BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Physical Sciences Data Infrastructure - ECPv6.17.2//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Physical Sciences Data Infrastructure X-ORIGINAL-URL:https://www.psdi.ac.uk X-WR-CALDESC:Events for Physical Sciences Data Infrastructure REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:Europe/London BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20250330T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20251026T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20260329T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20261025T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20270328T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20271031T010000 END:STANDARD END:VTIMEZONE BEGIN:VTIMEZONE TZID:Europe/Paris BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:20250330T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:20251026T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:20260329T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:20261025T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:20270328T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:20271031T010000 END:STANDARD END:VTIMEZONE BEGIN:VTIMEZONE TZID:Atlantic/Azores BEGIN:DAYLIGHT TZOFFSETFROM:-0100 TZOFFSETTO:+0000 TZNAME:+00 DTSTART:20250330T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0000 TZOFFSETTO:-0100 TZNAME:-01 DTSTART:20251026T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0100 TZOFFSETTO:+0000 TZNAME:+00 DTSTART:20260329T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0000 TZOFFSETTO:-0100 TZNAME:-01 DTSTART:20261025T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0100 TZOFFSETTO:+0000 TZNAME:+00 DTSTART:20270328T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0000 TZOFFSETTO:-0100 TZNAME:-01 DTSTART:20271031T010000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=Europe/London:20260312T130000 DTEND;TZID=Europe/London:20260312T163000 DTSTAMP:20260319T113611Z CREATED:20260126T125724Z LAST-MODIFIED:20260319T113611Z UID:36699-1773320400-1773333000@www.psdi.ac.uk SUMMARY:Online Meeting on Electronic Research Notebooks: Implementation & Adoption Success Stories DESCRIPTION:The recording of this webinar is now available on YouTube​ \n \n \n \n \n \n Event Description\nAre you considering implementing an Electronic Research Notebook (ERN) for your institution or research group but aren’t sure where to start? Have you perhaps already tried to implement an ERN and were unable to overcome certain obstacles? Or are you a digital master who has successfully implemented one and want to share your experiences? Join us for a thought provoking online meeting to share knowledge around the practicalities\, benefits\, and success stories of ERN adoption. \n \n \n \n \n \n Event Audience\nThis event is designed for anyone interested in digitising research workflows\, moving from paper notebooks (lab or otherwise!) to digital solutions\, and ensuring well-documented research data. Learn from real-world examples\, discover different ERN options\, and gain insight into the challenges and considerations required for successful ERN implementation.  \n \n \n \n \n \n Agenda\n\n13:00 – 13:15: Introductions to the Community\n13:15 – 14:15: Electronic Research Notebook Experiences\n\nOneNote Portfolios for Supporting Laboratory and Research Skills Development in Undergraduate Students – Chloe Harold and Chris Hawes (Keele University)Digital portfolios are increasingly used to support reflective and authentic assessment in higher education. This talk describes the use of Microsoft OneNote as a platform for laboratory portfolios in our undergraduate chemistry course. We discuss the rationale for adopting a portfolio-based assessment model\, outline the practical implementation of OneNote portfolios in laboratory courses across all levels\, and evaluate the strengths and limitations of OneNote for portfolio use. Student and staff feedback highlights improved organisation\, reflection\, and contemporaneous engagement with laboratory learning\, alongside improved module outcomes. We conclude by demonstrating how this approach can be transferred beyond laboratory assessment and adapted for use in other disciplines.\nUsing a general note-taking software as a flexible ERN – Dr. Danny Garside (Digital Research Academy)When Danny was a postdoc in a neuroscience lab at the National Institutes of Health in Washington DC they were tasked with finding a replacement to the lab’s system of paper notebooks. They settled on logseq – a general note-taking software which is open-source and flexible. They will discuss the reasons for this choice (free\, flexible\, no vendor lock-in\, supporting the development of open-source tools)\, how they implemented it (see this blog post)\, and lessons learnt along the way.\nImplementing OneNote in Chemistry Undergraduate Labs – Dr Philip Leadbitter (University of Southampton) In late 2019\, the undergraduate teaching laboratories in Chemistry and Chemical Engineering at the University of Southampton (UoS) underwent a major refurbishment\, including the introduction of teaching laptops to the labs. This paved the way for the teaching labs to phase out physical notebooks. Yet this phasing out process was not without its complications\, and it was not until 2024 a comprehensive replacement for the old physical notebooks was fully implemented. This talk will share insights from our implementation of OneNote and explain why ultimately a fully fledged ELN is now considered more suitable for our needs.\nTrialing and Implementing Revvity Signals in Chemistry Research Labs – Dr Samantha Pearman-Kanza (University of Southampton)In 2025\, the University of Southampton trialled the Revvity Signals Electronic Lab Notebook (ELN) across 12 chemistry research groups\, engaging 36 researchers and capturing over 120 experiments per week. This presentation shares key lessons from the pilot\, highlighting benefits such as improved workflow consistency\, ChemDraw integration\, and embedded Health & Safety documentation\, alongside technical and adoption challenges that emerged. The talk explores critical success factors for ELN implementation\, including stakeholder engagement and user support\, and outlines considerations for optimising and scaling ELN use across academic research environments.\nAI4Green: an open-source ELN promoting sustainability chemistry – Professor Jonathan Hirst (University of Nottingham)Digital tools will be a critical part of making chemistry research laboratories more sustainable. Our AI4Green open-source electronic laboratory notebook (ELN)\, https://ai4green.app\, combines features including data archival and collaboration tools. The application’s design facilitates the integration of auxiliary sustainability applications. For example\, the open-source retrosynthesis software\, AiZynthFinder has been integrated into the platform. AI4Green features a sustainable solvent selection tool\, which comprises the Solvent Guide and the Solvent Surfer. The latter is an interactive principal component analysis (PCA) that provides users with an easy method to determine greener solvent alternatives.\nImplementing RSpace as an institutional Electronic Research Notebook for UCL – James A J Wilson (UCL)After a couple of years of discussing and measuring the potential need for an institutional ERN/ELN for University College London\, a decision was made in 2020 that the time was right to acquire a system that would benefit a broad cross-section of the university and the university went to tender to purchase and implement such a system. We settled on RSpace\, as the best fit to our strategy and after user testing. RSpace has now been in place for five years – enough time to learn lessons about what has worked and what remains to be done. This presentation will summarize the story behind the selection of RSpace and what we have learnt on the way.