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4TU Energy grant for Bijoy Bera for research (with UT) on Magneto-Iono-caloric Heat Pumps

Recently, dr. Bijoy Bera (Interfacial Physis Lab/Transport Phenomena Section) received, together with his collaborator dr. Keerthivasan Rajamani (University of Twente), the 4TU Energy grant, which promotes collaborative efforts among the four technical universities of NL to address the energy issues/future of this country. ChemE News sat down with Bijoy for more info. What is a heat pump? Why does NL need them? What’s wrong with the current heat pumps? A pump is a device where we put (electrical) energy to obtain work. Heat pump is where work (together with heat from a source) is supplied to a device to obtain heat, very useful for efficient heating of households. The heating demand for the built environment in the Netherlands alone is expected to be 333 PJ of energy in 2030. As of 2022, 82% of Dutch households still use natural gas for heating. (Traditional vapor compression system) Heat pumps are being increasingly used in Dutch households (if you ask me, not as much as should be), but the major problem is their efficiency, which tends to hover around 40%-50%. How is your research going to improve the situation? Dr. Rajamani (UT) and I are going to investigate, model and design a new type of heat-pump: Magneto-iono-caloric heat pumps. We plan to use magnetic ionic liquids where low strength magnetic field can be used to bring the melting point of a salt down to below the room temperature. The heat of solidification/crystallization of the salt can then subsequently be used as the heat source of the heat pump, which will lead to higher Carnot efficiency. What is the nature of the collaboration in this project? Keerthi (Dr Rajamani) is an expert in magneto-caloric devices where magnetic fields are applied to change the energy input/output of a system. I will bring my expertise of ionic manipulation of energy interactions in a system. Keerthi and I were chatting about our areas of interest about a year ago, and we realized that by combining these two points of interest, we can come up with something unique! Dr. Bijoy Bera Why is this research important? Will this grant be sufficient in that quest? There is right now a strong direction in the Dutch research landscape to contribute to new forms of energy and how to increase efficiency in processes producing these forms of energy. However, classic thermodynamic processes (such as a heat pump) are often overlooked. This grant is a small but timely incentive for us to start the work, and hopefully our results will inspire colleagues to join us and create a platform for something bigger. Sounds interesting! When can we buy magneto-iono-caloric heat pumps for our houses? Not for a little while, unfortunately! But we are talking about years not decades! And once we can make it, it will open many doors for us, not only for household heating, but for renewed faith in novel energy systems!

Understanding the learning process: machine learning and computational chemistry for hydrogenation

