ABSTRACT Living cells harbor numerous membraneless organelles (MOs), which are dynamic protein/nucleic acid assemblies responding to specific physicochemical triggers. Liquid-liquid phase separation (LLPS) plays a crucial role in their formation and activity. Inspired by the natural MOs that maintain their individual identities, this work presents a bioengineering strategy to generate LLPS-driven, isochemical MO populations using surfactant-like peptides that stabilize the MO interface. The result is highly stable, monodispersed, sub-µm-sized MO populations, which are not only capable of compartmentalizing synthetic cells but also provide superior environments for enzymatic reactions. This is achieved using pH-responsive elastin-like polypeptides (PREs) as MOs and formulating an amphiphilic PRE-based peptide to stabilize the MO interface. Relative abundance of the surface-active peptide, as well as the rate of pH change, allows direct control over the MO size. Encapsulating these components within synthetic vesicles using a microfluidic platform leads to on-demand multi-compartmentalization via an external pH trigger. Lastly, a functional consequence of the acute size control is shown through a phosphatase reaction, where the highest reaction rate is observed in size-controlled MOs when compared to dilute environments and surfactant-free MOs. The presented strategy provides a new avenue for designing programmable MOs and thus achieve functional compartmentalization within synthetic cells.

Plant-derived biopolymers may become sustainable alternatives to fossil-based polymers, yet their poor material performance has so far limited their adoption. Plant-derived biopolymers require careful control over the micro- and nanostructures to tune their mechanical behavior. Silk-spinning as done by spiders is one such mechanism, which combines liquid-liquid phase separation (LLPS) and mechanical force to drive β-sheet formation from α-helical precursor proteins to achieve high strength fibers. We develop a similar processing route combining coacervation resulting from LLPS and mechanical force to enhance maize-derived zein into what we call a "plantymer" material, yielding films and fibers with superior mechanical performance. LLPS of zein is triggered by water-ethanol solvent control, resulting in a protein-rich phase that retains fluidity to enable the shear-induced fabrication of films and fibers, mimicking the strengthening mechanism of silk. The resulting materials demonstrate a rigidity comparable to silk and even exhibit good oxygen and moisture barrier properties. We demonstrate the efficacy of plantymer films in preventing banana browning. Our work highlights how nature-inspired polymer processing routes can lead to simple-yet-effective ways of producing plant-derived biopolymer materials with enhanced performance.

As central organelles for lipid and energy homeostasis in cells, lipid droplets (oleosomes) consist of a neutral lipid core - mainly triacylglycerols and sterol esters. Crucial to the droplet stability and dynamics, the droplet boundary is decorated by a dense phospholipid monolayer enriched in phosphatidylcholines (PCs) as well as surfactant-like proteins, which in plant cells, are predominantly oleosins (OLs). The monolayer keeps plant lipid droplets stable for years throughout seed dormancy yet delicately destabilizes them during germination to ensure the targeted release of their stored lipids. The respective contributions of PCs and OLs to the fine metastability of lipid droplets remain insufficiently understood. Here, we address this question using reconstituted oil-in-water emulsions stabilized by purified OLs and PCs in controlled microfluidic systems, enabling variation of interfacial OL:PC ratios and environmental conditions such as pH and ionic strength. Aided by super-resolution microscopy and dilatational rheology, we reveal that oleosins form a dense, elastic interfacial network protecting droplets from coalescence. The presence of PCs decreases the network density and interfacial elasticity, while their effect on coalescence resistance is condition-dependent. These findings indicate complementary roles of the two interfacial agents: OLs function as primary stabilizers that resist coalescence and provide interfacial mechanical robustness, whereas PCs reduce interfacial tension and attenuate the robustness by disrupting the OL organization. In conclusion, our reductionist approach provides insights into the metastable nature of seed lipid droplets by isolating the distinct interfacial-mechanical contributions of OLs and PCs and offers a basis for designing bioinspired emulsions with tunable and stimuli-responsive stability.

