CECAM
Fostering computational science for societal progress
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Datasets
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Role of computational methods in the era of precision medicine
Computational drug discovery has become an increasingly important tool in the search for new drugs to treat a wide range of diseases. One of the critical challenges in this field is simulating the complex behavior of biomolecules at the atomic level, which can be computationally very expensive and time-consuming. The thermodynamics and kinetics of drug-target binding play a crucial role in understanding and optimizing the interactions between drugs and their target molecules. To address this challenge, molecular dynamics (MD) and related approaches combined with machine learning and artificial intelligence play a crucial role in accelerating the exploration of the conformational space of molecules. These methods also enable researchers to compute the free energy differences between different states of a molecule and estimate thermodynamic and kinetics properties such as binding free energies and residence time. This talk overviews various enhanced sampling methods combined with machine learning in computational drug discovery, as well as their advantages and limitations. The talk focuses on using these methods for free energy and kinetics estimations, reporting on the significant limitations toward accurate estimations for large datasets of compounds. The talk then describes recent applications in drug discovery and discusses the challenges and limitations of these methodologies when applied to biological systems of increasing complexity. In conclusion, the talk illustrates how MD, enhanced sampling methods, and machine learning can improve the efficiency and effectiveness of computational drug discovery and accelerate the development of new therapeutics to treat significant unmet medical needs in the era of precision medicine.
Data generation and uncertainty quantification for universal graph deep learning interatomic potentials
One of the most exciting developments in recent years is the development of graph deep learning interatomic potentials such as the Materials 3-Body Graph Network (M3GNet), that have near-universal coverage across the entire periodic table. Such universal interatomic potentials (UIPs) have broad applications in the dynamic simulations and discovery of materials. However, current UIPs are still hampered by the lack of accurate potential energy surface (PES) data. In this talk, I will discuss these limitations and how advanced sampling approaches based M3GNet latent structural features can be used to generate high-quality PES data in an efficient manner. In addition, I will show that these approaches can also be used to quantify the uncertainty of a UIP for a structure. I will conclude with some observations on the relative performance of invariant versus equivariant UIP architectures, and a perspective on the challenges involved in UIPs with additional physics such as charges and magnetism.
Opportunities with the European spallation source: Leveraging data flows and simulations
The European Spallation Source (ESS) aims to become the world's leading neutron source. Emphasizing the crucial role of scientific computing from its inception, ESS prioritizes software, hardware, simulations, and data management to increase the impact from research with neutron scattering at ESS. This presentation introduces ESS and its data pipeline, highlighting the potential for the electronic structure simulation community to benefit from and contribute to ESS's scientific endeavors. Over recent decades, the integration of electronic structure simulations with neutron scattering has grown steadily, enhancing experimental data interpretation. Utilizing ray-tracing simulation programs like McStas allows for precise comparison between simulated and experimental data in a like-to-like manner, facilitating a 'digital twin' approach that includes experimental artifacts. The presentation will feature exemples and address associated challenges.
Performing large-scale quantum molecular dynamics simulations
In this talk I will discuss techniques and workflows targeted at the simulation of molecular dynamics protocols based on ab initio calculations, machine-learned (ML) potentials of ab initio quality and including quantum nature of the nuclei. I will discuss aspects of electronic-structure code efficiency in HPC architectures to generate data in order to train ML models and recent improvements in the i-PI code which decrease communication overhead when running over many HPC nodes, allowing to reach nanoseconds of molecular dynamics simulation per day with ML potentials.