Machine learning is being mentioned all around, but can it be applied to modelling homogeneous catalysis? Researchers from TU Delft together with Janssen Pharmaceuticals published an extensive study accompanied by one of the biggest datasets on rhodium-catalyzed hydrogenation in Chemical Science trying to answer this question. Adarsh Kalikadien Evgeny Pidko For more than half a century, Rhodium-based catalysts have been used to produce chiral molecules via the asymmetric hydrogenation of prochiral olefins. The importance of this transformation was acknowledged by a Nobel prize given to Noyori and Knowles for their contributions in this field. Nowadays, asymmetric hydrogenation catalysts are widely used in the pharmaceutical industry, numerous chiral ligands are available to tackle a wide range of prochiral substrates and the reaction mechanism has been extensively studied. Consequently, one would expect that finding the best catalyst for the asymmetric hydrogenation of a new substrate is a trivial task. Unfortunately, this is not the case and a tedious and costly experimental screening is still needed. Adarsh Kalikadien and Evgeny Pidko from TU Delft together with experts in high-throughput-experimentation, data science and computational chemistry from Janssen Pharmaceutica in Belgium decided to investigate whether a well-trained machine could do the job. To their surprise, the machine was actually not able to learn as much as they expected. The idea was to set up a simple model reaction with a well-known rhodium catalyst. Based on the experimental data generated by the high-throughput experimentation team of Janssen, a computational dataset was built to which multiple machine learning models were applied. “We digitalized the 192 catalyst structures and represented them with features of various levels of complexity for the machine learning models,” says Kalikadien, a PhD student in Pidko’s group. "The interesting thing was that all the simpler models, including the random model, showed similar performances as the expensive variant, which intrigued us. It turned out to be an early indication that the machine was not really learning anything useful.” "One of our conclusions was, when tested more extensively, that for an out-of-domain modeling approach, it doesn't matter what representation you put in”. Nevertheless, although the team was not able to build an accurate model, their study was worth publishing. The publication process went relatively smoothly. “Although the first journal we contacted rejected our submission as too specialized, the high-impact journal Chemical Science saw the value of this work. Not many researchers are interested in just seeing the R2 value of a model and then having no possibility to use it, they are probably interested in an in-depth analysis like ours. So we were able to submit our data, code and even interactive figures there for everyone to use.” At the moment there is a big incentive for publishing negative data in order to help the community to assess the true added value of machine learning, since models trained on mainly positive results tend to become very biased. "We made everything open source," says Kalikadien. "Not only is all the data accessible, but we also offer the code including packages and instructions, so that anyone who is interested can do the same type of research." In this way, they have published one of the largest datasets of a certain type of hydrogenation reaction. What's next? "Our representation of the catalyst wasn't as meaningful for the machine learning models as we had hoped, so we are now looking for a representation that may be less simplified but still as simple as possible," says Kalikadien. "Creating a digital representation of your catalyst should not cost way more money than running the actual experiment, so we are trying to incorporate more information from the reaction mechanism into the model without making it too extensive. A more dynamic and hopefully more informative version of the representation." Read the publication Adarsh Kalikadien, Cecile Valsecchi, Robbert van Putten, Tor Maes, Mikko Muuronen, Natalia Dyubankova, Laurent Lefort and Evgeny A. Pidko

Bipolar membranes for intrinsically stable and scalable CO2 electrolysis

The energy transition requires technology to supply sustainable carbon-based chemicals for hard-to-abate sectors such as long-distance transport and plastic manufacturing. These necessary hydrocarbon chemicals and fuels, responsible for 10-20% of the global greenhouse gas emissions, can be produced sustainably by the electrolysis of captured CO 2 using renewable electricity. Currently, the state-of-the-art CO 2 electrolyzers employ anion exchange membranes (AEMs) to facilitate the transport of hydroxide ions from the cathode to the anode. However, CO 2 is crossing the membrane as well, resulting in a loss of reactant and unfavourable anode conditions which necessitates the use of scarce anode materials. Bipolar membranes (BPMs) offer an alternative that addresses the problem of CO 2 crossover but still requires research to match the product selectivity of AEM-based systems. Our perspective, a collaboration between groups of David Vermaas, Tom Burdyny and Marc Koper, published in Nature Energy, assesses the potential of BPMs for CO 2 electrolysis by looking at CO 2 utilization, energy consumption, and strategies to improve the product selectivity. Abstract CO 2 electrolysis allows the sustainable production of carbon-based fuels and chemicals. However, state-of-the-art CO 2 electrolysers employing anion exchange membranes (AEMs) suffer from (bi)carbonate crossover, causing low CO 2 utilization and limiting anode choices to those based on precious metals. Here we argue that bipolar membranes (BPMs) could become the primary option for intrinsically stable and efficient CO 2 electrolysis without the use of scarce metals. Although both reverse- and forward-bias BPMs can inhibit CO 2 crossover, forward-bias BPMs fail to solve the rare-earth metals requirement at the anode. Unfortunately, reverse-bias BPM systems presently exhibit comparatively lower Faradaic efficiencies and higher cell voltages than AEM-based systems. We argue that these performance challenges can be overcome by focusing research on optimizing the catalyst, reaction microenvironment and alkali cation availability. Furthermore, BPMs can be improved by using thinner layers and a suitable water dissociation catalyst, thus alleviating core remaining challenges in CO 2 electrolysis to bring this technology to the industrial scale. Go to the publication Kostadin Petrov Christel Koopman David Vermaas Tom Burdyny Siddharta Subramanian

