Model System Research Articles

Synergy Effect of High K-Low Ca-High Si Biomass Ash Model System on Syngas Production and Reactivity Characteristics during Petroleum Coke Steam Gasification

The synergy effect of high K-low Ca-high Si biomass ash-based model system (BAMS) on the synthesis gas output and reaction characteristics of petroleum coke (PC) steam gasification process was studied using three biomass ash (BA) components, KCl, SiO2, and CaCO3, which were used as the model compounds. In the ternary model system, the steam gasification experiment of PC was conducted using a fixed bed reactor and gas phase chromatography. The synergistic effects of binary and ternary components in the ternary model system on the gasification of PC were obtained. These investigations were based on the data from the gas analysis and examined the gasification reaction process, syngas release behavior, and reaction characteristics. This study examined the effects of binary and ternary components in the ternary model system on the evolution of semi-char structure during PC gasification. This correlation revealed the synergistic effect of the model system on PC gasification. Scanning electron microscope (SEM) and Raman spectroscopy were used to characterize the structure and surface microstructure of the gasification semi-char. The results showed that the yields of different gases in the ternary model system were in H2 > CO > CO2. Compared with single PC gasification, the yields of H2, CO, syngas, and carbon conversion were increased by 29.42 mmol/g, 20.40 mmol/g, 56.68 mmol/g, and 0.35, respectively. All other components in the ternary model system with high K-low Ca-high Si demonstrated catalytic effect, except for SiO2 and the Ca-Si system, which showed inhibitory effects on syngas release and reaction features. Integrating SEM and Raman spectroscopic analyses, it was elucidated that CaCO3 and KCl diminished the degree of graphitization in semi-char through interactions with the carbonaceous matrix. This phenomenon facilitated the gasification process and exhibited a synergistic effect. Secondly, SiO2 will react with CaCO3 and KCl, producing inert silicates and inactivating these compounds, leading to the decline of catalysis.

Optimizing Numerical Weather Prediction Utility of the Maryland Mesonet with Observing System Simulation Experiments

Abstract The Maryland Mesonet Project will construct a network of 75 surface observing stations with aims that include mitigating the statewide impact of severe convective storms and improving analyses of record. The spatial configuration of mesonet stations is expected to affect the utility newly provided observations will have via data assimilation, making it desirable to study the effects of mesonet configuration. Furthermore, the impact associated with any observing system configuration is constrained by errors inherent to the prediction systems used to generate forecasts, which may change with future advances in data assimilation methodology, physical parameterization schemes, and resource availability. To address such possibilities, we perform sets of observing system simulation experiments using a high-resolution regional modeling system to assess the expected impact of four candidate mesonet configurations. Experiments cover seven 18-hour case-study events featuring moist convective regimes associated with severe weather over the state of Maryland and are performed using two versions of our experimental modeling system: a ’standard-uncertainty’ configuration tuned to be representative of existing convective-allowing prediction systems, and a ’constrained-uncertainty’ configuration with reduced boundary condition and model error that reflects a possible trajectory for future prediction systems. We find that the assimilation of mesonet data produces definitive improvements to analysis fields below 1000 m that are mediated by modeling system uncertainty. Conversely, mesonet impact on forecast verification is inconclusive and strongly variable across verification metrics. The impact of mesonet configuration appears limited by a saturation effect that caps local analysis improvements past a minimal density of observing stations.

A network pharmacology-based approach to understand the mechanism of action of anti-mycobacterial activity of Acacia nilotica: a modelling and experimental study.

The rapid rise in drug-resistant tuberculosis poses a serious threat to public health and demands the discovery of new anti-mycobacterial agents. Medicinal plants are a proven potential source of bioactive compounds; however, identifying those responsible for the putative anti-mycobacterial action still remains a challenging task. In this study, we undertook a systematic network pharmacology approach to identify and evaluate anti-mycobacterial compounds from a traditional plant, Acacia nilotica, as a model system. The protein-protein interaction network revealed 17 key pathways in M. tuberculosis encompassing 40 unique druggable targets that are necessary for its growth and survival. The phytochemicals of A. nilotica were preferentially found to interfere with the cell division and cell wall biogenesis proteins, especially FtsZ and Mur. Notably, the compounds epigallocatechin, ellagic acid, chlorogenic acid, and D-pinitol were found to exhibit a potential polypharmacological effect against multiple proteins. Further, in vitro studies confirmed that the selected candidates, chlorogenic acid, and ellagic acid exhibited potent anti-mycobacterial activity (against M. smegmatis) with specific inhibition of purified M.tb FtsZ enzyme. Taken together, the present study demonstrates that network pharmacology combined with molecular docking can be utilized as an efficient approach to identify potential bioactive phytochemicals from natural products along with their mechanism of action. Hence, the compounds identified in this study can be potential lead candidates for developing novel anti-mycobacterial drugs, while the key proteins identified here can be potential drug targets.

