all stood out. And most of all, his passions in life – the friends, the science, the music, the poetry.
Psi-k and CECAM, to which Sandro gave so much, will think of public ways to celebrate him, and any suggestion would be most welcome. If you wanted to dedicate some of your thoughts to him, he would have had a few suggestions himself. Light a candle, somewhere. Say a prayer. Listen to Glenn Gould play the 25th Goldberg variation – he always said that it contained all the sorrow of the world.
We are all with you, Sandro – with Christine, with your family, with your friends.