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At least 1,279 records · Page 71

Comparative Genomic Analysis of Three Pseudomonas Species Isolated from the Eastern Oyster (Crassostrea virginica) Tissues, Mantle Fluid, and the Overlying Estuarine Water Column

The eastern oysters serve as important keystone species in the United States, especially in the Gulf of Mexico estuarine waters, and at the same time, provide unparalleled economic, ecological, environmental, and cultural services. One ecosystem service that has garnered recent attention is the ability of oysters to sequester impurities and nutrients, such as nitrogen (N), from the estuarine water that feeds them, via their exceptional filtration mechanism coupled with microbially-mediated denitrification processes. It is the oyster-associated microbiomes that essentially provide these myriads of ecological functions, yet not much is known on these microbiota at the genomic scale, especially from warm temperate and tropical water habitats. Among the suite of bacterial genera that appear to interplay with the oyster host species, pseudomonads deserve further assessment because of their immense metabolic and ecological potential. To obtain a comprehensive understanding on this aspect, we previously reported on the isolation and preliminary genomic characterization of three Pseudomonas species isolated from minced oyster tissue (P. alcaligenes strain OT69); oyster mantle fluid (P. stutzeri strain MF28) and the water collected from top of the oyster reef (P. aeruginosa strain WC55), respectively. In this comparative genomic analysis study conducted on these three targeted pseudomonads, native to the eastern oyster and its surrounding environment, provided further insights into their unique functional traits, conserved gene pools between the selected pseudomonads, as well as genes that render unique characteristics in context to metabolic traits recruited during their evolutionary history via horizontal gene transfer events as well as phage-mediated incorporation of genes. Moreover, the strains also supported extensively developed resistomes, which suggests that environmental microorganisms native to relatively pristine environments, such as Apalachicola Bay, Florida, have also recruited an arsenal of antibiotic resistant gene determinants, thus posing an emerging public health concern.

Pathak, Ashish↗

Development of New g-function Data for Simulating a Novel Shallow Bore Ground Heat Exchanger

Geothermal heat pump (GHP), which is also referred as ground source heat pump, is the most energy-efficient technology for space heating and cooling. However, the application of GHP is hindered by its high initial cost, of which approximately 30% is for the ground heat exchanger (GHE). In recent years, researchers have developed different types of shallow bore ground heat exchangers (SBGHE) intending to reduce the cost of drilling. The ability to predict the thermal response of an SBGHE is critical for sizing SBGHE. While g-functions have been commonly used for predicting the thermal response of conventional vertical bore ground heat exchangers (VBGHE), they cannot be directly used for predicting the performance of SBGHE because they did not account for the impacts of the seasonal variation of the soil temperature along with the depth of an SBGHE. In addition, an SBGHE has a larger thermal mass within the borehole than the VBGHE due to the larger borehole diameter of SBGHE. This study develops new g-function data pairs for a new design of SBGHE, which is named Underground Thermal Battery (UTB). Impacts of the seasonal variation of soil temperature on the thermal response of UTB were accounted for by superposing a time-dependent soil temperature onto the g-functions calculated with a numerical model that assumes constant undisturbed soil temperature. The TOUGH program was used to predict the thermal response of several configurations involving multiple UTBs. The results indicate that the proposed methodology is appropriate to generate g-functions for the UTB, and the g-function value of UTB is much lower than that of VBGHE in the time range of 15 min to 1 year due to the large thermal mass and convection heat transfer within the UTB.

Shi, Liang↗

Data-driven modeling and control of dynamical systems using Koopman and Perron-Frobenius operators