Catalyzing Knoevenagel Condensation and Radioiodine Sequestration with Tuned Porous Organic Polymers to Decipher the Role of Surface Area, Pore Volume, and Heteroatom.

The impact of surface area, pore volume, and heteroatom type on the performance of porous organic polymers (POPs) in various applications remains unclear. To investigate this, three isoreticular POPs were employed having one common building block, resulting in varying surface areas, pore volumes, and heteroatom compositions. This study aimed to establish a correlation between the structural features of POPs (surface area, pore volume, and heteroatom type) with their adsorption capacity, and catalytic efficiency. To explore this relationship, the Knoevenagel condensation reaction was used as a model system, testing various substituted aldehydes to further validate our findings. Additionally, the capture of radioactive iodine vapor at 75°C was simulated to examine the correlation with adsorption capacity, comparing the gravimetric iodine uptake capacity of each POP to gain insights into this relationship.

Interactions of White Mugwort (Artemisia lactiflora Wall.) Extract with Food Ingredients during In Vitro Gastrointestinal Digestion and Their Impact on Bioaccessibility of Polyphenols in Various Model Systems

The bioaccessibility of phytochemicals is an important factor for new functional food design. The interaction of white mugwort extract (FE) and food ingredients (coconut oil, egg white albumen, brown rice powder, inulin, and mixtures thereof) was determined after in vitro digestion to inform the development of a functional soup for an aging population. Coconut oil exerted a protective effect on polyphenols, showing the highest bioaccessibility (62.9%) and antioxidant activity after intestinal digestion (DPPH 12.38 mg GAE/g DW, FRAP 0.88 mol Fe(ll)/g DW). In contrast, egg white albumen had the most significant negative effect on the polyphenol stability, resulting in the lowest bioaccessibility (12.49%). Moreover, FE promoted the emulsion stability and delayed starch digestion by inhibiting amylase activity via non-specific polyphenol–protein interactions, resulting in a decrease in the total reducing sugars (TRS) released during digestion. It also limited the protein digestion, probably due to the complex formation of polyphenols and proteins, consequently reducing the bioaccessibility of both amino acids and polyphenols. These findings provide useful information for designing functional food products that could promote the bioaccessibility and bioactivity of natural extracts.

Exploring the Relationship Between COVID-19 Transmission and Population Mobility over Time

This study explores the dynamic relationship between COVID-19 transmission and transportation mobility, with an emphasis on understanding the time-varying bidirectional interplay across the different phases of the pandemic. To gain insight into this relationship, we analyzed county-level data on transmission and mobility patterns from the United States over a 74-week period using a comprehensive list of factors including: temporal factors, socio-demographics, health indicators, health care infrastructure attributes, and spatial factors. For our analysis, we proposed a simultaneous econometric model system that explicitly accounts for the bidirectional relationship between COVID-19 transmission and mobility patterns while also accounting for the influence of common unobserved factors on the two variables. The model results strongly support our hypothesis that COVID-19 transmission and mobility patterns are interconnected. Further, our findings show distinct phases of the bidirectional relationship influenced by behavior changes, vaccine availability, and the emergence of new variants. Additionally, we conducted a validation exercise on a hold-out sample to assess the robustness of our model. The results confirm the superiority of the simultaneous model system with enhanced interpretability and prediction capability. By analyzing data from several weeks for the COVID-19 pandemic, our study provides valuable insights into the evolving dynamics and potential strategies for future pandemics.