Training physics and uncertainty-aware ML-models on data from DFT and large-scale facilities
Understanding the dynamic processes at solid-liquid interfaces in electrochemical devices like batteries is key to developing more efficient and durable technologies for the green transition. Fundamental and performance-limiting interfacial processes like the formation of the Solid-Electrolyte Interphase (SEI) [1] spans numerous time- and length scales. Despite decades of research, the fundamental understanding of structure-property relations remains elusive. Ab initio molecular dynamics (AIMD) generally provides sufficient accuracy to describe chemical reactions and the making and breaking of chemical bonds at these interfaces [3]. Still, the cost is prohibitively high to reach sufficiently long time- and length scales to ensure proper statistical sampling [4]. Machine learning (ML) potentials offer a potential solution to this challenge. Still, training ML-based potentials capable of handling activated processes in organic or aqueous electrolytes remains a fundamental challenge since the potential must capture both intra- and intermolecular interactions in the electrolyte and during chemical reactions at the interface [4]. Here, we present new approaches using foundation models [5], graph neural networks [6] and new transition state training sets [7] for chemical reaction networks, and machine/deep learning models to predict the spatio-temporal evolution of electrochemical interphases [3]. We also discuss the development of active learning methods to accelerate segmentation of microstructures in non-destructive 3D imaging techniques, such as X-ray nano-holo-tomography, and enable the visualization of battery electrodes. Finally, we discuss how such models trained on multi-sourced and multi-fidelity data from multiscale computer simulations, operando characterization, high-throughput synthesis, and testing, to provide uncertainty-aware and explainable ML for early prediction of patterns from chemical spectra (Figure 1) [8].
Ada Lovelace Centre - Integrating modelling and simulation at large facilities
The Ada Lovelace Centre (ALC) is a center of expertise for scientific computing within STFC with the primary objective of maximizing the scientific impact of the STFC large scale national facilities, Diamond, ISIS and the Central Laser Facility.
The ALC is seeking to cultivate integrated approaches to address and solve the scientific data challenges experienced by facilities and their users. In early discussions with the facilities, the integration of theory with experiments, the provision of theory as a service, and linking users to modelling and simulation experts were highlighted as priorities. Here we will discuss the ALC and efforts to shape a program to meet the modelling and simulation needs of the facilities.
Develop and engage: Sustainable software tools for large-scale facilities using the galaxy platform
In this talk, I will present the method for developing sustainable software tools, and engaging user communities, that is currently being implemented by members of the Scientific Computing Department (SCD) of the Rutherford Appleton National Laboratory, at the Science and Technologies Facilities Council of the UK.
At present, the method comprises two strands: a) development of theoretical models and sustainable tools for the interpretation of muon experiments; and b) management of the computational workflows associated with the processing, and interpretation, of muon and x-ray absorption spectroscopy (XAS) experiments performed at the lab.
Data-driven X-ray absorption spectral analysis at user facilities
X-ray absorption spectroscopy is a premier element-specific experimental technique for materials characterization. Specifically, X-ray absorption near edge structure (XANES) encodes rich local structural and chemical information around absorber sites, making it a powerful tool for probing physical and chemical processes at large synchrotron facilities. However, the correlation between XANES spectral features and the underlying local structural motifs or electronic descriptors is obscure. Recent progress in materials discovery using smart automation and in situ / operando experiments underscores emerging challenges and opportunities of spectral analysis in real time. This challenge cannot be tackled by empirical fingerprints, which have practical limitations on data availability and diversity, or first-principles simulations due to the high computational cost. Here I discuss the recent progress of the data-driven spectral analysis pipeline by combining first-principles theory, data analytics tools and software development to decipher the structure-spectrum relationship. I highlight the utility of key modules of this pipeline, including 1) Benchmark modules that quantify the effects of key approximations and implementations in different computational methods or codes; 2) Workflow modules that aim to lower the barrier for non-expert practitioners by providing appropriate calculation input parameters based on systematic benchmarks; 3) Database modules that provide FAIR spectral datasets; 4) Machine learning modules that accelerate spectral simulation and extract physical descriptors from spectra.
What is the influence of the band structure on the dielectric function?