\n\n\n14:15 – 14:45: Q+A Panel with Speakers  \n14:45 – 15:00: Coffee Break\n15:00 – 16:30: Interactive Discussion Session\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Speaker Details\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Chloe Harold (Keele University)Chloe Harold is a Chemistry lecturer at Keele University with 17 years of teaching experience. Three years ago\, she introduced OneNote laboratory portfolios into the first-year chemistry laboratory module in response to the limitations of traditional hard-backed lab diaries. Since then\, she has supported colleagues at Keele and at other universities in adopting digital laboratory portfolios. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Chris Hawes (Keele University)Chris Hawes is a lecturer and joint programme director of the Chemistry undergraduate programmes at Keele University\, with background as a structural inorganic chemistry researcher. As module lead of Keele’s year 2 laboratory module and year 4 MChem research project module\, he has followed Chloe’s successful year 1 pilot to help expand OneNote laboratory and research notebooks to the remainder of our Chemistry undergraduate programme as part of Keele’s recent curriculum redesign. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr. Danny Garside (Digital Research Academy)Danny Garside is a neuroscientist and meta-scientist\, who splits their time between researching colour vision and trying to make academia more accessible\, more efficient\, and happier. They are the Community Manager for the Digital Research Academy\, and currently excited about the opportunities for academic research co-operatives. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Philip Leadbitter (University of Southampton)Dr Philip Leadbitter is a research fellow at the University of Southampton\, working for the Physical Sciences Data Infrastructure (PSDI). His broad focus is on teaching\, both developing training and more relevant here process recording studies focused on undergraduate teaching laboratories. Recently he has working with the University teaching staff to successfully implement OneNote as a electronic lab notebook\, paving the way for a higher quality of teaching for students in the coming years. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Samantha Pearman-Kanza (University of Southampton)Dr. Samantha Pearman-Kanza is a Principal Enterprise Fellow at the University of Southampton\, the Principal Investigator for the Careers and Skills for Data-driven Research Network (CaSDaR)\, Co-Investigator  for the Physical Sciences Data Infrastructure (PSDI) Initiative\, and a researcher for the AI in Chemistry Hub (AIChemy). Samantha sits on the Advisory Boards for the Future Labs Live (Basel) and London Labs Live (UK) Conferences\, the Machines Learning Chemistry Project (University of Nottingham)\, the STEP-UP project (Imperial College London)\, and the Knowledger Project (University of North Florida)\, and the UK electronic information Group (UKeiG) STRIX Committee. She is also the Faculty Deputy Chair of the Ethics Committee. Samantha’s key research areas are ELNs\, process recording\, FAIR data\, data stewardship and research data management\, and semantic web technologies. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Professor Jonathan Hirst (University of Nottingham)Jonathan Hirstis Professor in Computational Chemistry at the University of Nottingham. In 2020\, he was awarded a Chair in Emerging Technologies by the Royal Academy of Engineering\, focusing on research that will empower the development of next-generation molecules that chemical engineers and chemists make\, by using machine learning to augment human decision-making. His tenure as Head of School (2013-2017) saw some significant transformations under his leadership\, including the building of the GSK Carbon Neutral Laboratory and a successful bid for an Athena Swan Silver Award. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n James A J WilsonDr James A J Wilson is Head of Research Data Services at the Centre for Advanced Research Computing (ARC) at UCL He has led the development of Research Data Stewardship as a profession in UCL\, building a team of eighteen research data stewards who run data management services and collaborate with researchers to support good data management and ensure data is as FAIR as possible. In 2020\, James led the implementation of an institutional Electronic Research Notebook at UCL\, based on RSpace\, and runs the ERN User Group. He is an active member of the Research Data Alliance and a co-chair of the Research Data Architectures for Research Institutions (RDARI) Interest Group. URL:https://www.psdi.ac.uk/event/electronic-research-notebooks/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/London:20260330T100000 DTEND;TZID=Europe/London:20260330T160000 DTSTAMP:20260304T154219Z CREATED:20260303T162325Z LAST-MODIFIED:20260304T154219Z UID:36783-1774864800-1774886400@www.psdi.ac.uk SUMMARY:Workshop: NMR Data Analysis of Paramagnetic Metal Complexes DESCRIPTION:As part of PSDI’s 2025 funding call\, project partners at the University of Bath (led by Dr Elizaveta Suturina) are hosting a one-day workshop focused on the NMR data analysis of paramagnetic metal complexes in solution\, supported by quantum chemistry calculations. \nThis event is supported by PSDI and is free to attend\, with lunch and refreshments provided. \n \n \n \n \n \n Event Details\n📅Date: Monday\, 30 March🕘Time: 10:00 am – 4:00 pm📍Location: 1 South 0.01\, Department of Chemistry\, University of Bath \n \n \n \n \n \n About the Workshop\nThis workshop will explore both experimental and computational approaches to paramagnetic NMR (pNMR)\, providing participants with practical tools and expert insights. \nMorning Session – Invited Speakers\nThe morning will feature talks from: \n\n Dr. Markus Enders (Universität Heidelberg)\n Lucas Lang (Technische Universität Berlin)\n\nSpeakers will cover advanced methods for analysing paramagnetic NMR data and integrating quantum chemical calculations to support structural interpretation. \nAfternoon Session – Hands-On Training\nThe afternoon will include a practical session using SimpNMR software\, along with a “bring your own research” segment where participants can receive direct support in analysing their own pNMR data. \nParticipants attending the afternoon session should bring their own laptops. \n \n \n \n \n \n Who Should Attend?