High‐throughput computational screening is a powerful approach in accelerating the identification of highly selective and stable catalysts. However, it is often hindered by lack of generalized descriptors and the complexity of handling numerous multidentate adsorption configurations. In this study, we propose a computational framework integrating graph theory and python‐based databasing tools with robust catalytic descriptors to enable high‐throughput screening of alloys for nonoxidative propane dehydrogenation. We derive mechanistic Brønsted–Evans‐Polanyi (BEP) correlations for C─H and C─C bond breaking, highlighting the role of metastable binding configurations in transition states involving more than three surface atoms. Although activity and stability descriptors exhibit strong scaling, these descriptors are uncorrelated, enabling construction of a pareto‐optimal line identifying alloys with the best balance between activity and selectivity. Known optimal catalysts, including PtZn, PdZn, PtSn, and PdIn, lie on this pareto‐optimal line validating the framework. Furthermore, Ir and Rh, typically known for hydrogenolysis, can be engineered for high selectivity by site‐isolating active ensembles with high promoter compositions. Experimental validation confirms that Ir 1 Sn 1 remains highly stable and selective over 15 h. Overall, our approach highlights the power of generalized descriptors combined with high‐throughput screening and experimental benchmarking to extract key mechanistic insights and computationally design novel catalysts.

Living organisms use biomolecular condensates to respond to dynamic environments and create functional materials with complex architectures. Exploring such phase-separated systems beyond the naturally occurring scenarios may offer valuable insights for emergent synthetic biosystems. Here, we report the self-assembly behavior of a short, disordered peptide sequence (termed CT45) derived from a protein present in the bioad-hesive system of tick ectoparasites. We show that CT45 spontaneously accumulates at polar-nonpolar interfaces, and further undergoes liquid-liquid and liquid-to-solid phase transitions to create mechanically stable structures. When encapsulated within vesicles and presented with a stable oil-water interface, CT45 rapidly forms solid shells, which can be reinforced by up-concentrating the material through osmotic imbalance. Unex-pectedly, when presented with a transient acetone-water interface, CT45 condenses at the evaporating interface and forms interconnected, porous mesoscopic scaffolds. The underlying mechanism is found to be the amphiphilic nature of CT45 leading to in-terfacial accumulation, enhancing intermolecular π -based interactions to trigger phase transitions. The micron-sized shells exhibit appreciable mechanical strength and the porous scaffolds present a highly stable platform capable of retaining molecules. In conclusion, the presented condensate-based microscopic and mesoscopic scaffolds hold significance in customizable condensate architectures, with potential applications in biomedical engineering and synthetic biology. ### Competing Interest Statement The authors have declared no competing interest. Dutch Research Council, https://ror.org/04jsz6e67, OCENW. KLEIN. 465

Living cells orchestrate a myriad of biological reactions within a highly complex and crowded environment. A major factor responsible for such seamless assembly is the preferential interactions between the constituent macromolecules, that can drive demixing to produce coexisting phases and thus provide dynamic intracellular compartmentalization. However, the way multiple-phase separation phenomena, occurring simultaneously within the cytoplasmic space, influence each other is still largely unknown. Here, we show that the interplay between segregative and associative phase separation within cell-mimicking confinements can lead to rich dynamics between multiple phases and the lipid boundary. Using on-chip microfluidic systems, we encapsulate the associative and segregative components and externally trigger their phase separation within cell-sized vesicles. We find that segregative phases create microdomains and tend to dictate the fate of associative components by acting as molecular recruiters, membrane-targeting agents, and initiators of condensation. The obtained multiphase architecture provides an isolated microenvironment for condensates, restricting their molecular communication as well as diffusive motion, and can further lead to global shape transformation of the confinement itself in the form of wetted, hierarchical domains at the lipid membrane. In conclusion, we propose segregative phase separation as a universal condensation regulation strategy by managing their molecular distribution, process initiation, and spatial localization, including membrane interaction. The presented interplay between the two phase separation systems suggests a distinct design principle in constructing complex synthetic cells and controlling the behavior of artificial membraneless organelles within.

