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At least 1,027 records · Page 57

Exploring Subsite Selectivity within Plasmodium vivax N -Myristoyltransferase Using Pyrazole-Derived Inhibitors

N-myristoyltransferase (NMT) is a promising antimalarial drug target. Despite biochemical similarities between Plasmodium vivax and human NMTs, our recent research demonstrated that high selectivity is achievable. Herein, we report PvNMT-inhibiting compounds aimed at identifying novel mechanisms of selectivity. Various functional groups are appended to a pyrazole moiety in the inhibitor to target a pocket formed beneath the peptide binding cleft. The inhibitor core group polarity, lipophilicity, and size are also varied to probe the water structure near a channel. Selectivity index values range from 0.8 to 125.3. Cocrystal structures of two selective compounds, determined at 1.97 and 2.43 Å, show that extensions bind the targeted pocket but with different stabilities. A bulky naphthalene moiety introduced into the core binds next to instead of displacing protein-bound waters, causing a shift in the inhibitor position and expanding the binding site. Our structure-activity data provide a conceptual foundation for guiding future inhibitor optimizations.

60 APPLIED LIFE SCIENCES↗

Supramolecular Enhancement of Electrochemical Nitrate Reduction Catalyzed by Cobalt Porphyrin Organic Cages for Ammonia Electrosynthesis in Water**

Abstract The electrochemical nitrate (NO 3 − ) reduction reaction (NO 3 RR) to ammonia (NH 3 ) represents a sustainable approach for denitrification to balance global nitrogen cycles and an alternative to traditional thermal Haber‐Bosch processes. Here, we present a supramolecular strategy for promoting NH 3 production in water from NO 3 RR by integrating two‐dimensional (2D) molecular cobalt porphyrin ( CoTPP ) units into a three‐dimensional (3D) porous organic cage architecture. The porphyrin box CoPB‐C8 enhances electrochemical active site exposure, facilitates substrate–catalyst interactions, and improves catalyst stability, leading to turnover numbers and frequencies for NH 3 production exceeding 200,000 and 56 s −1 , respectively. These values represent a 15‐fold increase in NO 3 RR activity and 200‐mV improvement in overpotential for the 3D CoPB‐C8 box structure compared to its 2D CoTPP counterpart. Synthetic tuning of peripheral alkyl substituents highlights the importance of supramolecular porosity and cavity size on electrochemical NO 3 RR activity. These findings establish the incorporation of 2D molecular units into 3D confined space microenvironments as an effective supramolecular design strategy for enhancing electrocatalysis.

An, Lun↗

Supramolecular Enhancement of Electrochemical Nitrate Reduction Catalyzed by Cobalt Porphyrin Organic Cages for Ammonia Electrosynthesis in Water**

Abstract The electrochemical nitrate (NO 3 − ) reduction reaction (NO 3 RR) to ammonia (NH 3 ) represents a sustainable approach for denitrification to balance global nitrogen cycles and an alternative to traditional thermal Haber‐Bosch processes. Here, we present a supramolecular strategy for promoting NH 3 production in water from NO 3 RR by integrating two‐dimensional (2D) molecular cobalt porphyrin ( CoTPP ) units into a three‐dimensional (3D) porous organic cage architecture. The porphyrin box CoPB‐C8 enhances electrochemical active site exposure, facilitates substrate–catalyst interactions, and improves catalyst stability, leading to turnover numbers and frequencies for NH 3 production exceeding 200,000 and 56 s −1 , respectively. These values represent a 15‐fold increase in NO 3 RR activity and 200‐mV improvement in overpotential for the 3D CoPB‐C8 box structure compared to its 2D CoTPP counterpart. Synthetic tuning of peripheral alkyl substituents highlights the importance of supramolecular porosity and cavity size on electrochemical NO 3 RR activity. These findings establish the incorporation of 2D molecular units into 3D confined space microenvironments as an effective supramolecular design strategy for enhancing electrocatalysis.