This dissertation studies the data-driven modeling and control problem of nonlinear systems by exploiting the linear operator theoretic framework involving Koopman and Perro-Frobenius operator. A systematic linear-operator based controller design procedure has been established, which can be used to solve a variety of nonlinear control problems, including feedback stabilization using control Lyapunov functions, optimal quadratic regulation using Koopman eigenfunctions and convex optimization formulation of optimal control problem using P-F and Koopman operator approximation. As the core of data-driven modeling, we first propose a new algorithm for the finite-dimensional approximation of the linear transfer Koopman and Perron-Frobenius operator from time-series data. We argue that the existing approach for the finite-dimensional approximation of these transfer operators such as Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode Decomposition (EDMD) do not capture two important properties of these operators, namely positivity and Markov property. The algorithm we propose preserves these two properties. We call the proposed algorithm as naturally structured DMD (NSDMD) since it retains the inherent properties of these operators. Naturally structured DMD algorithm leads to a better approximation of the steady-state dynamics of the system regarding computing Koopman and Perron- Frobenius operator eigenfunctions and eigenvalues. However, preserving positivity property is critical for capturing the real transient dynamics of the system. This positivity property of the transfer operators and it's finite-dimensional approximation play an important role for controller and estimator design of nonlinear systems. To solve the feedback stabilization problem for nonlinear control systems, we tried to take advantage of the Koopman operator framework. The Koopman operator approach provides a linear representation for a nonlinear dynamical system and a bilinear representation for a nonlinear control system. The problem of feedback stabilization of a nonlinear control system is then transformed to the stabilization of a bilinear control system. We propose a control Lyapunov function (CLF)-based approach for the design of stabilizing feedback controllers for the bilinear system. The search for finding a CLF for the bilinear control system is formulated as a convex optimization problem. This leads to a schematic procedure for designing CLF-based stabilizing feedback controllers for the bilinear system and hence the original nonlinear system. Another advantage of the proposed controller design approach outlined in this dissertation is that it does not require explicit knowledge of system dynamics. In particular, the bilinear representation of a nonlinear control system in the Koopman eigenfunction space can be obtained from time-series data. Next, we study the optimal quadratic regulation problem for nonlinear systems. The linear operator theoretic framework involving the Koopman operator is used to lift the dynamics of nonlinear control system to an infinite-dimensional bilinear system. The optimal quadratic regulation problem for nonlinear system is formulated in terms of the finite-dimensional approximation of the bilinear system. A convex optimization-based approach is proposed for solving the quadratic regulator problem for bilinear system. We applied a variety of examples and compared the simulation results between our framework and conventional LQR control using linearized model. For more general optimal control problems, we provide a density-function based convex formulation for the optimal control problem of the nonlinear system. The convex formulation relies on the duality result in the stability theory of a dynamical system involving density function and Perron-Frobenius operator. The optimal control problem is formulated as an infinite-dimensional convex optimization program. The finite-dimensional approximation of the optimization problem relies on the recent advances made in the data-driven computation of the Koopman operator, which is dual to the Perron-Frobenius operator. Simulation results are presented to demonstrate the application of the developed framework.

Huang, Bowen↗

Toward extreme high-temperature supercritical CO 2 power cycles: Leakage characterization of ceramic 3D-printed heat exchangers

We report future supercritical carbon dioxide (sCO 2 ) Brayton power cycles demand high-performance gas-to-gas heat exchangers (HXs) operating under extreme temperature and pressure conditions at which most existing superalloy materials fail to function safely. Ceramic HXs are deemed excellent candidates for advanced sCO 2 power plants as they can withstand high-temperature working environments. Particularly, ceramic 3D printing enables compact HX topologies employing complex and efficient heat transfer features. However, ceramic 3D-printed walls separating hot and cold flow streams are susceptible to a through-plane leakage inherent to a powder-based manufacturing process, including ceramic 3D printing. A potential leakage through ceramic separating walls poses a significant challenge in developing reliable ceramic 3D-printed HXs and could deteriorate thermal performance. In this study, various parameters, including feedstock slurry, 3D-printing direction, and post-processing conditions, are considered, for the first time, to characterize the argon gas leakage rate associated with alumina 3D-printed parts. Three 3D-printed ceramic structures of flat plates, curved tubes, and small-scale plate-and-frame HXs with various thicknesses are systematically studied to determine powder and ceramic 3D-printing conditions to eliminate the through-plane leakage. The results showed that an alumina 3D-printed plate with a thickness of 0.75 mm demonstrates a permeability of 6 x 10 -4 milli-darcy. An alumina 3D-printed tube with a wall thickness of 0.9 mm revealed a permeability of 9.6 x 10 -7 milli-darcy. Furthermore, leakage test results of functional 3D-printed modules showed a dependency on the 3D-printing direction. Particularly, alumina cell-scale HXs employing 1.5-mm-thick horizontal and vertical 3D-printed separating walls demonstrated impermeability and gas permeability of 7.2 x 10 -5 millidarcy, respectively. Insights gained from the present study facilitate the development of complex ceramic 3D-printed HXs and other balance of plant components for next-generation high-temperature high-pressure sCO 2 power cycles.

36 MATERIALS SCIENCE↗

Proton spin structure and generalized polarizabilities in the strong quantum chromodynamics regime

The strong interaction is not well understood at low energies or for interactions with low momentum transfer. Chiral perturbation theory gives testable predictions for the nucleonic generalized polarizabilities, which are fundamental quantities describing the nucleon’s response to an external field. We report a measurement of the proton’s generalized spin polarizabilities extracted with a polarized electron beam and a polarized solid ammonia target in the region where chiral perturbation theory is expected to be valid. The investigated structure function g2 characterizes the internal spin structure of the proton. From its moments, we extract the longitudinal–transverse spin polarizability δLT and twist-3 matrix element and polarizability d2¯. Our results provide discriminating power between existing chiral perturbation theory calculations and will help provide a better understanding of this strong quantum chromodynamics regime.