Modeling X chromosome inactivation using t5iLA naive human pluripotent stem cells

BackgroundX chromosome inactivation (XCI) is a critical epigenetic event for dosage compensation of X-linked genes in female mammals, ensuring developmental stability. A robust in vitro model is required for mimicking XCI during the early stages of embryonic development. This methodology article introduces an advanced framework for the in-depth study of XCI using human pluripotent stem cells (hPSCs). By focusing on the transition between naive and primed pluripotent states, we highlight the role of long non-coding RNA X-inactive specific transcript (XIST) and epigenetic alterations in mediating XCI.ResultsOur methodology enables the distinction between naive and primed hESCs based on XIST expression and the activity of X-linked reporters, facilitating the investigation of XCI initiation and maintenance. Through detailed experimental procedures, we demonstrate the utility of our hESC lines in modeling the process of human XCI, including the establishment of conditions for random XCI induction and the analysis of X chromosome reactivation.MethodsThe study outlines a comprehensive approach for characterizing the X chromosome status in hPSCs, employing dual fluorescent reporter hESC lines. These reporter lines enable real-time tracking of XCI dynamics through differentiation processes. We detailed protocols for the induction of X chromosome reactivation and inactivation, as well as the X status characterization methods including cultivation of hESCs, flow cytometric analysis, RNA fluorescence in situ hybridization (FISH), and transcriptome sequencing, providing a step-by-step guide for researchers to investigate XCI mechanisms in vitro.ConclusionsThis article provides a detailed, reproducible methodology for studying XCI mechanisms in vitro, employing hPSCs as a model system. It presents a significant advance in our ability to investigate XCI, offering potential applications in developmental biology, disease modeling, and regenerative medicine. By facilitating the study of XCI dynamics, this methodological framework paves the way for deeper understanding and manipulation of this fundamental biological process.

Multiresolution molecular dynamics simulations reveal the interplay between conformational variability and functional interactions in membrane-bound cytochrome P450 2B4.

Cytochrome P450 2B4 (CYP 2B4) is one of the best-characterized CYPs and serves as a key model system for understanding the mechanisms of microsomal class II CYPs, which metabolize most known drugs. The highly flexible nature of CYP 2B4 is apparent from crystal structures that show the active site with either a wide open or a closed heme binding cavity. Here, we investigated the conformational ensemble of the full-length CYP 2B4 in a phospholipid bilayer, using multiresolution molecular dynamics (MD) simulations. Coarse-grained MD simulations revealed two predominant orientations of CYP 2B4's globular domain with respect to the bilayer. Their refinement by atomistic resolution MD showed adaptation of the enzyme's interaction with the lipid bilayer, leading to open configurations that facilitate ligand access to the heme binding cavity. CAVER analysis of enzyme tunnels, AquaDuct analysis of water routes, and Random Acceleration Molecular Dynamics simulations of ligand dissociation support the conformation-dependent passage of molecules between the active site and the protein surroundings. Furthermore, simulation of the re-entry of the inhibitor bifonazole into the open conformation of CYP 2B4 resulted in binding at a transient hydrophobic pocket within the active site cavity that may play a role in substrate binding or allosteric regulation. Together, these results show how the open conformation of CYP 2B4 facilitates the binding of substrates from and release of products to the membrane, whereas the closed conformation prolongs the residence time of substrates or inhibitors and selectively allows the passage of smaller reactants via the solvent and water channels.

E-Counseling : Mobile-Based Specialization System in Vocational Schools

Many students who will continue their studies to the high school level are confused about choosing a major. This is because most students do not understand the majors at the vocational level, making it difficult for students to enter majors according to the talents and interests of each student. This research is a continuation of previous research that has developed web-based applications. With a majors specialization system using the Inventory Personal Survey Test model system which was built as a majors selection system at the SMK level, mobile access is needed to make it easier for students to access this service via an application on a smartphone.This system is designed using Android Studio and the database creation using MYSQL. The results of the specialization that has been carried out show that the system can be used to conduct online counseling and makes it easier for counselors to collect and analyze counseling results.

Mycologists and Virologists Align: Proposing Botrytis cinerea for Global Mycovirus Studies

Mycoviruses are highly genetically diverse and can significantly change their fungal host’s phenotype, yet they are generally under-described in genotypic and biological studies. We propose Botrytis cinerea as a model mycovirus system in which to develop a deeper understanding of mycovirus epidemiology including diversity, impact, and the associated cellular biology of the host and virus interaction. Over 100 mycoviruses have been described in this fungal host. B. cinerea is an ideal model fungus for mycovirology as it has highly tractable characteristics—it is easy to culture, has a worldwide distribution, infects a wide range of host plants, can be transformed and gene-edited, and has an existing depth of biological resources including annotated genomes, transcriptomes, and isolates with gene knockouts. Focusing on a model system for mycoviruses will enable the research community to address deep research questions that cannot be answered in a non-systematic manner. Since B. cinerea is a major plant pathogen, new insights may have immediate utility as well as creating new knowledge that complements and extends the knowledge of mycovirus interactions in other fungi, alone or with their respective plant hosts. In this review, we set out some of the critical steps required to develop B. cinerea as a model mycovirus system and how this may be used in the future.