An, Lun↗

Trophic interactions at avian carcasses: Do scavengers feed on vulture carrion?

Scavenging is a pervasive foraging strategy among vertebrates, yet researchers have only recently begun to reveal the complex implications of scavenging dynamics. Scavenging studies have predominantly used lower trophic level (i.e., herbivore) species as carrion bait, and the few studies that have used higher trophic level (i.e., carnivore) carrion have found these carcass types are generally avoided by vertebrates or scavenged by fewer species than similarly sized herbivore carcasses. No studies have assessed the fate of carcasses of obligate scavengers. To investigate potential differences in scavenging dynamics among avian carrion representing different guilds and trophic levels, we conducted scavenging trials using 20 replicates of two obligate scavenger species (i.e. black vulture, Coragyps atratus; turkey vulture, Cathartes aura) and two lower trophic level species, chicken (Gallus gallus domesticus), and mallard (Anas platyrhynchos). Carcass trials were conducted at the Savannah River Site, SC, USA, and monitored with remote cameras. We hypothesized carcasses of vultures would persist longer and have a distinct scavenging community compared to lower trophic level carcasses (mallard and chicken). As expected, turkey and black vulture carcasses persisted in the environment longer, were less likely to be entirely consumed by vertebrate scavengers, and had a different scavenging community than mallard and chicken carcasses. Furthermore, these results contribute to the growing body of evidence suggesting higher trophic level carrion is exploited differently by vertebrate scavengers. Our findings suggest nutrients derived from vulture carcasses are likely largely reincorporated into lower trophic levels.

59 BASIC BIOLOGICAL SCIENCES↗

Mesoporous Crystalline Niobium Oxide with a High Surface Area: A Solid Acid Catalyst for Alkyne Hydration

A mesoporous crystalline niobium oxide with tunable pore sizes was synthesized via the sol–gel-based inverse micelle method. The material shows a surface area of 127 m 2 /g, which is the highest surface area reported so far for crystalline niobium oxide synthesized by soft template methods. The material also has a monomodal pore size distribution with an average pore diameter of 5.6 nm. A comprehensive characterization of niobium oxide was performed using powder X-ray diffraction, Brunauer–Emmett–Teller, thermogravimetric analysis, scanning electron microscopy, transmission electron microscopy, UV–vis, and X-ray photoelectron spectroscopy. The material acts as an environmentally friendly, solid acid catalyst toward hydration of alkynes under with excellent catalytic activity (99% conversion, 99% selectivity, and 4.39 h –1 TOF). Brønsted acid sites present in the catalyst were found to be responsible for the high catalytic activity. Lastly, the catalyst was reusable up to five cycles without a significant loss of the activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-Dimensional Molecular Charge Density Waves in Single-Layer-Thick Islands of a Dirac Fermion System

Charge density waves have been intensely studied in inorganic materials such as transition metal dichalcogenides however its counterpart in organic materials has yet to be explored in detail. Here we report the finding of a robust two dimensional charge density waves in molecular layers formed by α-(BEDT-TTF) 2 -I 3 on a Ag(111) surface. Low temperature scanning tunnelling microscopy images of a multi-layer thick α-(BEDT-TTF) 2 -I 3 on Ag(111) substrate reveal coexistence of 5a0 x 5a0 and √31 a0 x √31 a0 R9° charge density wave patterns commensurate with the underlying molecular lattice at 80 K. Both charge density wave patterns remain in nano-size molecular islands with just a single constituent molecular-layer thickness at 80 K and 5 K. Local tunneling spectroscopy measurements reveal the variation of the gap from 244 meV to 288 meV between the maximum and minimum charge density wave locations. Density functional theory calculations further confirm a vertical positioning of BEDT-TTF molecules in the molecular layer. While the observed charge density wave patterns are stable for the defect sites, they can be reversely switched for one molecular lattice site by means of inelastic tunnelling electron energy transfer with the electron energies exceeding 400 meV using a scanning tunneling microscope manipulation scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulating scalar field theories on quantum computers with limited resources

