Research in the CRN Lab
We investigate how Chemical reaction networks (CRNs) can become capable of functions akin artificial intelligence. To this end, we work on three synergistic research lines in the CRN lab, focusing on how CRNs can i) memorize, ii) communicate, and iii) self-organize. In greater detail, we aim to; |
i) | understand the driving force that enables CRNs to temporarily memorize past events, a prerequisite for (artificial) intelligence. As a starting point we demonstrated how gradients drive an enzymically-driven autocatalytic network to display history-dependent behaviors. |
ii) | establish a platform for local biochemical feedback in CRNs. We recently demonstrated how reactive surfaces (that built on polylysine-coated surfaces) enable CRNs with the capacity of signal transduction. We also explore if such systems could provide the foundation for systems with biosensing capabilities. |
iii) | use hypergraphs to generalize how reactions self-organize into CRNs. We are currently developing a novel mathematical framework that translates synthetic CRNs into graphs. This work builds on my expertise in the synthesis of out-of-equilibrium networks and collaboration with Dr. Stegehuis (expert in graph analyses). |
Impressions | |
December 6, 2024. NWA Research grant awarded for a consortium named "PRELIFE-Pathways, Reactions, and Environments leading to LIFE". In this interdisciplinary research consortium, led by Professor Inge Loes ten Kate (Utrecht University), Albert Wong will collaborate with Rick Quax (University of Amsterdam) to develop a so-called hypergraph model for chemical reaction networks. The consortium is part of the Origins Center and consists of scientists from sixteen universities and research institutes across the Netherlands, along with experts in science communication and education. The interview with Albert Wong by UToday can be found here & full list of involved scientists and institutes can be found here.
| September 14, 2023. Albert Wong delivered the opening talk of 2023 seminars at Life-Inspired Hybrid Materials, LIBER (2023, Espoo, FIN). "How can chemistry play a role in advancing future materials?" A big thank you to Hang Zhang, as well as Olli Ikalla and Arri for hosting me at Aalto University in wonderful area of Espoo!
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December 3,4, 2024. CRN team at CHAINS 2024: Proud to see Yanna, Éverton, Hazal & Dmitrii all presenting their work, with Éverton also invited to give a talk in the parallel sessions. After the post-covid hybrid (2022) and IUPAC (2023) editions, we finally managed to go to CHAINS as a team for the first time: Always good to be back at Veldhoven to share our enthusiasm for chemistry!
| December 28, 2023. Our paper (#12) in ChemSystemsChem is selected as Cover Art! The image shows a microfluidic channel with multilayer polylysine surfaces, which provide the potential to bestow an acid-base equilibrium with the capacity of signal transduction. Read the full text of the Research Article at 10.1002/syst.202300030, and our cover profile at 10.1002/syst.202300052. Cover design by Niels van der Velde (University of Twente, NL)
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Temporal and local control over feedback systems
Methods that enable a balance between (often opposing) feedback loops and maintain out-of-equilibrium conditions are essential in the de novo design of CRNs. We recently demonstrated how gradients drive CRNs to display history-dependent behaviors (Fig. a). Under continuous flow, Tg acts as a fuel for generating the catalyst Tr, creating a positive feedback loop (+), and its process is regulated by the inhibitor, which can suppress the activation of autocatalysis (-). The incorporation of an inhibitor into the network was crucial as it enables a controlled release of Tr, giving rise to behaviors such as hysteresis and adaptation. We, thus, showed that CRNs can temporarily memorize past events (#10), a prerequisite for (artificial) intelligence. In another work, we reported how reactive surfaces could create CRNs with the capacity to transduce, delay, and perturb chemical signals (#12). Fig. b depicts an acid-base equilibrium which can be perturbed by two opposing processes, one of which is immobilized on a surface. Fixating poly-l-lysine (PLL) on the surface allowed us to work under flow so that the PLL can exert its function (in this case, binding/ releasing protons) on the liquid-surface interface. Our demonstrations include write and read operations to encode ‘CRN@UT’ (my at research group at the University of Twente).
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Fig. Examples of chemical systems from the CRN lab: A (a) gradient-driven autocatalytic network (#10), and (b) surface-driven competing activation network (#12). |
background
Intelligent behavior, similar to other complex behaviors, can emerge under out-of-equilibrium conditions. In my first research article, published in Nature Chemistry (2015, #1), I demonstrated that oscillatory behavior (i.e., a hallmark of life, and a phenomenon that can only sustain under out-of-equilibrium conditions) could be rationally designed. Its ground-breaking character is emphasized by the high FCWI (6.5) and my publications in JACS (2015, #2, 2017, #3, 2017, #6, 2019, #7) and Nature (2023, #11) that further laid out the underlying principles. Overall, I established how an integral approach involving chemical synthesis, microfluidic fabrication, and mathematical modelling is required to design chemical systems with complex behaviors (#5). Among other demonstrations, this approach formed the foundation for establishing how competing reactions can become cooperative (#6, #7), which could translate into the design of an autonomous periodic catalyst (#11).