\nThis workshop is aimed at PhD students and researchers who: \n\nWork with paramagnetic metal complexes\nHave experience measuring pNMR and/or calculating NMR/EPR parameters ab initio\n\n \n \n \n \n \n Registration Details\nRegistration for this event is required and places are limited. To secure a place\, please complete the Expression of Interest form. \nFor specific enquiries\, please contact Dr Elizaveta Suturina at e.suturina@bath.ac.uk. URL:https://www.psdi.ac.uk/event/nmr_workshop_bath/ LOCATION:Private: University of Bath CATEGORIES:Workshop END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20260413 DTEND;VALUE=DATE:20260418 DTSTAMP:20251024T100532Z CREATED:20251024T100349Z LAST-MODIFIED:20251024T100532Z UID:36525-1776038400-1776470399@www.psdi.ac.uk SUMMARY:Chemical and Materials Machine Learning School 2026 DESCRIPTION:📅 Dates: 13–17 April 2026📍 Venue: STFC Daresbury Laboratory\, United Kingdom💷 Fee: £250 (includes 4 nights’ accommodation & catering)👉 Website / Apply here: spring2026.camml.ac.uk \n \n \n \n \n \n Overview\n \n \n \n \n \n The Chemical and Materials Machine Learning School (CaMMLs) is a five-day intensive training course designed for PhD students (and a limited number of industrial applicants) working in the field of materials and molecular simulations who have coding experience but are not yet highly experienced with machine learning (ML). The school is organised by Physical Sciences Data Infrastructure (PSDI) in collaboration with AIchemy\, and supported by STFC‑SCD\, CCP5 and CCP9. \nParticipants will explore the latest ML methods for atomistic simulation of materials and molecules through a combination of talks\, hands-on practical sessions and poster presentations. Topics include fundamentals of machine learning\, interatomic potentials and graph neural networks. \n \n \n \n \n \n Learning Outcomes\n \n \n \n \n \n By the end of the school\, participants will: \n\n\nGain awareness of state-of-the-art ML methods for atomistic and molecular simulations \n\n\nGain practical experience applying ML techniques in real-world research contexts \n\n\n \n \n \n \n \n Key Dates\n \n \n \n \n \n \n\nApplication deadline: 26 November 2025 \n\n\nNotification of acceptance: 17 December 2025 \n\n\nPayment deadline: 13 February 2026 \n\n\n \n \n \n \n \n Who Should Attend\n \n \n \n \n \n This school is aimed primarily at PhD students in materials & molecular simulation who already code but are new to machine learning. A limited number of places may be available for industrial applicants. Places are limited and\, in the event of oversubscription\, we will prioritise a diverse cohort of participants. \n \n \n \n \n \n How to Apply\n \n \n \n \n \n Visit spring2026.camml.ac.uk to complete your application. Payment of the course fee must be made by 13 February 2026 upon acceptance. Accommodation and catering for four nights are included in the fee. \n \n \n \n \n \n Contact / Further Information\n \n \n \n \n \n For any enquiries please contact Alin M Elena at alin-marin.elena@stfc.ac.uk. We encourage you to share this opportunity with colleagues and students who may be interested. URL:https://www.psdi.ac.uk/event/cammls-2025-2/ LOCATION:Daresbury Laboratory\, Keckwick Lane\, Daresbury\, WA4 4AD\, United Kingdom CATEGORIES:Training END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/Paris:20260423T140000 DTEND;TZID=Europe/Paris:20260423T150000 DTSTAMP:20260501T130001Z CREATED:20260310T164302Z LAST-MODIFIED:20260501T130001Z UID:36874-1776952800-1776956400@www.psdi.ac.uk SUMMARY:Webinar: BioSimDR - A Collection of Data Tools and Infrastructure for Biomolecular Simulation DESCRIPTION:This webinar illustrates how BioSimDR transforms scattered biomolecular simulation data into interoperable\, provenance-rich resources for broader reuse. \nThe recording of this webinar is now available on YouTube \n \n \n \n \n \n Abstract\nBiomolecular simulations generate rich\, atomic-level insights into the dynamics of complex biological systems\, but sharing\, interpreting and reusing these datasets remains challenging. BioSimDR (BioSim Data Resources) is a PSDI-funded initiative that works with the CCPBioSim and HECBioSim communities to bring FAIR principles to biomolecular simulation data. \nIn this webinar\, we will outline common barriers to simulation reproducibility\, including inaccessible protocols\, missing metadata\, and incomplete records of simulation steps\, and we will introduce the BioSimDR tools designed to address these challenges. We will demonstrate BioSimDB\, a prototype data repository tailored for biomolecular simulations\, and new provenance-capture tools that allow researchers to automatically record every simulation step for easier sharing and reuse. \nAttendees will learn: \n\n\n\nHow provenance capture supports reproducible and reusable MD simulations\nHow BioSimDB enables standardised storage\, discovery\, and sharing of biomolecular simulation datasets\nHow the BioSimDR initiative collaborates with the community to build consensus-driven standards for FAIR simulation data\n\n\n\nThis session is intended for researchers generating\, analysing\, or reusing biomolecular simulations who want to improve transparency and reproducibility in their workflows. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Biography\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Jas Kalayan from STFC is a scientific software engineer specialising in reproducible workflow development and data‑sharing solutions for molecular simulation. She has a strong research background in advanced molecular modelling\, including the development of machine‑learned interatomic potentials and entropy‑based methodologies. Her work has supported molecular dynamics studies focusing on protein–ligand binding\, hydration phenomena\, and free‑energy calculations\, with an overarching goal of improving transparency and reproducibility in computational biomolecular science. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Watch the recording\nYou can watch the recording of this webinar via our YouTube channel. Slides are available on Zenodo. \n\n\n\n\n\n\n\n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/webinar-biosimdr/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Atlantic/Azores:20260430T150000 DTEND;TZID=Atlantic/Azores:20260430T160000 DTSTAMP:20260522T100616Z CREATED:20260401T100337Z LAST-MODIFIED:20260522T100616Z UID:36980-1777561200-1777564800@www.psdi.ac.uk SUMMARY:Webinar: From Project to Platform: New Resources on PSDI - Session 1 DESCRIPTION:PSDI is pleased to launch a new webinar series entitled “From Project to Platform: New Resources on PSDI”. This series aims to showcase the high-quality tools and resources developed through the funding call 2025\, introduce them to a broader community\, and foster engagement with relevant user groups.   \nThe recording of this webinar is now available on YouTube \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Presentation 1\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n “Universal” Hyper-Active Learning for Machine Learning Interatomic Potentials\n \n \n \n \n \n Challenge\n \n \n \n \n \n \n\n\nBuilding accurate machine‑learning models of atomic interactions requires carefully curated training datasets\, yet generating these datasets is often the hardest and most time‑consuming step.\n\n\n\n \n \n \n \n \n Approach\n \n \n \n \n \n \n\n\nWe introduce ase‑uhal\, a Python tool developed through a PSDI Pilot Project (Oct 2025–Mar 2026).\nIt automates and accelerates dataset generation\, steering atomistic simulations toward the most informative configurations and avoiding redundant calculations.\nThe tool is available via pip install ase-uhal and integrates seamlessly with the ASE ecosystem.\n\n\n\n \n \n \n \n \n Innovation\n \n \n \n \n \n \n\n\nA “universal” extension of the Hyperactive Learning (HAL) framework makes the method compatible with modern foundation models that can be fine‑tuned.\nA new batched workflow significantly increases throughput compared to existing methods.\nDemonstrated on an InGaP alloy system\, where models trained on diverse data outperform those trained on random sampling.\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n James Kermode is a Professor in the School of Engineering at the University of Warwick (UoW)\, where he directs the EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems (HetSys CDT) and the Warwick Centre for Predictive Modelling (WCPM)\, both of which have strong synergies with PSDI activities across the full spectrum from theory and algorithm development through research software engineering to applications. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Presentation 2\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n MOFevaluator: A Cloud-Based Platform for Process-Informed Discovery of Metal–Organic Frameworks for Carbon Capture and Beyond\n \n \n \n \n \n Challenge\n \n \n \n \n \n \n\n\nMetal‑Organic Frameworks (MOFs) are promising for carbon capture and gas‑separation applications\, but moving from research to industrial‑scale decarbonization requires demonstrating economically viable production and deployment routes.