Particle-stabilized emulsions and foams, commonly referred to as Pickering emulsions and foams, offer superior stability and greater functional versatility compared to their conventional polymer- or surfactant-stabilized counterparts, bestowing them with unique features. However, the understanding of particle adsorption dynamics, particle-droplet (or particle-bubble), and interdroplet (or interbubble) interactions during large-scale emulsification remains limited, hindering full exploitation of their potential. In recent years, on-chip microfluidic techniques have provided an effective experimental platform to precisely design and produce Pickering emulsions, and perform systematic analyses with regards to their formation, stability, and dynamics. This review examines recent microfluidic advances in the production and analysis of Pickering emulsions and foams. The discussion focuses on their underlying working principles and classification of the current methods based on the mechanisms by which particles are loaded onto interfaces. The review concludes with a critical evaluation of the advantages, limitations, and emerging applications of microfluidic strategies in this field. Looking ahead, this review highlights how the integration of microfluidics with advanced materials science and analytical tools is expected to open new opportunities for designing functional interfacial systems, enabling process scale-up, and translating Pickering systems into practical applications.

Advances in the theoretical understanding of electrochemical systems have, over the past decade, led to growing use of periodic Density Functional Theory (DFT) studies to treat a surprisingly large ensemble of electrocatalytic reactions, ranging from carbon dioxide electroreduction to oxygen evolution. Many such studies have employed simplified models of the electrochemical environment to determine reactivity trends across a broad space of catalytic materials, while other efforts have focused on developing detailed descriptions of electrochemical phenomena, such as the structure of electrochemical double layers, on model catalyst structures. An emerging challenge is to combine these approaches to ultimately enable theoretical design of electrocatalysts for reactions of significantly expanded chemical and materials complexity. In this talk, we begin by discussing how we develop and apply DFT-based methods to study the electrooxidation of ethanol and related oxygenated species on Pt surfaces. We show how explicit double layer models and ab initio molecular dynamics provide exciting insights beyond the traditional computational hydrogen electrode treatments, leading to improved descriptions of elementary reaction steps involving adsorption/desorption of reaction intermediates and proton-coupled electron transfer processes. By combining the aggregate results with detailed microkinetic models and explicit descriptions of adsorbate-adsorbate interactions, we further demonstrate how these effects can influence both the predicted overpotentials and the selectivities to acetic acid, acetaldehyde, and carbon dioxide. We conclude with some perspectives on how these insights may be used to enhance the search for improved oxygenate electrooxidation catalysts.

High-throughput screening of catalysts using first-principles methods, such as density functional theory (DFT), has traditionally been limited by the large, complex, and multidimensional nature of the associated materials spaces. However, machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of these spaces in a data-efficient manner, typically through active learning-based workflows. In this work, we combine such an active learning scheme with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). Specifically, we train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and utilize the model to make and improve predictions on ternary structures. To do so, we perform reduced optimization over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the manifold learning scheme known as Diffusion Maps. Inspired by statistical mechanics, we derive and apply a dropout-informed acquisition function to select ensembles from which to sample additional structures. During each iteration of our active learning scheme, a representative number of crystals that minimize the acquisition function is selected, their energies are computed with DFT, and our dGCN model is retrained. We demonstrate that both of our reduced optimization techniques can be used to improve predictions of the formation free energy, the target property that determines HEA stability, in the ternary alloy space with a significantly reduced number of costly DFT calculations compared to a high-fidelity model. However, the manner in which these two disparate schemes converge to the target property differs: the physics-based scheme appears akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both active learning schemes can be extended further to incorporate greater number of elements, surface structures, and adsorbate motifs.

Liquid-liquid phase separation of biomolecules is crucial for maintaining the functional organization in biological systems. Intrinsically disordered proteins are particularly prone to form phase-separated condensates in response to various physicochemical triggers. While the effect of ionic strength and temperature on phase separation dynamics have been studied extensively, the influence of pH is less explored. Here, we study a model glycine-rich protein present in the tick bioadhesive, given its capability to undergo phase separation. After confirming its disordered nature through spectroscopy, we investigated its pH dependence and underlying molecular mechanisms. Our findings reveal that pH significantly influences the protein hydrophobicity via ionic residues, driving notable variations in the coacervation behavior (propensity, progression) and in shaping the material properties (viscosity, interfacial activity) of the formed condensates. Given the ubiquitous presence of disordered proteins in biology, this study provides valuable insights about the broad implications of the pH-dependent behavior of intrinsically disordered proteins. ### Competing Interest Statement The authors have declared no competing interest.