Applying double cropping and interactive irrigation in the North China Plain using WRF4.5

Abstract. Irrigated cultivation exerts a significant influence on the local climate and the hydrological cycle. The North China Plain (NCP) is known for its intricate agricultural system, marked by expansive cropland, high productivity, compact rotation, a semi-arid climate, and intensive irrigation practices. As a result, there has been considerable attention on the potential impact of this intensive irrigated agriculture on the local climate. However, studying the irrigation impact in this region has been challenging due to the lack of an accurate simulation of crop phenology and irrigation practices within the climate model. By incorporating double cropping with interactive irrigation, our study extends the capabilities of the Weather Research Forecast (WRF) model, which has previously demonstrated commendable performance in simulating single-cropping scenarios. This allows for two-way feedback between irrigated crops and climate, further enabling the inclusion of irrigation feedback from both ground and vegetation perspectives. The improved crop modeling system shows significant enhancement in capturing vegetation and irrigation patterns, which is evidenced by its ability to identify crop stages, estimate field biomass, predict crop yield, and project monthly leaf area index. The improved simulation of large-scale irrigated crops in the NCP can further enhance our understanding of the intricate relationship between agricultural development and climate change.

Probing the Linear-to-Plastic Transition in Polymer Nanocomposites via Atomistic Simulations: The Role of Interphases.

Polymer nanocomposites have found ubiquitous use across diverse industries, attributable to their distinctive properties and enhanced mechanical performance compared to conventional materials. Elucidating the elastic-to-plastic transition in polymer nanocomposites under diverse mechanical loads is paramount for the bespoke design of materials with desired mechanical attributes. In the current work, the elastic-to-plastic transition is probed in model systems of polyethylene oxide (PEO) and silica, SiO2, nanoparticles, through detailed atomistic molecular dynamics simulations. This comprehensive, multi-scale analysis unveils pivotal markers of the elastic-to-plastic transition, highlighting the quintessential role of microstructural and regional heterogeneities in density, strain, and stress fields, featuring the polymer-nanoparticle interphase region. At the atomic level, the behavior of polymer chains interacting with nanoparticle surfaces is traced, differentiating between free and adsorbed chains, and identifying the microscopic origins of the linear-to-plastic transition. The mechanical behavior of subregions are characterized within the PEO/SiO2 nanocomposites, focusing on the interphase and bulk-like polymer areas, probing stress heterogeneities and their decomposition into various force contributions. At the inception of plasticity, a disruption is discerned in isotropy of the polymeric density field, the emergence of low-density regions, and microscopic voids/cavities within the polymer matrix concomitant with a transition of adsorbed chains to free. The yield strain also emerges as an inflection point in the local versus global strain diagram, demarcating the elastic limit, and the plastic regime shows pronounced strain heterogeneities. The decomposition of the atomic Virial stress into bonded and non-bonded interactions indicates that the rigidity of the material is primarily governed by non-bonded interactions, significantly influenced by the volume fraction of the nanoparticle. These findings emphasize the importance of the microstructural and micromechanical environment at the polymer-nanoparticle interface on the linear-to-plastic transition, which is of great importance in the design of nanocomposite materials with advanced mechanical properties.

A DFT Mechanistic Study on the Aza-Aldol Reaction of Boron Aza-Enolates: Relative Stability of Six-Membered Transition State and Its Relevance to the Coordination Mode of the Leaving Group.