\nIdentifying optimal MOFs requires understanding the full energy‑system context\, including CO₂ sources\, sinks\, costs\, and process constraints.\n\n\n\n \n \n \n \n \n Approach\n \n \n \n \n \n \n\n\nThe MOFevaluator project builds on the PrISMa platform\, which evaluates MOF performance based on:\n\nspecific CO₂ sources (power plants\, industry\, direct air capture)\npossible CO₂ sinks (geological storage\, mineralisation\, conversion\, etc.)\nregional constraints\n\n\nThis includes process modelling\, techno‑economic analysis\, and life‑cycle assessment\, ensuring that system‑scale requirements guide material discovery.\n\n\n\n \n \n \n \n \n Innovation\n \n \n \n \n \n \n\n\nMOFevaluator transforms the workflow from a local simulation tool into a cloud‑based platform with a fully searchable MOF materials database.\nResearchers can:\n\nvisualise data through an interactive web interface\nintegrate the database via API\nuse a streamlined environment to explore new opportunities for MOF discovery and application\n\n\nThe platform enables faster\, more scalable\, and system‑informed materials discovery.\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Peter McCallum is a Research Software Engineer at Heriot-Watt University\, specialising in the architectures and development of web-based research systems. Having spent a decade in industry working on low-carbon energy system as a mechanical engineer\, he has since led software development activities in academic settings\, across themes including fluid dynamics\, control engineering\, energy networks\, built-environment modelling\, and for the new MOFevaluator web-platform. His main ambition is to build tools that not only support research but also translate quickly to applied industrial settings\, through distributed computing\, web-based visuals\, and API connected data via the cloud. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Susana Garcia Trained as a Chemical Engineer\, Susana Garcia is a Full Professor in Chemical and Process Engineering and the Associate Director on CCUS at the Research Center for Carbon Solutions (RCCS) in Heriot-Watt University (Edinburgh). An internationally recognised expert on low carbon separation processes\, CCUS and DAC technologies\, leading AI-driven materials discovery for industrial decarbonisation projects. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Watch the recording\nYou can watch the recording of this webinar via our YouTube channel. Slides are available on Zenodo: https://zenodo.org/records/20273802 and https://zenodo.org/records/20273806 \n\n\n\n\n\n\n\n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/new-resources-webinar-1/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Atlantic/Azores:20260521T140000 DTEND;TZID=Atlantic/Azores:20260521T150000 DTSTAMP:20260604T092733Z CREATED:20260417T151512Z LAST-MODIFIED:20260604T092733Z UID:37049-1779372000-1779375600@www.psdi.ac.uk SUMMARY:Webinar: From Project to Platform: New Resources on PSDI - Session 2 DESCRIPTION:PSDI is pleased to launch a new webinar series entitled “From Project to Platform: New Resources on PSDI”. This series aims to showcase the high-quality tools and resources developed through the funding call 2025\, introduce them to a broader community\, and foster engagement with relevant user groups.   \nThe recording of this webinar is now available on YouTube \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Abstract\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n When TD-DFT Fails: BenchmarkSet1500\, a Multireference Excited-State Dataset for Organic Semiconductor Discovery\n \n \n \n \n \n Challenge\n \n \n \n \n \n \n\n\nAccurate excited‑state prediction is critical for organic semiconductor design (e.g. OLEDs\, OPVs)\nWidely used single‑reference methods (e.g. TD‑DFT) often fail for: strong static correlation; double‑excitation character; inverted singlet–triplet gaps\nLack of reliable\, large‑scale multireference benchmark data limits: method development; validation of excited‑state models; data‑driven and ML‑based discovery\n\n\n\n \n \n \n \n \n Approach\n \n \n \n \n \n \n\n\nDevelopment of BenchmarkSet1500\n\na curated dataset of 1\,500 organic molecules\nexcited‑state properties computed using multireference electronic structure methods\n\n\nSystematic analysis of\n\nmolecular diversity\nstatistical distribution of excited‑state properties\n\n\nDerivation of practical guidelines\n\nselecting suitable levels of theory\nbased on molecular fragment type\n\n\nDemonstration through targeted molecular screening\n\ninverted singlet–triplet gaps\nthermally activated delayed fluorescence (TADF)\ndeviations from Kasha’s rule\n\n\n\n\n\n \n \n \n \n \n Innovation\n \n \n \n \n \n \n\n\nFirst large‑scale multireference benchmark dataset focused on organic excited states\nEnables quantitative assessment of TD‑DFT failure regimes\nProvides a foundation for systematic excited‑state photophysics exploration\nSupports method development\, benchmarking\, and validation beyond single‑reference models\nEstablishes a high‑quality data resource for future machine‑learning‑driven materials discovery\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Bio\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Malin Zollner (University of Strathclyde) is a Research Assistant in Chemistry at the University of Strathclyde\, funded by PSDI. Her work focuses on developing data resources to support organic semiconductor discovery\, with applications in data-driven modelling and machine learning.She completed her MChem in Pure and Applied Chemistry at the University of Strathclyde in 2024\, where she began exploring the intersection of computational chemistry and materials discovery\, and has since developed a strong background in machine learning for chemical applications. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Watch the recording\nYou can watch the recording of this webinar via our YouTube channel.Slides are available on Zenodo: https://zenodo.org/records/20539210 \n \n \n \n \n \n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/new-resources-webinar-3/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Atlantic/Azores:20260618T140000 DTEND;TZID=Atlantic/Azores:20260618T150000 DTSTAMP:20260730T142945Z CREATED:20260416T102949Z LAST-MODIFIED:20260730T142945Z UID:37017-1781791200-1781794800@www.psdi.ac.uk SUMMARY:Webinar: From Project to Platform: New Resources on PSDI - Session 3 DESCRIPTION:PSDI is pleased to launch a new webinar series entitled “From Project to Platform: New Resources on PSDI”. This series aims to showcase the high-quality tools and resources developed through the funding call 2025\, introduce them to a broader community\, and foster engagement with relevant user groups.   \nThe recording of this webinar is now available on YouTube \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Abstract\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Challenge\n \n \n \n \n \n \n\n\nGrowing concerns of a reproducibility crisis in electrochemical devices\, particularly within the flow battery research community\nA lack of standardised experimental practices and few consistent reporting frameworks\nLimited reliability and comparability of reported results across laboratories\nInter‑lab differences are difficult to interpret\, slowing collective progress and best‑practice development\n\n\n\n \n \n \n \n \n Approach\n \n \n \n \n \n \n\n\nSince 2023\, multi‑institutional round‑robin studies co‑led by QUB and MIT\nSystematic investigation of repeatability\, replicability\, reproducibility in flow battery cell testing\nPhase 1 (complete)\n\nIdentical flow battery test cell kits distributed to 11 researchers from 7 institutions\nNominally identical electrochemical measurements performed\n\n\nPhase 2 (on-going)\n\nCommunity‑scale expansion to over 40 researchers from 35 institutions\nPhase 2a: reproducibility using participants’ own cells\nPhase 2b: large‑scale replicability study using updated standardised kits\n\n\n\n\n\n \n \n \n \n \n Innovation\n \n \n \n \n \n \n\n\nCombination of community‑scale participation\, shared nomenclature\, and affordable 3D-printed cells\nDevelopment of a PSDI‑supported data infrastructure for:\n\ncross‑institutional data collection\ninteractive visualisation\ncomparative analysis at scale\n\n\nEnables identification of systematic trends across laboratories\nEstablishes a pathway toward transparent\, comparable\, and reproducible testing standards for single‑cell flow batteries\n\n\n\n \n \n \n \n \n Phase 1: Replicability Study Timeline\n \n \n \n \n \n \n \n \n \n \n \n Phase 2: Community‑Scale Participation\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Bio\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Josh J. Bailey is an Illuminate Fellow at Queen’s University Belfast\, working at the interface of physical experimentation and computational modelling to improve performance\, durability\, and sustainability of electrochemical devices. He co-leads international activities aiming to measure and improve reproducibility in flow battery testing\, whilst designing new materials and protocols. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Watch the recording\nYou can watch the recording of this webinar via our YouTube channel.Slides are available on Zenodo: https://zenodo.org/records/21700990 \n \n \n \n \n \n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/new-resources-webinar-2/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Atlantic/Azores:20260709T140000 DTEND;TZID=Atlantic/Azores:20260709T150000 DTSTAMP:20260723T063723Z CREATED:20260519T143425Z LAST-MODIFIED:20260723T063723Z UID:37435-1783605600-1783609200@www.psdi.ac.uk SUMMARY:Webinar: From Project to Platform: New Resources on PSDI – Session 4 DESCRIPTION:Registration link: https://us06web.zoom.us/webinar/register/WN_ws-354zrRTGV6faNNmEUxg   \nPSDI is pleased to launch a new webinar series entitled “From Project to Platform: New Resources on PSDI”. This series aims to showcase the high-quality tools and resources developed through the funding call 2025\, introduce them to a broader community\, and foster engagement with relevant user groups.   \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Abstract\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n SimpNMR – a Tool for Ab initio-assisted analysis of NMR data of paramagnetic metal complexes in solution\n \n \n \n \n \n Challenge\n \n \n \n \n \n \n\n\nNMR spectra of paramagnetic metal complexes in solution are notoriously difficult to interpret\, as unpaired electrons produce large chemical shifts\, broadened lineshapes\, and temperature-dependent behaviour that standard diamagnetic analysis tools cannot handle.\nExtracting meaningful electronic structure information (magnetic susceptibility tensors\, correlation times\, spin-Hamiltonian parameters) from pNMR data requires combining experimental spectra with ab initio calculations\, a workflow that today remains fragmented\, manual\, and inaccessible to many researchers.\n\n\n\n \n \n \n \n \n Approach\n \n \n \n \n \n \n\n\nSimpNMR is a Python package that streamlines pNMR analysis by directly incorporating outputs of ab initio calculations.\nIt provides an end-to-end workflow for paramagnetic complexes in solution\, including:\n\nprediction of 1D NMR spectra (e.g. 1H\, 13C)\nassignment of experimental peaks to molecular sites\nfitting of the magnetic susceptibility tensor and correlation times to experimental pNMR data\n\n\nWith variable-temperature experiments\, SimpNMR extracts spin-Hamiltonian parameters such as the g-tensor\, and in certain cases the D-tensor\, directly from solution pNMR data\, information typically accessible only from EPR or SQUID magnetometry.\n\n\n\n \n \n \n \n \n Innovation\n \n \n \n \n \n \n\n\nSimpNMR transforms pNMR analysis from a bespoke\, expert-only procedure into a reproducible\, scriptable Python workflow that bridges computational and experimental chemistry.\nSimpNMR_DB\, a curated companion database\, stores the input data required for SimpNMR analysis\, enabling:\n\nreuse and benchmarking of ab initio inputs across complexes\nreproducible\, shareable analysis pipelines\naccelerated discovery by lowering the barrier to quantitative pNMR interpretation\n\n\nTogether\, SimpNMR and SimpNMR_DB open up solution pNMR as a practical route to electronic-structure parameters of paramagnetic metal complexes.\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Bio\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Elizaveta A. Suturina (University of Bath) is a senior lecturer in Computational Chemistry at the University of Bath. Her research combines computational and experimental approaches to reveal key structural modifications that enhance magnetic properties in cobalt(II) complexes.She currently leads a project developing a Python toolkit for ab initio-assisted analysis of paramagnetic NMR of metal complexes\, which has inspired further research extending these approaches across different chemical systems. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Register for this webinar\nRegister for this webinar directly through zoom:https://us06web.zoom.us/webinar/register/WN_ws-354zrRTGV6faNNmEUxg \n \n \n \n \n \n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/new-resources-webinar-4/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/London:20260716T100000 DTEND;TZID=Europe/London:20260716T160000 DTSTAMP:20260709T104031Z CREATED:20260430T113441Z LAST-MODIFIED:20260709T104031Z UID:37165-1784196000-1784217600@www.psdi.ac.uk SUMMARY:Transitioning from FAIR to AI Ready Data in the Physical Sciences: A PSDI & AIchemy Workshop DESCRIPTION:Event Details\n📅Date: Thursday\, 16 July\n🕘Time: 10:00 am – 4:00 pm\n📍Location: University of Southampton\, B100 Room 6009\, Highfield Campus\, Southampton\, SO17 1BJ\n \n \n \n \n \n About the Workshop\nIn recent years\, the physical sciences community has been generating increasingly large and complex datasets\, at a scale that is now beyond what can be fully explored or analysed by humans alone. As a result\, researchers are turning to AI and machine‑learning techniques\, which have matured significantly and offer powerful new ways to extract insight from data. However\, while the adoption of FAIR data principles has improved data sharing and reuse\, experience is showing that FAIR does not necessarily mean AI‑ready. Many datasets remain difficult to use effectively in AI and Machine Learning models.   \nThis interactive workshop has been co-created by the Physical Sciences Data Infrastructure (PSDI) and the AI in Chemistry Hub (AIchemy). It aims to bring together researchers\, data professional and infrastructure developers to facilitate knowledge exchange and explore what it truly means to be “AI Ready”. The workshop is comprised of invited presentations\, lightning talks from participants and interactive discussion sessions. The talks will share current practices\, highlighting successes and challenges\, and the discussion sessions will explore the practical approaches and tools for evaluating and improving AI readiness.   \nAudience\nThis in-person event is aimed at anyone interested in dataset standards\, curation\, and developing robust methods to assess the applicability and reliability of data for reuse. It will be particularly relevant for researchers and research software engineers working with data and AI/ML\, data stewards and research data managers\, infrastructure and platform developers\, and scientists interested in enabling future reuse of their datasets.  \nLightning Talks\n Applications for Lightning Talks have now closed. \n\nThe organising team is currently reviewing submissions and will notify successful applicants by 26 June 2026. \n\n  \nAgenda  \n\n10:00 – 10:30 Registration + coffee\n10:30 – 10:35 Housekeeping + Intro\n10:35 – 10:45 Introduction to PSDI\n10:45 – 10:55 Introduction to AIChemy\n10:55 – 11:10 Setting the Scene\n11:10 – 11:25 Coffee Break & Networking\n11:25 – 11:45 Aileen Day – What did PSDI learn when making physical sciences datasets AI ready?\n11:45 – 12:05 Matthew Partridge – Making a data collection AI Ready\n12:05 – 12:25 Nessa Carson – Building trustworthy\, reusable reaction data\n12:25 – 12:45 Otello Roscioni – Balancing FAIRness and Data Sovereignty n Computational Materials Science\n12:45 – 13:30 Networking Lunch\n13:30 – 14:20 Lightning Talks / Use Case Presentations  \n14:20 – 14:25 Introduce Discussions\n14:25 – 14:55 Discussion Sessions – part 1  \n14:55 – 15:10 Coffee Break & Networking\n15:10 – 15:40 Discussion Sessions – part 2\n15:40 – 16:00 Wrap Up\n\n\nEvent Travel\nThe University of Southampton is accessible via various different transport links \n\nTravelling by Train: Southampton Airport Parkway is the closest station\, but Highfield Campus is also close to St Denys and Southampton Central Station\n\n\nTravelling by Bus: Highfield Campus is on the bus route for all Unilink Busses\n\n\nTravelling by Car: Highfield Campus has very limited parking\, and unfortunately the usual short stay car park is temporarily closed.  You can find nearby parking at Hampton Car Park – please ensure you pay for your parking using the signs provided to avoid any unnecessary parking charges.\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Bio\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Aileen Day is currently working as Senior Data Engineer of Physical Sciences Data Infrastructure (PSDI) leading the development of its metadata. This involves applying best practices in designing the metadata schema\, development of tools and workflows to support metadata input\, update and validation\, integration with other PSDI services and providing support and guidance to PSDI contributors and users.  Throughout her career she has worked with one foot in science (Chemistry and Materials Science) and one foot in computing (computer modelling\, programming\, databases).  Aileen initially studied materials science at the University of Cambrige\, then completed a PhD in the chemistry department at University College London (computer modelling zeolites). She has been a Materials Information Consultant for Granta Design where she worked with customers to make databases of materials properties.  She also spent many years at the Royal Society of Chemistry\, developing RSC publications and ChemSpider and linking them to each other and other relevant resources. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Matthew Partridge is Senior Enterprise Fellow and Director of Outreach in the School of Chemistry and Chemical Engineering at the University of Southampton. His work focuses on physical chemistry data collections\, and on making these more accessible and useful for the wider chemistry community. He works within the Physical Sciences Data Infrastructure (PSDI)\, contributing to Alchemy projects including electronic lab notebook adoption in chemistry and making data AI-ready. He also helps develop and grow the School’s outreach activities\, bringing chemistry to as wide an audience as possible. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Nessa Carson received Master’s degrees in synthesis and catalysis from Oxford University and the University of Illinois at Urbana-Champaign. She started out as a synthetic chemist for AMRI\, then moved within the company to run the high-throughput automation facility for Eli Lilly in Windlesham\, working across discovery and process chemistry\, then in high-throughput reaction optimization at Pfizer and then Syngenta. Nessa moved to AstraZeneca in 2022 as Digital Champion\, focussing on digital transformation and making life easier for scientists\, and currently works in the Predictive Science\, Digital\, and Automation team. She was awarded the Salters’ Institute Centenary Award for early-career chemists with the potential to make an outstanding long-term contribution to industrial chemistry. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Otello Roscioni is a PhD-qualified computational chemist who has spent four years working as an Ontologist\, bringing rigorous scientific grounding to knowledge engineering. He made a key contribution to the release of the Elementary Multiperspective Material Ontology (EMMO)\, one of the most significant open ontologies in materials science and engineering. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Registration Details\nPlease register for this event here\, please note spaces are limited. \n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n PSDI Project Shows How Physical Sciences Data Can Be Made Ready for AI\nPlease check out this recent article by Dr Matthew Partridge and Dr Aileen Day  \nPSDI Project Shows How Physical Sciences Data Can Be Made Ready for AI \n  URL:https://www.psdi.ac.uk/event/ai-ready-data/ LOCATION:University of Southampton\, Highfield Campus\, Southampton\, Hampshire\, SO17 1BJ\, United Kingdom CATEGORIES:Workshop ATTACH;FMTTYPE=image/png:https://www.psdi.ac.uk/wp-content/uploads/2026/04/Transitioning-from-FAIR-to-AI-Ready-data-in-the-Physical-Sciences-A-PSDI-AIchemy-Workshop-1.png END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20260729 DTEND;VALUE=DATE:20260801 DTSTAMP:20260629T085516Z CREATED:20260518T131804Z LAST-MODIFIED:20260629T085516Z UID:37432-1785283200-1785542399@www.psdi.ac.uk SUMMARY:PSDI & Royce Materials Data Summit DESCRIPTION:📅 Dates: 29th -31st July 2026📍 Location: Nancy Rothwell Building\, University of Manchester\, Manchester\, M13 9PL🤝 Organised by: The Henry Royce Institute & the Physical Sciences Data Infrastructure \n \n \n \n \n \n Overview\nThe Henry Royce Institute and the Physical Sciences Data Infrastructure (PSDI) are pleased to announce the PSDI & Royce Materials Data Summit\, which will be held from 29th to 31st July 2026 at the University of Manchester. \nThis event aims to bring together professionals working on digitalisation in materials science\, giving them the opportunity to share their work\, learn about recent developments\, and build collaborations. \nTopics in scope for the event include\, but are not limited to\, the following (in the context of materials): \n\n\n\nData standards\, metadata quality\, ontologies\, and semantic interoperability\nDigital research tools\, including workflow automation frameworks and electronic laboratory notebooks\nCommunity databases and curated data collections\nData-driven applications of AI\nAutonomous laboratories and digital twins\n\n\n\nWe welcome participants from a wide range of backgrounds\, e.g. experimentalists\, computational scientists\, industry\, software engineers\, data engineers\, data stewards. \nFormat\nThe event will be split into two parts: \n1. The 29th July will be dedicated to hands‑on training sessions where participants will be given the chance to try bleeding-edge digital tools. This training day will run from 1100-1845. \n2. The 30th and 31st July will have the format of a traditional conference\, featuring invited talks from leaders in the field and a poster exhibition. Participants attending this part of the event will be invited