Ruth, D↗

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, in this study, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.

36 MATERIALS SCIENCE↗

Distinguishing Desirable and Undesirable Reactions in Multicomponent Systems for Redox Activation of the Uranyl Ion

Although it has been established that covalent functionalization of the U–O bonds in the uranyl dication (UO 2 2+ ) generally requires use of strong reductants and electrophiles, little work has examined how interactions between the individual reaction components could affect final outcomes in solution. Here, the patterns of such reactivity have been studied in a UO 2 2+ -containing model system supported by a workhorse pentadentate ligand, 2,2′-[(methylimino)bis(2,1-ethanediylnitrilomethylidyne)]bis-phenol. Oxo activation and functionalization have been tested with (i) electrochemical and chemical reduction, and (ii) coordinating and noncoordinating solvents. In acetonitrile, uranyl reduction was achieved cleanly, but treatment of the reduced species with tris(pentafluorophenyl)borane (BCF) resulted in a mixture of products arising from direct electron transfer to BCF. In dichloromethane (CH 2 Cl 2 ), electrochemical reduction of uranyl was achieved cleanly, but clean chemical reactivity was inaccessible. Despite these challenges, one trinuclear and oxo-deficient uranium-containing product was crystallized from CH 2 Cl 2 solution and characterized; thus, desirable electrophilic reactivity can proceed to some degree in CH 2 Cl 2 with BCF. Computational studies were used to investigate the properties of the trinuclear uranium product and the changes that could be inducible by further reduction. Here, taken together, the reactivity patterns identified here could inform design of improved systems for actinyl oxo functionalization.

cations↗

Transient Triamidoamine Neptunium(V)–Mono(Imido) Complexes: C–H Activations and Hydrogen Atom Transfer Driven by Effective Nuclear Charge

Metal-mono(imido) linkages have been known for seven decades, and they are found in transition metal, main group, lanthanide, thorium, and uranium complexes. However, transuranium-mono(imido) complexes remain unknown in any scenario. Here, we present evidence for transient neptunium(V)–mono(imido) complexes. Treatment of [Np III (Tren TIPS )] (1, Tren TIPS = {N(CH 2 CH 2 NSiPr i 3 ) 3 } 3– ) with N 3 R (R = SiMe 3 ; 1-adamantyl, Ad) results in N 2 evolution and dark purple solutions consistent with the formation of [Np V (Tren TIPS )(NR)] (3NpNR). However, solutions of 3NpNR rapidly turn orange, where for R = SiMe 3 the isolated 1:1 products are [Np IV (Tren TIPS ){N(H)SiMe 3 }] (4a) and [Np IV (Tren TIPS-2H ){N(H)SiMe 3 }] (4b, Tren TIPS-2H = {N(CH 2 CH 2 NS i Pri 3 ) 2 (NCH 2 CH 2 NSiPr i 2 C[Me]=CH 2 )} 3– ). The latter contains a dehydrogenated-Pr i vinyl functionality accounting for the source of the two amido H atoms. The reaction for R = Ad proceeds similarly, but only [Np IV (Tren TIPS ){N(H)Ad}] (5a) could be unequivocally confirmed, though its isolation suggests generality of the imido-to-amido functional group transformation. Complexes 4a/4b exhibit slow relaxation of their magnetization, adding to the small number of transuranium single ion magnets. Experimental and computational analysis suggests that the amido products are formed by C–H activation and two sequential hydrogen atom transfer reactions involving a three-step proton-coupled electron-transfer sequence of H • radical abstraction, electron transfer, then another H • radical abstraction step. In contrast to transient 3NpNR, the 5f 2 uranium(IV)-imido complex [K(2.2.2-cryptand)][U IV (Tren TIPS )(NSiMe 3 )] (8UNSiMe 3 ) is robust, even in boiling THF, suggesting the transience of 5f 2 3NpNR is not due to the 5f n -count but the increased effective nuclear charge of neptunium vs uranium. This work highlights divergence of uranium- and neptunium-imido stabilities, emphasizing that the latter is an inherently challenging synthetic target.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Support of the Third Summer School and Workshop Focused on Theory and Applications of Time-Dependent Density Functional Theory, Electronic Excited States, and Excited State Dynamics