Liquid-liquid phase separation (LLPS) of biomolecules is crucial for maintaining the functional organization in biological systems. Intrinsically disordered proteins are particularly prone to LLPS and form condensates in response to various physicochemical triggers. This work studies the influence of pH on the LLPS behavior and material properties of condensates. A glycine-rich protein present in the saliva and the resulting bioadhesive of tick ectoparasites is selected for the study, given its ability to undergo LLPS. After confirming its disordered nature through spectroscopy, the effect on LLPS dynamics over a wide pH range of the full protein and its two halves is investigated. By combining fluorescence microscopy, droplet evaporation, and tensiometry assays, the findings reveal that pH-dependent changes in the protein hydrophobicity drive striking variations in the coacervation behavior, including the propensity to phase separate and the underlying microstructure dynamics. Importantly, pH dictates the viscosity of condensates and can confer amphiphilic character to the peptides, making them interfacially active. Lastly, pH-dependent curcumin encapsulation by condensates is demonstrated, exhibiting their potential as drug-delivery agents. Given the ubiquitous presence of disordered proteins in biology, this study provides valuable insights about the broad implications of the pH-dependent manifestation of the material properties of protein condensates.

Precise molecular engineering of surfaces is critical for advancing biosensing, antifouling technologies, and smart material interfaces, yet current methods often suffer from uncontrolled orientation or require complex surface chemical modifications. Here, we report a modular protein-based platform that combines two key elements: (1) self-assembling B-M-E protein antifouling brushes composed of a solid-binding peptide (B), a multimerization domain (M), and an antifouling polypeptide (E). (2) Bioorthogonal SpyCatcher/SpyTag chemistry for precise post-assembly covalent immobilization of target molecules with site-specific control. We demonstrate high-efficiency conjugation on both gold and polystyrene surfaces using quartz crystal microbalance with dissipation (QCM-D) and fluorescence assays. This bioorthogonal strategy offers one-step surface coating without complex chemical modifications, tunable and stable protein immobilization, and universal substrate compatibility. Our post-assembly functionalization platform provides a versatile toolbox for creating functional protein coatings by suppressing non-specific binding, which minimizes background interference and improves detection sensitivity and specificity. This approach holds significant potential for applications such as point-of-care diagnostics and continuous monitoring devices.

Unwanted nonspecific adsorption caused by biomolecules influences the lifetime of biomedical devices and the sensing performance of biosensors. Previously, we have designed B-M-E triblock proteins that rapidly assemble on inorganic surfaces (gold and silica) and render those surfaces antifouling. The B-M-E triblock proteins have a surface-binding domain B, a multimerization domain M and an antifouling domain E. Many biomedical technologies involve organic (polymeric) surfaces where B-M-E triblock proteins could potentially be used. In this study, we computationally and experimentally investigate the assembly of B-M-E triblock proteins on polystyrene (PS) surfaces, using PS-binding peptides as a surface-binding block B. We used atomic force microscopy, dynamic light scattering, fluorescence microscopy and quartz crystal microbalance to test the antifouling coating functionality. We found that, like for inorganic surfaces, the B-M-E proteins with PS-binding peptides as B block, form homogeneous monomolecular layers on PS surfaces with good stability against PBS washing. The adsorbed protein layer fully prevents adsorption of fluorescently labeled bovine serum albumin to PS microfluidic chips. Similarly, no significant fouling was observed using quartz crystal microbalance when 1 % (v/v) or 10 % (v/v) human serum were used as foulants.