to submit abstracts for the poster exhibition. The conference will run from 0900-1800 on 30th July\, and 0900-1730 on 31st July. Moreover\, we hope to provide a optional conference dinner on the evening of the 30th July (1925-2125 to be confirmed)\, and tours of the host institution’s laboratories during the conference days. \nParticipants can register for one or both parts of the event (see below for link). At registration participants can specify their interest in\, e.g. the conference dinner and lab tour. Note that this event will be free to attend\, but requires registration. The exception is the optional conference dinner\, which will have a cost to be determined. \nNote that this event is in-person only for participants. \nA detailed timetable for the event (both parts) will be published at PSDI & Royce Materials Data Summit (29th-31st July 2026): Timetable · STFC Indico. \n\nParticipate\n\n\n\n\n\nThe link to register to attend (one or both of the training day and conference) is PSDI & Royce Materials Data Summit (29th-31st July 2026): Registration · STFC Indico. At registration participants can express interest in the conference dinner and laboratory tours for the conference.\nTo submit poster abstracts the link is PSDI & Royce Materials Data Summit (29th-31st July 2026): Call for Abstracts · STFC Indico.\n\n\n\n\nMotivation\n\nThis event builds on the success of the 2025 PSDI Materials Community Workshop\, hosted at the Royce Institute\, which attracted strong interest from researchers across the UK and Europe. That workshop became a catalyst for ongoing cross‑community dialogue on digital approaches in materials research. \n\n\nWhile numerous specialised meetings exist – for example\, on computational simulation\, data curation\, AI\, semantic interoperability\, or experimental data analysis – these events typically focus on their own technical domain rather than on materials as a unifying theme. As a result\, communication across the materials community remains fragmented\, slowing the development of coherent\, multi‑aspect digitalisation strategies. \n\n\nConversely\, broad materials‑research conferences (such as the UK’s Materials Research Exchange) include digitalisation as one topic among many\, but their generalist audiences limit the depth and continuity of discussions around digital technologies. \n\n\n‘PSDI & Royce Materials Data Summit’ aims to close this gap by offering a dedicated and inclusive forum for a holistic\, multi‑faceted conversation about materials digitalisation. \nFurther information\n\n\nFor specific enquiries please contact: \n\n\n\n\n\nStavrina Dimosthenous (stavrina.dimosthenous@manchester.ac.uk)\nTom Underwood (tom.underwood@stfc.ac.uk).\n\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n The call for abstracts is open\n \n \n \n \n \n You can submit an abstract for reviewing. \n \n \n \n \n \n \n \n Submit new abstract\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Registration\n \n \n \n \n \n Registration for this event is currently open. \n \n \n \n \n \n \n \n Register now \n \n \n \n \n \n 29th-31st July 2026 URL:https://www.psdi.ac.uk/event/psdi_royce_materials_data_summit/ LOCATION:University of Manchester CATEGORIES:Large Event ATTACH;FMTTYPE=image/jpeg:https://www.psdi.ac.uk/wp-content/uploads/2026/05/PSDIROYCEheader5-2048x1171-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/Paris:20260820T140000 DTEND;TZID=Europe/Paris:20260820T150000 DTSTAMP:20260722T135731Z CREATED:20260722T120309Z LAST-MODIFIED:20260722T135731Z UID:37674-1787234400-1787238000@www.psdi.ac.uk SUMMARY:Webinar: From Project to Platform: New Resources on PSDI – Session 5 DESCRIPTION:Registration link: https://us06web.zoom.us/webinar/register/WN_vaiecs9ETrKM3WsOV1EC1w \nPSDI is pleased to launch a new webinar series entitled “From Project to Platform: New Resources on PSDI”. This series aims to showcase the high-quality tools and resources developed through the funding call 2025\, introduce them to a broader community\, and foster engagement with relevant user groups.   \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \nAbstract\nKinetic mechanisms are essential for understanding\, modelling and optimising reacting systems\, yet they are often difficult to access\, reproduce and reuse. Mechanisms are frequently distributed across journal articles\, supplementary files and bespoke software formats\, with limited standardisation and incomplete documentation of species\, reactions\, thermodynamic data and provenance.  These barriers hinder reproducibility\, comparison between models and the development of reliable digital workflows in reaction engineering. \nThis webinar introduces ORKiM\, an open-access repository designed to support the publication\, curation and reuse of kinetic mechanisms. ORKiM provides a structured platform through which researchers can share mechanisms together with their associated metadata\, supporting transparency\, interoperability and long-term accessibility.  The repository aims to promote community-driven development of kinetic mechanisms and models and facilitate their integration with simulation\, mechanism-generation and microkinetic-analysis tools. \nThe webinar will present a case study on alkene oligomerisation in acidic zeolites\, illustrating how mechanistic information can be obtained\, organised\, validated and disseminated.  The case study highlights the complexity of reaction networks involving surface intermediates\, competing pathways and catalyst-specific effects\, and demonstrates how an openly accessible\, well-documented mechanism can support reproducibility\, model comparison and further development by the wider catalysis and reaction-engineering communities. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Biography\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Sergio Vernuccio is an Associate Professor in the School of Chemistry and Chemical Engineering at the University of Southampton.  His research activity employs a synergistic combination of computational and experimental approaches to unravel the kinetics of complex reacting systems for sustainable development\, including catalytic processes\, photochemical transformations\, thermal decompositions. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Register for this webinar\nRegister for this webinar directly through zoom:https://us06web.zoom.us/webinar/register/WN_vaiecs9ETrKM3WsOV1EC1w \n \n \n \n \n \n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/new-resources-webinar-5/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=Atlantic/Azores:20261022T140000 DTEND;TZID=Atlantic/Azores:20261022T150000 DTSTAMP:20260813T123023Z CREATED:20260807T133320Z LAST-MODIFIED:20260813T123023Z UID:37802-1792677600-1792681200@www.psdi.ac.uk SUMMARY:Webinar: From Project to Platform: New Resources on PSDI – Session 6 DESCRIPTION:Registration link: https://us06web.zoom.us/webinar/register/WN_6Y8kFYYFQyOv5i5J9Qxx_A \nPSDI is pleased to launch a new webinar series entitled “From Project to Platform: New Resources on PSDI”. This series aims to showcase the high-quality tools and resources developed through the funding call 2025\, introduce them to a broader community\, and foster engagement with relevant user groups.   \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Abstract\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n TopoStats and AFMDB – an open source toolkit for the analysis and sharing of Atomic Force Microscopy datasets.\n \n \n \n \n \n Challenge\n \n \n \n \n \n \n\n\nAFM generates rich multimodal nanoscale data without the need for labelling or vacuum environments.\nQuantitative analysis has historically been limited by manual\, non-standardised\, and difficult-to-reproduce workflows.