In this talk, I will introduce various analytical approaches used in the literature to compute the dielectric function. These methods are based on the homogeneous electron gas/liquid. Our ultimate goal is to describe properly the plasmon peak in core level spectroscopies and model its variations as a function of the outgoing angle. For this, we need a good description of the dielectric function both in frequency AND momentum, and especially along the plasmon dispersion. I will show that most, if not all, the methods developed in the literature can be seen as particular cases of the memory function scheme, which will be explicated. In order to assess the validity of this approach for our goal, I will then compare our results based on the homogeneous electron gas with ab initio calculations (i.e. taking fully into account the band structure). This comparison will be made for a metal with a simple band structure, Al and for a semiconductor GaN.
Collections
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Series on High Performance Computing
The relevance and impact of High Performance Computing (HPC) on simulation and modeling can be quite different depending on the specific area, but we are all confronted with the relationship between new methods and algorithms and their implementation in proficient codes. We invite you to join us in an exploration of the relevance of HPC as an enabler of leading-edge simulation and modeling.[order][{"id":"656d9ff2e4b0c3a3247cf9c1","name":"June 18 2020","description":"The relevance and impact of High Performance Computing (HPC) on simulation and modeling can be quite different depending on the specific area, but we are all confronted with the relationship between new methods and algorithms and their implementation in proficient codes. We invite you to join us in an exploration of the relevance of HPC as an enabler of leading-edge simulation and modeling. The focus of this webinar series will be on the science made possible by combining state-of-the-art methods with optimal exploitation of supercomputing resources.","created":"Mon Dec 04 09:46:26 UTC 2023","thumbnail":"656da7a8e4b0c3a3247cfa9f","authorId":"649ad15af7aa6e15fad92ed5","spaces":["5a79b568e4b05cb28bae3f60"],"resource_type":"dataset"},{"id":"656da01de4b0c3a3247cf9ca","name":"June 25 2020","description":"The relevance and impact of High Performance Computing (HPC) on simulation and modeling can be quite different depending on the specific area, but we are all confronted with the relationship between new methods and algorithms and their implementation in proficient codes. We invite you to join us in an exploration of the relevance of HPC as an enabler of leading-edge simulation and modeling. The focus of this webinar series will be on the science made possible by combining state-of-the-art methods with optimal exploitation of supercomputing resources. Link to CECAM webinars","created":"Mon Dec 04 09:47:09 UTC 2023","thumbnail":"656daf16e4b0c3a3247cfc6e","authorId":"649ad15af7aa6e15fad92ed5","spaces":["5a79b568e4b05cb28bae3f60"],"resource_type":"dataset"},{"id":"656da030e4b0c3a3247cf9de","name":"July 2 2020","description":"The relevance and impact of High Performance Computing (HPC) on simulation and modeling can be quite different depending on the specific area, but we are all confronted with the relationship between new methods and algorithms and their implementation in proficient codes. We invite you to join us in an exploration of the relevance of HPC as an enabler of leading-edge simulation and modeling. The focus of this webinar series will be on the science made possible by combining state-of-the-art methods with optimal exploitation of supercomputing resources.","created":"Mon Dec 04 09:47:28 UTC 2023","thumbnail":"656db619e4b0c3a3247cfe0f","authorId":"649ad15af7aa6e15fad92ed5","spaces":["5a79b568e4b05cb28bae3f60"],"resource_type":"dataset"},{"id":"656da044e4b0c3a3247cf9e9","name":"July 9 2020","description":"The relevance and impact of High Performance Computing (HPC) on simulation and modeling can be quite different depending on the specific area, but we are all confronted with the relationship between new methods and algorithms and their implementation in proficient codes. We invite you to join us in an exploration of the relevance of HPC as an enabler of leading-edge simulation and modeling. The focus of this webinar series will be on the science made possible by combining state-of-the-art methods with optimal exploitation of supercomputing resources","created":"Mon Dec 04 09:47:48 UTC 2023","thumbnail":"656dbc13e4b0c3a3247cffa5","authorId":"649ad15af7aa6e15fad92ed5","spaces":["5a79b568e4b05cb28bae3f60"],"resource_type":"dataset"},{"id":"656da05ee4b0c3a3247cf9f4","name":"July 16 2020","description":"The relevance and impact of High Performance Computing (HPC) on simulation and modeling can be quite different depending on the specific area, but we are all confronted with the relationship between new methods and algorithms and their implementation in proficient codes. We invite you to join us in an exploration of the relevance of HPC as an enabler of leading-edge simulation and modeling. The focus of this webinar series will be on the science made possible by combining state-of-the-art methods with optimal exploitation of supercomputing resources.","created":"Mon Dec 04 09:48:14 UTC 2023","thumbnail":"656dc31ae4b0c3a3247d0104","authorId":"649ad15af7aa6e15fad92ed5","spaces":["5a79b568e4b05cb28bae3f60"],"resource_type":"dataset"}][endorder]
Mixed-Gen
Join us for on-line sessions bringing together simulators young in years or at heart. Mixed-Gen is a venue for PhD students and young researchers to share their work, get expert feedback and have an opportunity to strengthen their scientific relations via a series of seminars on a broad range of topics.