Tandem metal-metal oxide catalysts, where metallic and metal oxide active sites work synergistically to drive complex chemistries, have been shown to improve the catalyst stability, activity, and selectivity. Although experimental techniques have probed the active site structure of such catalysts, the key atomic features that drive structure evolution under synthesis and reaction conditions remain poorly understood. Here, we develop a computational framework to elucidate the chemical, geometric, and stoichiometric features of the tandem overcoated catalyst, Pt-InOxHy, in driving the Oxidative Propane Dehydrogenation (ODHP) reaction, integrating propane dehydrogenation (PDH) and Selective Hydrogen Combustion (SHC). Exploration of the chemical space of stable InOxHy phases on Pt relevant to the experimental conditions reveals that the pore formation of the ALD-deposited InOxHy catalyst results from the oxide destabilization on well-coordinated Pt-terrace sites and preferential decoration around under-coordinated Pt-step sites. Reaction mechanistic analysis of the Pt-InOxHy catalyst reveals a dual-site mechanism for SHC, where O* activates on Pt and subsequently forms OH* at the InOxHy sites, facilitating water formation and controlling overoxidation. Further, due to passivation of the under-coordinated Pt-step sites, the Pt-InOxHy surface exhibits similar PDH activity as that on a well-coordinated Pt-terrace surface, in addition to enhanced stability by destabilizing deep-dehydrogenated intermediates. These insights establish a structure-performance relationship of the Pt-InOxHy catalyst for ODHP chemistry, with key features being the extent of reducibility of the metal oxide and the sensitivity of the oxide structure to the oxygen chemical potential. This framework can be extended to other metal-metal oxide systems and complex reactions to develop next-generation tandem catalysts.

CRISPR-Cas systems are responsible for antiviral immunity of prokaryotic cells and have been repurposed as powerful genome-editing tools. Cell-free gene expression has been applied for the rapid characterization of CRISPR-Cas systems in microtiter plates. In vitro compartmentalization makes use of artificial microcompartments that individually act as bioreactors. Here, we performed cell-free reactions of CRISPR-Cas activity into microtiter plates, which we proceeded to encapsulate into double emulsion (DE) droplets generated by on-chip microfluidics. Emulsion droplets were screened for CRISPR-Cas activity based on relative fluorescence levels using a common cell sorter, and enrichment for the expected guide (g)RNA genotype was observed. Encapsulation of single gene copies per droplet is an important prerequisite for applying this technique to complex gene libraries. We show a proof-of-principle assay for efficient, compartmentalized gene amplification using magnetic microbeads. In conclusion, we demonstrate the feasibility of microfluidics-based, high-throughput, cell-free screening of CRISPR-Cas activity.

Particle-stabilized emulsions, also known as Pickering emulsions, have shown promise in areas that require long-term stability with minimum use of surfactants. While most work has focused on densely covered Pickering emulsions, such emulsions are known to retain stability even when the interfaces are sparsely covered with particles. Here, the formation, dynamics, and stability of poorly covered model Pickering emulsions are studied in a controlled manner by utilizing a microfluidic platform. The formed Pickering emulsions remain highly stable, over at least 12 h, even with a surface area coverage below 3%. By directly visualizing the droplet interface at various stages, the exceptional stability is attributed to the highly spatially heterogeneous distribution of adsorbed particles which exclusively form particle bridges at the contact point between the droplets. Remarkably, these bridges are assembled in the form of crowns between the droplet interfaces, as visualized by confocal microscopy. The assembly behavior of the adsorbed particles in response to hydrodynamic forces and the formation of non-uniform particle distribution are discussed by analyzing the different forces present during emulsification, corroborated by numerical simulations. In conclusion, using a lab-on-a-chip approach, this work provides further understanding toward the fabrication of Pickering emulsions via preferential interfacial localization of particles.

Lipid-based vesicles are widely used, minimalistic model containers for in vitro reconstitution of biological systems and engineering synthetic cells. These containers provide a micro-chassis to encapsulate biomolecules and study biochemical interactions. Liposomes are often the most sought-after vesicles owing to their cell-mimicking nature, and numerous bulk and on-chip methods exist for their production. However, exploring the scope of synthetic containers, both in terms of the alternative lipid assemblies as well as newer production methods is useful for expanding the toolbox for synthetic biology. In this paper, we report the development of an electrospray-based technique, which we term "ATPS-templated lipid assemblies via electrofusion of SUVs" (ATLAES), to form lipid-based vesicles. Using an aqueous two-phase system (ATPS), free of organic solvents, we demonstrate efficient formation of microscopic vesicles stabilized via interfacial lipid assembly. Interestingly, the formed vesicles exhibit a nebulous and disordered, but highly stable coating of lipids, and tend to form interconnected vesicle populations. Remarkably, the lipid assemblies can continue to rearrange and reconfigure over time, leading to spherical vesicles with ultra-thin and smooth lipid coating, suggestive of liposomes. Our work provides a new avenue, in the form of electrospray, to form various lipid-based assemblies using all-aqueous systems and we believe this platform can be further exploited for high-throughput vesicle production and higher-order assemblies.