Here we present a quantum algorithm for implementing φ 4 lattice scalar field theory on qubit computers. The field is represented in the discretized field amplitude basis. The number of qubits and elementary gates required by the implementation of the evolution operator is proportional to the lattice size. The algorithm allows efficient φ 4 state preparation for a large range of input parameters in both the normal and broken-symmetry phases. The states are prepared using a combination of variational and adiabatic evolution methods. First, the ground state of a local Hamiltonian, which includes the φ 4 self-interaction, is prepared using short variational circuits. Next, this state is evolved by switching on the coupling between the lattice sites adiabatically. The parameters defining the local Hamiltonian are adjustable and constitute the input of our algorithm. We present a method to optimize these parameters in order to reduce the adiabatic time required for state preparation. For preparing broken-symmetry states, the adiabatic evolution problems caused by crossing the phase transition critical line and by the degeneracy of the broken-symmetry ground state can be addressed using an auxiliary external field which gradually turns off during the adiabatic process. We show that the time dependence of the external field during the adiabatic evolution is important for addressing the broken-symmetry ground state degeneracy. The adiabatic time dependence on the inverse error tolerance can be reduced from quadratic to linear by using a field strength that decreases exponentially in time relative to one that decreases linearly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Leveraging Existing Assets for Long Duration Energy Storage

Increased renewables penetration to electrical grid is necessary to reduce overall emissions from the electrical power generation sector. Nonetheless, its integration creates challenges to grid operators who must match the power being generated by intermittent renewables and other traditional energy sources with the demand from consumers, while ensuring the reliability and power quality for the entire system. Energy storage has been proposed as an alternative to natural gas peaking plants and a form to deliver excess renewable energy generation at times of peak demand. For energy storage to provide benefits to end customers (energy consumers), it must be reliable, efficient, and cost effective. The Illinois Sustainable Technology Center (ISTC), one of the surveys that integrate the Prairie Research Institute (PRI), aims to develop a Center for Energy Storage at Existing Assets (CESEA) at UIUC with the participation of Waste Pressure Corp and Ecotek Engineering USA LLC. CESEA will focus on LDES systems that can integrate to existing infrastructure in a manner that reduces the initial capital expenditure and demonstrates the ability to repurpose fossil assets that would otherwise become stranded, to serve the energy transition. CESEA aims to leverage UIUC’s unique facilities to validate LDES systems performance at a relevant operating environment. UIUC’s facilities include a 85-MW combined heat and power (CHP) power plant, two (2) solar PV plants totaling over 18 MWdc of installed capacity, an electrical grid along with a substation at transmission and distribution voltages, a 22-mile gas pipeline network operating at two pressure levels, along with steam and chilled water distribution networks. The new LDES systems will connect to the existing UIUC grid through a new test electrical station, which will have the capacity to accommodate additional connections to test new devices and technologies as part of future CESEA R&D activities. The test electrical station will contain meters, instrumentation, and controls to accurately capture data and allow optimization of control algorithms. CESEA will initially focus on technologies that: i) utilize existing equipment or facilities to perform at least one of the process steps in LDES (charging, storage, or discharging), ii) leverage mature or commercially available components or controls, iii) show potential for cost-leadership in 10+ hour storage at a commercial scale. Initial technologies that were identified to meet these criteria include Compressed Gas Energy Storage (CGES), and TES. CGES stores electricity by raising the pressure of a compressible gas inside a control volume and converting the stored energy to electricity via expansion-generation. CGES is a generalization of CAES that covers any working gas (not just air). A successful CGES demo will help to circumvent many challenges faced by CAES (long development times due to site prospecting, high cost of compression and storage, heat recovery management, etc.) by: 1) utilizing existing infrastructure (compressors, pipelines, underground storage or pressure vessels) used in the transportation and storage of industrial gases for LDES charging and storage; 2) deploying over sites already-developed for industrial applications with minor additional work; 3) leveraging the price structure of commercial industrial gas to cover the costs of electricity used during charging. A previous DOE-sponsored conceptual study (DE-FE-0032018) estimated the levelized cost of energy of a 1.1 MW / 17 MWh CGES system at $0.08/kWh, with a commercial 10x scale system cost estimated at <$0.04/kWh (Giardinella, 2022). The pilot-sized system was estimated to avoid up to 2693 tons of CO2/year.