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Hoe systeemveiligheid Machine Learning systemen veiliger kunnen maken in de publieke sector

Machine Learning (ML), een vorm van AI waarbij patronen worden ontdekt in grote hoeveelheden data, kan heel handig zijn. Het wordt steeds vaker gebruikt, denk aan chatbot Chat GPT, voor gezichtsherkenning of aan spraaksoftware. Maar er zijn ook zorgen over de toepassing van ML systemen in de publieke sector. Hoe voorkom je dat het systeem bijvoorbeeld discrimineert, of op grote schaal fouten maakt met negatieve effecten op burgers? TU Delft wetenschappers, waaronder Jeroen Delfos, onderzochten hoe lessen uit de systeemveiligheid kunnen bijdragen aan een veiliger ML systeem in de publieke sector. ‘Beleidsmakers zijn druk met het bedenken van maatregelen om negatieve effecten van ML tegen te gaan. Uit ons onderzoek blijkt dat zij veel meer kunnen leunen op bestaande concepten en theorieën die hun waarde al hebben aangetoond in andere sectoren,’ zegt Jeroen Delfos. Jeroen Delfos Leren van andere sectoren In het onderzoek gebruikten de onderzoekers concepten van systeemveiligheid en systeemtheorie om de uitdagingen van het gebruik van ML systemen in de publieke sector te beschrijven. Delfos: ‘Concepten en tools uit de systeemveiligheidsliteratuur worden al veel gebruikt om de veiligheid van bijvoorbeeld de luchtvaart te ondersteunen, onder andere door ongelukken te analyseren met systeemveiligheidsmethodes, maar binnen het veld van AI en ML is dit nog niet gebruikelijk. Door de systeemtheoretische blik bekijken we veiligheid niet alleen als een resultaat van hoe de techniek werkt, maar juist als een resultaat van complexe set aan technische, sociale en organisationele factoren.’ De onderzoekers interviewden professionals uit de publieke sector om te zien welke factoren worden onderkend, en welke nog onderbelicht zijn. Bias Op een aantal punten kan terrein worden gewonnen om ML systemen in de publieke sector veiliger te maken. Zo wordt bijvoorbeeld bias in data nog vaak als een technisch probleem gezien, terwijl de oorsprong van die bias ver buiten het technische systeem kan liggen. Delfos: ’Denk dan bijvoorbeeld aan de registratie van criminaliteit. In buurten waar de politie vaker surveilleert wordt logischerwijs meer criminaliteit geregistreerd, waardoor deze buurten overgerepresenteerd worden in criminaliteitscijfers. Een ML systeem dat geleerd wordt patronen te ontdekken in deze cijfers zal deze bias gaan herhalen of zelf versterken. Het probleem zit echter in de manier van registreren, en niet in het ML systeem zelf.’ Risico’s verminderen Volgens de onderzoekers doen beleidsmakers en ambtenaren die bezig zijn met de ontwikkeling van ML systemen er goed aan om concepten van systeemveiligheid mee te nemen. Zo is het aan te raden om bij het ontwerpen van een ML systeem vooraf te identificeren wat voor ongelukken men wil voorkomen. Verder is een les vanuit systeemveiligheid, bijvoorbeeld in de luchtvaart, dat systemen in de praktijk de neiging hebben om over tijd steeds risicovoller te worden, omdat veiligheid steeds ondergeschikter raakt aan efficientie zolang er geen ongelukken gebeuren. ‘Het is dus belangrijk dat veiligheid een terugkomend onderwerp is bij evaluaties en dat de eisen voor veiligheid worden gehandhaafd’, aldus Delfos. Lees het paper over dit onderzoek.