Compartmentalization is a vital aspect of living cells to orchestrate intracellular processes. In a similar vein, constructing dynamic and responsive sub-compartments is key to synthetic cell engineering. In recent years, liquid-liquid phase separation via coacervation has offered an innovative avenue for creating membraneless organelles (MOs) within artificial cells. Here, we present a lab-on-a-chip system to reversibly trigger peptide-based coacervates within cell-mimicking confinements. We use double emulsion droplets (DEs) as our synthetic cell containers while pH-responsive elastin-like polypeptides (ELPs) act as the coacervate system. We first present a high-throughput microfluidic DE production enabling efficient encapsulation of the ELPs. The DEs are then harvested to perform multiple MO formation-dissolution cycles using pH as well as temperature variation. For controlled long-term visualization and modulation of the external environment, we developed an integrated microfluidic device for trapping and environmental stimulation of DEs, with negligible mechanical force, and demonstrated a proof-of-principle osmolyte-based triggering to induce multiple MO formation-dissolution cycles. In conclusion, our work showcases the use of DEs and ELPs in designing membraneless reversible compartmentalization within synthetic cells via physicochemical triggers. Additionally, presented on-chip platform can be applied over a wide range of phase separation and vesicle systems for applications in synthetic cells and beyond.

Metal oxides on metal (inverse) catalysts can selectively drive many important reactions. However, understanding the active site under experimentally relevant conditions is lacking. Herein, we introduce a computational framework for predicting atomic models of stable inverse catalysts and demonstrate it for WOx on Pt(553) and a Pt79 nanoparticle at variable WOx coverages. An evolutionary algorithm identifies a small (5%) subset of promising atomic configurations on which DFT simulations are performed. We predict a maximum coverage of ∼50% WOx on Pt(553), consisting of small clusters (tetramers and pentamers), which preferentially reside on the terrace, with their oxygen atoms interacting with the Pt step sites. Consistently, WOx does not lie on curved and undercoordinated metal sites of Pt nanoparticles. The oxide clusters prefer a partially reduced oxidation state. Theoretical EXAFS spectra for select configurations provide insights into interpreting experimental spectra of inverse catalysts. The framework applies to other catalysts.

Advances in the theoretical understanding of electrochemical systems have, over the past decade, led to growing use of periodic Density Functional Theory studies to treat a surprisingly large ensemble of electrocatalytic reactions, ranging from carbon dioxide electroreduction to oxygen evolution. Many such studies have employed simplified models of the electrochemical environment to determine reactivity trends across a broad space of catalytic materials, while other efforts have focused on developing detailed descriptions of electrochemical phenomena, such as the structure of electrochemical double layers, on model catalyst structures. An emerging challenge is to combine these approaches to ultimately enable theoretical design of electrocatalysts for reactions of significantly expanded chemical and materials complexity. In this talk, I will begin by discussing how we have applied strategies from computational heterogeneous catalysis to design enhanced electrocatalysts for the classic oxygen reduction reaction. In such treatments, we have effected highly detailed analyses of the catalyst surface structure and have employed machine learning-based methods to describe interactions between the various ORR reaction intermediates that are present at significant surface coverages. I will then explore challenges in obtaining more detailed descriptions of the electrocatalytic reaction environment, including the structure of catalysts with solid/solid interfaces, the distribution of charges in electrochemical double layers, and the structure and entropy of solvents near the electrocatalyst surface. I will conclude with some perspectives on how these complexities may be incorporated into traditional computational catalyst screening approaches to identify improved materials for more complex electrocatalytic systems.