25 ENERGY STORAGE↗

Coastal Cloud Chemistry during EPCAPE Field Campaign Report

For this campaign, Principal Investigator Markus Petters deployed a suite of instruments inside Lynn Russell’s container that was sited at Mt. Soledad during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) campaign. Funding for this activity was provided by National Science Foundation Award 2410536. The instrument rack (Figure 1) included a differential mobility analyzer, a condensation particle counter, a portable optical particle spectrometer, and a continuous flow diffusion cloud condensation nuclei counter (CCN). The instruments sampled from a counterflow virtual impactor (CVI) inlet and an isokinetic inlet. The measurements provided aerosol size distribution, size-resolved CCN activity, and denuded versus undenuded CCN activity of aerosols and cloud drop residuals.

54 ENVIRONMENTAL SCIENCES↗

Elucidating CO Oxidation Pathways on Rh Atoms and Clusters on the “29” Cu 2 O/Cu(111) Surface

We report single-atom catalysts have attracted a great deal of attention due to their distinct reactivity and potential for cost savings. However, despite the wealth of literature in recent years, identifying the exact nature of the active sites and associated reaction mechanisms remains challenging in many cases. Herein, we take a surface science approach to understand how Rh single atoms and small clusters behave on the thin film “29” Cu 2 O grown on Cu(111). We find that in contrast to Pt, which is present solely as single atoms on the “29” Cu 2 O surface, Rh atoms and clusters coexist and each enable low-temperature CO oxidation, but via different pathways. Specifically, the single Rh atoms produce CO 2 at 444 K via a Mars van Krevelen mechanism whereas the Rh clusters can also dissociate CO, as demonstrated via isotope labeling, and liberate CO 2 at 313 K. Density functional theory (DFT) calculations quantify the energetics of these different pathways and demonstrate that only extended Rh is capable of CO dissociation. Low-temperature scanning tunneling microscopy (STM) reveals that unlike Pt atoms on the same surface, which stay atomically dispersed, the distribution of Rh structures is dependent on pretreatment conditions. DFT calculations reveal the greater tendency of Rh atoms to cluster than Pt, and STM image simulations confirm the active sites. Ambient pressure X-ray photoelectron spectroscopy studies on the same single crystal model systems demonstrate that 1% of a monolayer of Rh on the “29” Cu 2 O thin film significantly accelerates its reduction by CO at 400 K, thus confirming the ultrahigh vacuum surface science findings. Together, these results illustrate how well-defined single crystal experiments are useful in building structure–function relationships that elucidate the reactivity of different ensemble sizes with a level of detail beyond what is possible with high surface area catalysis.

36 MATERIALS SCIENCE↗

Structure and Dynamics of Aqueous Electrolytes Confined in 2D-TiO 2 /Ti 3 C 2 T 2 MXene Heterostructures