Innovatief onderwijs ondersteunt duurzaam bouwen

Innovatief onderwijs ondersteunt duurzaam bouwen Op 17 september lanceerde TU Delft een nieuw initiatief om duurzame bouwpraktijken te integreren in het Nederlandse beroepsonderwijs. Dit project brengt docenten van verschillende MBO-instellingen samen met TU Delft docenten om de nieuwste kennis op het gebied van duurzaam bouwen uit de wisselen. Vorige week vond op de TU Delft-campus bij de Green Village de aftrap plaats. Tien docenten van het MBO kwamen daar bijeen met de docenten van de TU Delft die de onlinecursus Sustainable Building with Timber verzorgen. Onderwijs met impact Van september tot december 2024 volgen de MBO-docenten de MOOC als deelnemers. Ze bekijken de video’s, maken opdrachten en nemen deel aan online sessies onder begeleiding van de TU Delft-docenten en een onderwijsspecialist. Vanaf december ligt de focus op het ontwikkelen van flexibele en open leermaterialen, specifiek voor het MBO. Een domino-effect Door docenten de juiste kennis en middelen aan te bieden, ondersteunt dit initiatief de overgang naar duurzamere bouwpraktijken. Dankzij de samenwerking met Leren voor Morgen en de MBO Raad wordt deze kennis breder gedeeld, waarmee toekomstige professionals in de bouwsector kunnen bijdragen aan een duurzamere toekomst. Het project richt zich aanvankelijk op een klein aantal MBO-instellingen, maar de impact op termijn zal veel breder zijn. De ontwikkelde leermaterialen zullen via de docenten toekomstige generaties bereiken en daarmee de impact van dit project versterken. Sustainable Building with Timber MOOC Cursus details Een leerproces in twee richtingen Het project staat voor wederzijds leren. MBO-docenten krijgen toegang tot up-to-date kennis over bouwen met hout, terwijl TU Delft profiteert van de praktijkervaring die de docenten inbrengen. Deze uitwisseling verrijkt zowel het beroepsonderwijs als het onderzoek en onderwijs van de universiteit. Open leermaterialen voor blijvende verandering Een belangrijk doel is om open en flexibele leermaterialen te ontwikkelen, die docenten kunnen aanpassen aan de specifieke behoeften van hun scholen en studenten. Zo draagt het initiatief bij aan bredere verspreiding van duurzame bouwtechnieken. Met dank aan Met grote dank aan alle betrokkenen die dit initiatief mogelijk hebben gemaakt. Samen bouwen we aan een duurzamere toekomst.