The mechanism of the aza-aldol reaction between boron aza-enolate and benzaldehyde is investigated by using density functional theory calculations. The result shows that the syn-E isomer is preferentially formed, consistent with experimental observations. The six-membered ring transition state (TS) with the boat form leads to the E isomer, while the more unstable chair TS does to the Z isomer. The preference of the syn isomer is determined by the interactions between the substituents of aza-enolate and benzaldehyde. Structural distortion and intrinsic reaction coordinate analyses of simplified model systems provide insights into the origin of the relative stability of the rate-determining TS with boat and chair forms. The boat TS is an early TS; thus, minimal structural distortions of the reactant are required to reach this TS. The Lewis pair interactions between the boron and imine groups during B-N elimination also influenced the relative stability of the TSs. This interaction involves the nitrogen lone pair in the boat TS, while the π(N═C) orbital is involved in the chair TS. The Lewis pair with the lone pair stabilizes the TS more than that with the π orbital. The boron aza-enolate with 9-BBN generates an ate complex and forms C-C bonds sequentially, whereas that with Bpin does not generate an ate complex and exhibits the concerted formation of B-O and C-C bonds. Thus, the higher electrophilicity of boron such as 9-BBN enhances the reactivity by facilitating the formation of the ate complex. A reaction design is proposed to reverse the syn/anti selectivity. Proof-of-concept DFT calculations suggested that the modification of the imine group would change the relative stability of the boat/chair TSs and give the anti-product.

Immiscible Polymer-Filler Systems for Tunable Mechanical Properties

Abstract A model system consisting of a 50/50 immiscible mixture of polyethylene glycol (PEG) and polytetrahydrofuran (PTHF), with covalently bound nano-silica reinforcing particles, was used to investigate how the distribution of particles affects viscoelastic properties. The rubbery polymers were generated by chain extending from their respective oligomers through hydroxyl end groups with 1,6-diisocyanato hexane. The viscosities of the resulting PEG and PTHF polymers were 32 and 1000 Pa-s, respectively. Setting the overall SiO2 concentration to 10 phr, we explored three different silica distributions: (1) “all-in-PEG” ‒ 20 phr in PEG and neat PTHF; (2) “uniform” ‒ 10 phr in both PEG and PTHF; and (3) “all-in-PTHF” ‒ neat PEG and 20 phr in PTHF. When compared to the uniform system, the storage and loss shear moduli, and the viscosity of the all-in- PTHF system showed a 20-fold increase of the stiffness at low strain, yet nearly the same viscosity at high strain. Similarly, the storage and loss moduli of all-in-PEG mixtures were roughly 1/10 that of the uniform system. The surprisingly high modulus and high viscosity of the all-in-PTHF system can be understood as the entire PTHF regions themselves becoming solid filler.

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li7La3Zr2O12-LiCoO2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li7La3Zr2O12-LiCoO2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. Our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

Exploring a Dynamic Homotopy Technique to Enhance the Convergence of Classical Power Flow Iterative Solvers in Ill-Conditioned Power System Models

This paper presents a dynamic homotopy technique that can be used to calculate a preliminary result for a power flow problem (PFP). This result can then be used as an initial estimate to efficiently solve the PFP using either the classical Newton-Raphson (NR) method or its fast decoupled version (FDXB) while still maintaining high accuracy. The preliminary stage for the dynamic homotopy problem is formulated and solved by employing integration techniques, where implicit and explicit schemes are studied. The dynamic problem assumes an initial condition that coincides with the initial estimate for a traditional iterative method such as NR. In this sense, the initial guess for the FPF is adequately set as a flat start, which is a starting for the case when this initialization is of difficult assignment for convergence. The static homotopy method requires a complete solution of a PFP per homotopy pathway point, while the dynamic homotopy is based on numerical integration methods. This approach can require only one LU factorization at each point of the pathway. Allocating these points properly helps avoid several PFP resolutions to build the pathway. The hybrid technique was evaluated for large-scale systems with poor conditioning, such as a 109,272-bus model and other test systems under stressed conditions. A scheme based on the implicit backward Euler scheme demonstrated the best performance among other numerical solvers studied. It provided reliable partial results for the dynamic homotopy problem, which proved to be suitable for achieving fast and highly accurate solutions using both the NR and FDXB solvers.