\nLimited availability of automated analytical tools and machine learning integration has restricted large-scale\, data-driven AFM research.\n\n\n\n \n \n \n \n \n Approach\n \n \n \n \n \n \n\n\nAFM Reader\n\nFAIR open-source utility for standardised access to AFM datasets across multiple instrument formats.\nSimplifies data loading and improves interoperability between datasets.\n\n\nTopoStats\n\nFAIR open-source Python pipeline for data cleaning\, processing\, feature identification\, and instance segmentation.\nSupports automated batch analysis\, enabling robust and repeatable quantitative measurements.\n\n\nAFMDB\n\nOpen repository linking raw AFM files (.spm\, .jpk\, .asd\, .ibw\, etc.) with processed outputs.\nPromotes open data practices and long-term reuse of AFM datasets.\n\n\n\n\n\n \n \n \n \n \n Innovation\n \n \n \n \n \n \n\n\nEnables scalable\, fully quantitative\, and reproducible AFM data analysis through an integrated open-source ecosystem.\nCombines data access\, automated image analysis\, and data management within a FAIR framework.\nCreates a growing repository of curated AFM datasets that:\n\nfacilitates data sharing and community benchmarking;\nsupports the training and validation of machine learning and deep learning models;\naccelerates the development of next-generation AI-enabled AFM analysis tools.\n\n\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Thomas Catley is a Research Associate in Single Molecule Microscopy and DNA Biophysics at the University of Sheffield. His research uses experimental and computational approaches to understand the structure and dynamics of DNA-protein interactions. Tom is currently leading a collaboration with PSDI to develop TopoStats capabilities for materials science applications\, alongside AFMDB. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Register for this webinar\nRegister for this webinar directly through zoom:https://us06web.zoom.us/webinar/register/WN_6Y8kFYYFQyOv5i5J9Qxx_A \n \n \n \n \n \n The PSDI team looks forward to seeing you at the webinar\, if you have any questions you can always get in contact with us. URL:https://www.psdi.ac.uk/event/new-resources-webinar-6/ LOCATION:Online\, Virtual Event\, Online CATEGORIES:Webinar END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20261102 DTEND;VALUE=DATE:20261107 DTSTAMP:20260603T142225Z CREATED:20260603T133859Z LAST-MODIFIED:20260603T142225Z UID:37596-1793577600-1794009599@www.psdi.ac.uk SUMMARY:Workshop: 5th Ontologies4Chem – Limburg\, Germany DESCRIPTION:📣 SAVE-THE-DATE ANNOUNCEMENT \n5th Ontologies4Chem Workshop \nThe next iteration of Ontologies4Chem is in planning with our team of collaborators. \n\n📅 Dates: November 2–6\, 2026📚 Workshop core program: November 3–5\, 2026📍 Location: Domhotel Limburg Grabenstraße 57\, Limburg\, Germany \n\n \n \n \n \n \n Organisers\n\n\n\nTIB\, Beilstein-Institut\, NFDI4Chem\, NFDI4Cat & PSDI \n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n\nOverview\n\nFollowing the positive experience of last year’s workshop\, we aim to continue fostering open discussions\, hands-on collaboration\, and community-driven progress in chemical ontologies and semantic infrastructure. \n\n\nTo help us shape the program according to the needs and interests of the community\, we would greatly appreciate your feedback. In particular\, we would be interested to hear: \n\n\n\n\n\n\nWhich topics\, discussions\, or breakout sessions from the 2025 workshop you would like to see continued or deepened\nAny specific ontology-related challenges\, use cases\, or infrastructure topics you would like to address\nSuggestions for formats\, discussion themes\, or collaborative sessions\n\n\n\n\n\n\nYour input will directly help us design a workshop program that reflects the priorities and interests of the Ontologies4Chem community. Please send your ideas and suggestions to ontologies@nfdi4chem.de. \n\n\nFurther details\, including registration information and the preliminary program\, will follow in the coming months. You can also check out the nfdi4chem event webpage: https://nfdi4chem.de/event/5th-ontologies4chem-workshop/. \n\n\nWe very much hope to welcome you again in Limburg in November 2026. \nBest regards\,the Ontologies4Chem Workshop Organization Team URL:https://www.psdi.ac.uk/event/5th-ontologies4chem-workshop/ LOCATION:Dom Hotel Limburg\, Limburg\, Germany CATEGORIES:Workshop END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/London:20261125T120000 DTEND;TZID=Europe/London:20261126T153000 DTSTAMP:20260728T171450Z CREATED:20260727T132602Z LAST-MODIFIED:20260728T171450Z UID:37663-1795608000-1795707000@www.psdi.ac.uk SUMMARY:PSDI Showcase 2026 DESCRIPTION:Save the Date for our Showcase event!\n👉Register your interest now!  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 🗓 Date: 25-26 November 2026 📍Venue: Leonardo Royal Hotel Southampton Grand Harbour\, West Quay Road\, Southampton SO15 1AG 🕘 Time: 12:00 (Day 1) – 15:30 (Day 2)💵 Cost: Nominal fee to be charged (~£50) \n \n \n \n \n \n About the Event\nJoin us for the second Physical Sciences Data Infrastructure (PSDI) Showcase\, taking place in Southampton on 25-26 November 2026. This two-day event will bring together researchers\, technical specialists\, data professionals\, infrastructure providers\, funders and policymakers with an interest in research data\, digital infrastructure\, AI and machine learning\, open science\, and data-intensive physical sciences research. \nThe Showcase will provide an opportunity to explore the latest PSDI developments\, discover new tools\, services and datasets\, share experiences across the community\, and contribute to discussions that will help shape the future direction of PSDI. \nWhether you are already engaged with PSDI or are interested in learning more about how digital research infrastructure can support physical sciences research\, this event offers an opportunity to connect with colleagues from across the UK\, exchange ideas and explore opportunities for collaboration. \n \n \n \n \n \n Who Should Attend?\nThe Showcase is intended for anyone with an interest in data-enabled physical sciences research\, including: \n\nResearchers\, academics and research group leaders\nResearch software engineers and technical specialists\nData stewards and data managers\nInfrastructure and platform providers\nLibrarians and research support professionals\nFunders\, policymakers and strategy leads\nIndustry partners interested in data-intensive research and innovation\n\n \n \n \n \n \n Why Attend? \nResearch is becoming more data-intensive\, collaborative\, and open which brings new opportunities and new challenges.  This Showcase is your opportunity to:  \n\nSee PSDI in action – discover PSDI resources to support research\nBuild your network – connect with like-minded researchers\, collaborators and infrastructure providers across the UK \nContribute your perspective – help shape the direction of PSDI’s future resources \nTake practical knowledge back to your team – and accelerate your next data-intensive project\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \nWe look forward to welcoming you to Southampton as we bring together the UK’s physical sciences community to explore\, share and shape the future of research data infrastructure. \nRegistration details and programme updates will be announced in due course. In the meantime\, please register your interest and join the PSDI mailing list to stay informed. \n \n Revisit PSDI Showcase 2025 URL:https://www.psdi.ac.uk/event/showcase-2026/ LOCATION:Leonardo Royal Hotel Southampton Grand Harbour\, West Quay Rd\, Southampton\, Hampshire\, SO15 1AG\, United Kingdom CATEGORIES:Large Event ATTACH;FMTTYPE=image/png:https://www.psdi.ac.uk/wp-content/uploads/2026/07/Showcase-2026-website-banner.png END:VEVENT END:VCALENDAR