Three Students Nominated for the ECHO award

Three TU Delft students have been nominated for the ECHO Award 2024. The ECHO award is awarded to students with a non-western background who are actively engaged in society. Sibel, TJ and Pravesha talk about their background their nomination. The finalists will be selected on September 27th. Sibel Gökbekir How has your background influenced your academic journey? As a woman with Turkish roots, my academic journey has been about more than just pursuing degrees in engineering and law; it’s been about consistently advocating for the diverse needs of women and multicultural groups, ensuring their voices are heard in important decisions. This is why I actively contributed to different board positions at TU Delft, working to promote inclusivity and equality. My background inspired me to explore how engineering, law, and social justice intersect, particularly in empowering marginalised communities. I chose to study energy transitions and human rights to contribute to a fairer, more inclusive World. How have you turned this into contributions to society? I’ve dedicated my academic and personal life to promoting diversity and inclusion. As a youth ambassador for Stop Street Harassment, I aimed to create safer spaces for women and minorities because I believe everyone has the right to feel free and safe in society. Through the Turkish Golden Tulip Foundation, I advocated for vulnerable communities in earthquake relief. Additionally, I founded an initiative for migrant students in Rotterdam-South and I have been committed to improving educational opportunities for secondary school students with a migration background. Next, I gave guest lectures across the Netherlands to educate the younger generation about climate change and equitable energy transitions, emphasising the importance of a fair transition for all communities. What does it mean for you to nominated to the ECHO award? I feel very honoured to have been nominated on behalf of TU Delft. My commitment to community engagement is part of who I am, and therefore the ECHO Award is more than just a recognition; It offers me an opportunity to further expand my contributions to a more inclusive society. As an ECHO Ambassador, I plan to expand my efforts in promoting equality and sustainability, while inspiring others to take action for a more equitable World. TJ Rivera How has your background influenced your academic journey? My background as a Filipino in a Dutch-speaking bachelor’s programme made my academic journey both challenging and enriching. Being gay in a male-dominated field like Architecture, where most role models were heteronormative men, added another layer of difficulty. It was intimidating to not see people like me represented. However, this experience fuelled my belief that systems can and should be challenged, changed, and updated. I aimed to bring a fresh perspective, advocating for greater diversity and inclusivity in the field. How have you turned this into contributions to society? I translated my personal challenges into tangible contributions by advocating for inclusivity within architecture. Together with like-minded individuals, I began exploring the intersection of identity, sexuality, and architecture, and collaborated with my faculty’s diversity team to raise awareness. As I became known for my work with the queer community, I saw an opportunity to create lasting change. I co-revived ARGUS, the once-inactive study association for the Master of Architecture, which now serves as a platform to discuss and address issues of diversity within the field. This initiative continues to foster a more inclusive academic environment. What does it mean for you to be nominated to the Echo award? Being nominated for the ECHO Award is a significant milestone in my journey to expand my mission beyond the confines of my faculty. This national platform provides the opportunity to raise awareness and advocate for social justice on a larger scale. I believe students are key to driving change, and my focus is on amplifying the voices of the queer community, which is often overlooked. The ECHO Award will enable me to form partnerships with organizations and universities, further promoting diversity, inclusivity, and equality. It’s a chance to create broader, tangible change, addressing the needs of those who often go unheard. Pravesha Ramsundersingh How has your background influenced your academic journey? As a woman in STEM (Science, Technology, Engineering, and Mathematics), my background has been a powerful motivator to challenge gender disparities within Computer Science. Experiencing firsthand the underrepresentation of women in this field, I have been driven to not only excel academically but also become an advocate for diversity. Through leadership roles in the Faculty and Central Student Councils, I’ve focused on creating an inclusive environment that supports women and minority students, ensuring that everyone has the opportunity to succeed. How have you turned this into contributions to society? I’ve translated my experiences into actionable contributions by actively advocating for DEI at TU Delft. I ensured sexual education and consent training for 3,000 freshmen students, and I led initiatives like the Social Safety Initiatives Conference alongside the Dutch National Coordinator against Racism and Discrimination. In my student governance roles, I pushed for policies that address gender discrimination and social safety concerns, creating a more supportive environment for students of all backgrounds to thrive in both academic and social spaces. What does it mean for you to nominated to the ECHO award? Being nominated for the ECHO Award is an incredible honour that highlights the importance of the work I have done to promote DEI. It inspires me to continue advocating for systemic change in the tech industry and academia. This nomination reaffirms my commitment to driving equity in STEM, ensuring that future generations have more inclusive opportunities. It also motivates me to keep pushing boundaries and empower others to take action for a more just and equal society. The ECHO Award Every year ECHO, Center for Diversity Policy, invites colleges and universities to nominate socially active students who make a difference in the field of Diversity & Inclusion for the ECHO Award 2024. The ECHO Award calls attention to the specific experiences that students with a non-Western background* carry with them and the way they manage to turn these experiences into a constructive contribution to society. Winners are selected by an independent jury and may attend a full-service Summercourse at UCLA in the United States in 2025. Read more: ECHO Award - ECHO (echo-net.nl)