Wnt/β-Catenin Signaling Regulates Yap/Taz Activity during Embryonic Development in Zebrafish

Hippo-YAP/TAZ and Wnt/β-catenin signaling pathways, by controlling proliferation, migration, cell fate, stemness, and apoptosis, are crucial regulators of development and tissue homeostasis. We employed zebrafish embryos as a model system to elucidate in living reporter organisms the crosstalk between the two signaling pathways. Co-expression analysis between the Wnt/β-catenin Tg(7xTCF-Xla.Siam:GFP)ia4 and the Hippo-Yap/Taz Tg(Hsa.CTGF:nlsmCherry)ia49 zebrafish reporter lines revealed shared spatiotemporal expression profiles. These patterns were particularly evident in key developmental regions such as the midbrain–hindbrain boundary (MHB), epidermis, muscles, neural tube, notochord, floorplate, and otic vesicle. To investigate the relationship between the Wnt/β-catenin pathway and Hippo-Yap/Taz signaling in vivo, we conducted a series of experiments employing both pharmacological and genetic strategies. Modulation of the Wnt/β-catenin pathway with IWR-1, XAV939, or BIO resulted in a significant regulation of the Yap/Taz reporter signal, highlighting a clear correlation between β-catenin and Yap/Taz activities. Furthermore, genetic perturbation of the Wnt/β-catenin pathway, by APC inhibition or DKK1 upregulation, elicited evident and robust alteration of Yap/Taz activity. These findings revealed the intricate regulatory mechanisms underlying the crosstalk between the Wnt/β-catenin and Hippo-Yap/Taz signaling, shedding light on their roles in orchestrating developmental processes in vivo.

Genomics and synthetic community experiments uncover the key metabolic roles of acetic acid bacteria in sourdough starter microbiomes.

This study is a comprehensive genomic and ecological survey of acetic acid bacteria (AAB) isolated from sourdough starters. By combining comparative genomics with manipulative experiments using synthetic microbiomes, we demonstrate that even strains with >97% average nucleotide identity can shift important microbiome functions, underscoring the importance of species and strain diversity in microbial systems. We also demonstrate the utility of sourdough starters as a model system to understand the consequences of genomic diversity at the strain and species level on multispecies communities. These results are also relevant to industrial and home-bakers as we uncover the importance of AAB in shaping properties of sourdough starters that have direct impacts on sensory notes and the quality of sourdough bread.

Structure and Defect Identification at Self-Assembled Islands of CO2 Using Scanning Probe Microscopy.

Understanding how carbon dioxide (CO2) behaves and interacts with surfaces is paramount for the development of sensors and materials to attempt CO2 mitigation and catalysis. Here, we combine simultaneous atomic force microscopy (AFM) and scanning tunneling microscopy (STM) using CO-functionalized probes with density functional theory (DFT)-based simulations to gain fundamental insight into the behavior of physisorbed CO2 molecules on a gold(111) surface that also contains one-dimensional metal-organic chains formed by 1,4-phenylene diisocyanide (PDI) bridged by gold (Au) adatoms. We resolve the structure of self-assembled CO2 islands, both confined between the PDI-Au chains as well as free-standing on the surface and reveal a chiral arrangement of CO2 molecules in a windmill-like structure that encloses a standing-up CO2 molecule and other foreign species existing at the surface. We identify these species by the comparison of height-dependent AFM and STM imaging with DFT-calculated images and clarify the origin of the kagome tiling exhibited by this surface system. Our results show the complementarity of AFM and STM using functionalized probes and their potential, when combined with DFT, to explore greenhouse gas molecules at surface-supported model systems.

Synthesis and Characterization of Monolayer Colloidal Sheets.

Sheet-like colloidal assemblies represent model systems to investigate the structure and properties of two-dimensional materials. Here, we report a simple yet versatile method for the preparation of colloidal monolayer sheet-like assemblies that affords control over the size, crystalline order, flexibility, and defect density. The protocol that we report relies on self-assembly of colloids as a sessile drop of dispersion is evaporated on an oil-covered substrate. In this case, the contact line continually moves as the drop shrinks. Polyethyleneimine polymer-covered micrometer-sized colloidal particles are transported to the air-water interface and assemble to form a monolayer sheet as the drop dries. Cross-linking the polymer renders the colloidal assembly permanent. Interestingly, monodisperse colloidal particles form disordered assemblies when dried from low concentration dispersions, while polycrystalline ordered assemblies form at higher concentrations. We demonstrate that increasing the cross-linker to polymer ratio decreases the flexibility of the assembly. Introduction of different-sized colloidal particles in a sheet leads to increased disorder. Removal of sacrificial particles from the sheet allowed the introduction of "holes" in the sheets. Thus, these colloidal sheets are models for probing the effects of disorder, doping, and vacancies in two-dimensional systems.