CECAM-MARVEL Mary Ann Mansigh Conversations
The Mary Ann Mansigh Conversation series focuses of non-strictly technical topics of cultural interest for the simulation and modelling community. The format reflects the informative and informal nature of these sessions, with talks introducing the subject followed by a conversation between the speakers and the audience.[order][{"id":"66503b84e4b08465bc3424b3","name":"Science writing and science editing - from journals to journalism","description":"CECAM and MARVEL present a new event in our Mary Ann Mansigh Conversation series. In a discussion with Nature Physics editor Nina Meinzer and former Nature/Chemistry World news editor Mark Peplow, we will explore how scientific editing and scientific journalism work, how they are being transformed by new technologies, how young scientists can learn to better interact with editors and writers - or become editors and writers themselves. ","created":"Fri May 24 07:02:28 UTC 2024","thumbnail":"665044e2e4b08465bc3425e7","authorId":"649ad15af7aa6e15fad92ed5","spaces":["62dfafa8e4b0cc21d437dcea","5a79b568e4b05cb28bae3f60"],"resource_type":"dataset"},{"id":"648ad5a9e4b03bae712e38ec","name":"Fascination and industrial value of materials modeling","description":"Understanding ! the marvelous complexity of nature is a deeply human desire, and to this end modeling is a uniquely powerful tool. Starting from this view, this lecture will revolve around an aspect of high actuality, namely energy. Moving from a society burning fossil fuels and thereby destroying our vulnerable environment to solutions that are sustainable and realistic, is perhaps one of the biggest technological and societal challenges of the 21st century. By discussing specific examples including metal alloys and polymers, batteries, electronic devices, and CO2 capture. This lecture will show how modeling and simulations are applied in a wide range of length and time scales, supporting the path to better and sustainable technologies. With deeply founded theoretical concepts, highly efficient algorithms in sophisticated computer programs, and unprecedented compute power, never before had humans such fascinating tools in their hands. Thus, materials modeling creates industrial value and it satisfies our human desire for understanding the processes that form and transform materials around us.\n\nErich Wimmer is co-founder, Chief Scientific Officer, and Chairman of the Board of Materials Design. He has initiated major software development programs, organized industrial consortia, and leads research efforts to create industrial value through computational chemistry and materials science. Dr. Wimmer is author and co-author of over 130 scientific publications and has given numerous lectures 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Long before Microsoft and Apple and at a time when computers were big and expensive machines largely unknown to the general public, the Olivetti industries presented the Programma 101, the world’s first desktop computer.\n\nInnovative technological solutions and a sleek design made the Programma 101 an instant hit: specialists and public alike queued to see it, the New York Times, Wall Street Journal and several other American newspaper hailed it as a revolution, more than 40.000 pieces were sold worldwide to universities, banks, hospitals, small businesses…\n\n…And then what happened? Why don’t we all own an Olivetti laptop today? Some say it’s the nature of the market, some say that it is a spy story. We hope you will find it interesting food for thought.\n\nCECAM and MARVEL invite you to (re)discover the machine that transformed the specifications and the look and feel of calculators, opening the path to our modern laptops. With the help of two invited speakers, we shall explore the cultural environment that fostered the development of Programma 101 and learn more about its technical characteristics. Along the way, we shall meet Pier Giorgio Perotto - the father of this little marvel - and a young team of developers in the Electronic Division at Olivetti, and get to know Adriano Olivetti, an unusual industrialist who thought that profit could not be achieved without houses, libraries and social security for his employees or without schools and playgrounds for their children.