The synthesis of heterostructures of different two-dimensional (2D) materials offers an approach to combine advantages of different materials constituting the heterostructure and ultimately enhance their performance for applications such as electrochemical energy storage, achieving high energy, and high-power densities. Understanding the behavior of ions and solvents in confinement between these dissimilar layers is critical to understand their performance and control. Considering aqueous electrolytes, we explore the heterostructure of 2D lepidocrocite-type TiO 2 (2D-TiO 2 ) and hydroxylated or O-terminated Ti 3 C 2 MXene using ReaxFF molecular dynamics simulations and elastic/quasielastic neutron scattering techniques. Simulating a bilayer water intercalation, we find that the extent of interlayer hydration is impacted most by the surface terminations on the MXene and is marginally affected by 2D-TiO 2 . However, the introduction of 2D-TiO 2 decreases the water self-diffusion due to the notch sites (i.e., surface oxygen ridges) entrapping water molecules. Intercalating alkali cations into the heterostructures, we find that Li + is predominantly adsorbed at the 2D-TiO 2 surface instead of the MXenes with the preferential occupation of the notch sites. In contrast, Na+ forms a planar solvation with water, while K + is adsorbed both at the O-terminated MXene and 2D-TiO 2 . This behavior is altered when OH-terminated MXene is involved—the repulsion from the protons on the MXene surface forces the K + ions to be adsorbed exclusively to 2D-TiO 2 , while Na + retains some of its solvation in the water layer due to its smaller size. In OH-terminated MXenes, we see a consistent transfer of protons from the MXene surface toward 2D-TiO 2 , implying a greater capacity to store protons in the heterostructures. Of the three cations simulated, Na + hinders the proton migration the least and Li + the most because of its position near the 2D-TiO 2 surface. Furthermore, 2D-TiO 2 /MXene heterostructures are likely to exhibit a higher energy density but lower power density, especially with Na + intercalation.

25 ENERGY STORAGE↗

Enhanced Menshutkin S N 2 Reactivity in Mesoporous Silica: The Influence of Surface Catalysis and Confinement

A significant enhancement in the Menshutkin S N 2 reaction between 1-methylimidazole (MeIm) and methyl thiocyanate (MeSCN) is observed when the reaction is confined in the nanoscale silica pores of MCM41 and SBA15. The experiments in the silica pores are conducted without surrounding bulk reaction mixture. The influences of temperature, pore radius, and surface chemistry on the kinetics of the confined reaction are analyzed with time-dependent infrared spectroscopy, molecular dynamics simulations, and ab initio calculations. The rate constant of the pseudo-first order reaction increases with decreasing pore size, and the activation energy is found to decrease by 5.6 kJ/mol in the smallest pore studied (2.8 nm) relative to the bulk reaction. The rate constant dependence on pore size is accurately described by a two-state model in which molecules within the 4.6 Å interfacial layer experience a 2.4-fold rate constant increase relative to those reacting at the bulk rate further away from the interface. The removal of polar silanol groups from the silica surface via passivation with trimethylsilyl chloride results in bulk-like kinetics despite a reduction in the pore diameter, demonstrating the role of silanols as catalytic sites. Here, electronic structure calculations of the energy profile on a model silica surface confirm that silanol groups, particularly those of the vicinal type, can reduce the activation energy and reaction endothermicity through the donation of hydrogen bonds to the reactant, transition state, and product complexes.

36 MATERIALS SCIENCE↗

Similarities in Meteorological Composites Among Different Atmospheric River Detection Tools During Landfall Over Western Coastal North America

Many atmospheric river detection tools (ARDTs) have been developed over the past few decades to identify atmospheric rivers (ARs). Different ARDTs have been observed to capture a variety of frequencies, shapes, and sizes of ARs. Due to this, questions have arisen about the underlying phenomena associated with the detected ARs: do all ARDTs detect the same meteorological phenomena? In this paper, we assess eight ARDTs and investigate the underlying synoptic scale phenomena during landfalling ARs along the west coast of North America. We find that during landfalling AR events, prevalent low-pressure and high-pressure systems converge and enhance moisture influx toward the landfalling site. We identify that all eight ARDTs identify AR conditions associated with baroclinic waves, with the region of intense integrated vapor transport (IVT) located downstream of the upper level (500 hPa) trough. The magnitude of IVT is enhanced by the strength of the pressure gradients in the confluence region. Although the ARDTs assessed agree on the general phenomena, there are however subtle differences in each ARDT per the clustering analysis we performed. We conclude that the eight ARDTs identify similar underpinning synoptic scale meteorological phenomena.