\n\nOur guests and speakers for this conversation are Beniamino de’ Liguori Carino, Foundation Adriano Olivetti, and Pierpaolo Perotto, Finsa – Technology for People. As you will discover, for them this story is, also, a family 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Mary Ann's long collaboration with Berni Alder at Lawrence Livermore National Laboratory was instrumental for establishing molecular dynamics as a key tool to study condensed matter systems. The event was introduced by a presentation on the early days of computer simulations in condensed matter physics by former CECAM director Prof. Michel Mareschal.\n\nBelow are the videos of the two parts of the event.\n\nPart 2: A conversation between Mary Ann Mansigh Karlsen and Daan Frenkel (University of Cambridge, UK). Insights on her fascinating story and her experiences as a coder at Livermore over a period of almost thirty years, providing a unique point of view on the scientific and technological development of computer simulation from the early days of molecular dynamics in the late 1950, to the mid 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Jun 15 09:00:31 UTC 2023","thumbnail":"648b2b10e4b03bae712e55a3","authorId":"6218c1087c5ca1bb51509d98","spaces":["5a79b568e4b05cb28bae3f60","62dfafa8e4b0cc21d437dcea"],"resource_type":"dataset"},{"id":"648ad2c1e4b03bae712e1e64","name":"Almost famous, a woman behind the codes Part I","description":"On November 15 2017, CECAM and NCCR MARVEL invited a truly outstanding representative of the first generation of coders, Mary Ann Mansigh Karlsen, to share her recollections of those pioneering efforts. Mary Ann's long collaboration with Berni Alder at Lawrence Livermore National Laboratory was instrumental for establishing molecular dynamics as a key tool to study condensed matter systems. The event was introduced by a presentation on the early days of computer simulations in condensed matter physics by former CECAM director Prof. Michel Mareschal.\n\nBelow are the videos of the two parts of the event.\n\nPart 1: It's only numerics: an introduction to the early days of computer simulation by Michel 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Jun 15 08:58:41 UTC 2023","thumbnail":"648bdbb6e4b03bae712e7055","authorId":"6218c1087c5ca1bb51509d98","spaces":["5a79b568e4b05cb28bae3f60","62dfafa8e4b0cc21d437dcea"],"resource_type":"dataset"},{"id":"648ace96e4b03bae712e0e8e","name":"Computer modelling for industrial applications","description":"In this conversation, Massimo Noro, formerly at Unilever and current Business Development Director at Daresbury labs, will discuss with Prof. William Curtin, EPFL, and with the audience the relevance of simulation for industry and his role as the leader of an important computing facility that interacts directly with industry. This conversation will offer insight on how to promote and facilitate industrial use of simulation and modelling, and will allow us to meet a “living example” of a carrier path for simulators outside 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Jun 15 08:40:54 UTC 2023","thumbnail":"648aee6de4b03bae712e4914","authorId":"6218c1087c5ca1bb51509d98","spaces":["5a79b568e4b05cb28bae3f60","62dfafa8e4b0cc21d437dcea"],"resource_type":"dataset"}][endorder]
CECAM-MARVEL Classics in molecular and materials modeling
A series of lectures and interviews, dedicated to some of the pioneering contributions in the field of molecular and materials simulations.
The following datasets have been published through this Space and any affiliated Spaces.
Statistics
| Collections | 6 |
| Datasets | 76 |
| Files: | 78 |
| Bytes: | 86.2 GB |
| Users: | 4 |
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