54 ENVIRONMENTAL SCIENCES↗

Carbon nanospike coated nanoelectrodes for measurements of neurotransmitters

Here, carbon nanoelectrodes enable the detection of neurotransmitters at the level of single cells, vesicles, synapses and small brain structures. Previously, the etching of carbon fibers and 3D printing based on direct laser writing have been used to fabricate carbon nanoelectrodes, but these methods lack the ability of mass manufacturing. In this paper, we mass fabricate carbon nanoelectrodes by growing carbon nanospikes (CNSs) on metal wires. CNSs have a short, dense and defect-rich surface that produces remarkable electrochemical properties, and they can be mass fabricated on almost any substrate without using catalysts. Tungsten wires and niobium wires were electrochemically etched in batch to form sub micrometer sized tips, and a layer of CNSs was grown on the metal wires using plasma-enhanced chemical vapor deposition (PE-CVD). The thickness of the CNS layer was controlled by the deposition time, and a thin layer of CNSs can effectively cover the entire metal surface while maintaining the tip size within the sub micrometer scale. The etched tungsten wires produced tapered conical nanotips, while the etched niobium wires were long and thin. Both showed excellent sensitivity for the detection of outer sphere ruthenium hexamine and the inner sphere test compound ferricyanide. The CNS nanosensors were used for the measurement of dopamine, serotonin, ascorbic acid and DOPAC with fast-scan cyclic voltammetry. The CNS nanoelectrodes had a large surface area and numerous defect sites, which improved the sensitivity, electron transfer kinetics and adsorption. Finally, the CNS nanoelectrodes were compared with other nanoelectrode fabrication methods, including flame etching, 3D printing, and nanopipettes, which are slower to make and more difficult for mass fabrication. Thus, CNS nanoelectrodes are a promising strategy for the mass fabrication of nanoelectrode sensors for neurotransmitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

Activating low-temperature diesel oxidation by single-atom Pt on TiO 2 nanowire array

Supported metal single atom catalysts (SACs) present an emerging class of low-temperature catalysts with high reactivity and selectivity, which, however, face challenges on both durability and practicality. Herein, we report a single-atom Pt catalyst that is strongly anchored on a robust nanowire forest of mesoporous rutile titania grown on the channeled walls of full-size cordierite honeycombs. This Pt SAC exhibits remarkable activity for oxidation of CO and hydrocarbons with 90% conversion at temperatures as low as ~160 °C under simulated diesel exhaust conditions while using 5 times less Pt-group metals than a commercial oxidation catalyst. Such an excellent low-temperature performance is sustained over hydrothermal aging and sulfation as a result of highly dispersed and isolated active single Pt ions bonded at the Ti vacancy sites with 5 or 6 oxygen ions on titania nanowire surfaces.

36 MATERIALS SCIENCE↗

Functional characterization of diverse type I-F CRISPR-associated transposons

CRISPR-Cas systems generally provide adaptive immunity in prokaryotes through RNA-guided degradation of foreign genetic elements like bacteriophages and plasmids. Recently, however, transposon-encoded and nuclease-deficient CRISPR-Cas systems were characterized and shown to be co-opted by Tn7-like transposons for CRISPR RNA-guided DNA transposition. As a genome engineering tool, these CRISPR-Cas systems and their associated transposon proteins can be deployed for programmable, site-specific integration of sizable cargo DNA, circumventing the need for DNA cleavage and homology-directed repair involving endogenous repair machinery. Here, we selected a diverse set of type I-F3 CRISPR-associated transposon systems derived from Gammaproteobacteria, predicted all components essential for transposition activity, and deployed them for functionality testing within Escherichia coli. Our results demonstrate that these systems possess a significant range of integration efficiencies with regards to temperature, transposon size, and flexible PAM requirements. Additionally, our findings support the categorization of these systems into functional compatibility groups for efficient and orthogonal RNA-guided DNA integration. This work expands the CRISPR-based toolbox with new CRISPR RNA-guided DNA integrases that can be applied to complex and extensive genome engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