To create a community of scholars with a deep understanding of TDDFT and excited state methods, both their capabilities and limitations, and how they can be used to model the excited state properties and charge transfer in materials and molecules, we are planning the third iteration of a summer school and workshop focusing on theory and applications of TDDFT, Excited States, and Excited State Dynamics to be offered in the summer of 2023. The two iterations of the US-based school that we previously organized have been very successful with overwhelmingly positive feedback. There is a high level of engagement, enthusiasm, and active participation and networking amongst the students of the school and the scientists of the workshop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Driving Electron Transfer in Photosystem I Using Far-Red Light: Overall Perspectives

Photosystem I (PSI) is a photosynthetic protein–pigment complex that, upon photoexcitation, transfers electrons to ferredoxin, facilitating the production of NADPH. Isolated PSI reaction centers (RCs) have also been used in hybrid systems to reduce protons and produce ‘biohydrogen’. This review article examines how various cyanobacteria with similar photosynthetic machinery utilize different wavelengths of light to execute photosynthetic electron transport through PSI. Key factors, such as, the structure of the electron transfer cofactors, the protein environment surrounding the primary donor pigments and hydrogen-bonding interactions with the surrounding protein matrix are analyzed to understand their roles in maintaining efficient electron transfer when it is driven using photons of different energies. We compare PSI complexes with known atomic structures from four species of cyanobacteria, Thermosynechococcus elongatus, Acaryochloris marina, Halomicronema hongdechloris, and Fischerella thermalis. T. elongatus is typical of most oxygenic photosynthetic organisms in that it requires visible light and uses only chlorophyll a (Chl a ) in PSI. In contrast, H. hongdechloris and F. thermalis are photoacclimating species capable of producing Chl f and Chl d that use red light when little visible light is available. A. marina , on the other hand, is adapted to red light conditions and consistently utilizes Chl d as its primary photosynthetic pigment, maintaining a stable pigment composition. Here, we explore the structural and functional differences between the PSI RCs of these organisms and the impact of these differences on electron transport. The structural differences in the cofactors influence both the absorption wavelengths of the cofactors and the energy levels of the intermediate states of electron transfer. An analysis of the surrounding protein shows how it has been adapted and underscores the interplay between the pigment structure, protein environment, and hydrogen bonding networks in tuning the efficiency and adaptability of photosynthetic mechanisms across different species of cyanobacteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomically Precise Membranes for the Separation of Gases

Industrial separations require enormous amounts of energy, accounting for approximately half the industrial energy use and 10–15% of the total energy consumption. Distillation alone accounts for about half the energy demand for industrial separations. If these processes could be replaced by an energy-efficient membrane separation process, this energy demand could be reduced by 90%. However, although some membrane processes have made inroads into thermal distillation, for membrane-based separations to replace the distillation process to a far more significant and practical level, new membranes with higher robustness, selectivity, and flux still need be developed. In this membrane development program, we leveraged Temple University’s prior work in spiroligomers to develop robust membrane structures. These structures can be formed into atomically precise pores by controlling the chemical synthesis and the oligomer building blocks to first build precisely controlled macrocycles and then subsequently crosslinking these macrocycles to produce a membrane. Furthermore, through the highly controllable chemistry of our molecular building blocks, not only can we integrate pores with highly controllable and reproducible size and morphology, but we can also target internal functionalization. By using a range of scalable membrane synthesis approaches, combined with control of each and every pores internal chemistry and molecular conformation we can achieve membrane structures that can display the ultimate in high selectivity and permeance. The Mainstream-Temple University membranes can be designed to achieve ultra-selective separations based on the key factors of molecular size, shape, and functionality. In our approach to fabricate scalable atomically precise membranes, we used our molecular Lego nanostructures. We demonstrated an approach to create atomically precise pores within the membrane with pores that are the dimensions of the molecule we are trying to separate. Moreover, in addition to controlling the morphology of the membrane structure by controlling the size of every pore, we can also decorate every pore with precisely targeted and placed functional groups. These accurately placed functional groups can provide selective binding to molecules and provide enhanced selectivity via a facilitated transport mechanism. In Phase II, the Mainstream-Temple University team demonstrated the scalable synthesis of oligomers and the ability to control the pore internal and external functionality, or chemistry, to allow the fabrication of a thin-film membrane. The initial steps of the spiroligomer synthesis to produce the two key bis-amino enantiomer building blocks were scaled from the gram scale to the kilogram scale, obtaining 25 kg of the materials by transferring the procedure to a toll manufacturer. Finally, we successfully optimized the fabrication of these macrocycles into robust membranes. We successfully transitioned from a laboratory based, hard-to-scale Langmuir trough synthesis to a highly scalable, roll-to-roll applicable, interfacial polymerization process. During this Phase II program, we established a platform of atomically precise membranes where our highly controllable, atomically precise macrocycles served as a scaffold with precisely and uniformly controlled pores. Furthermore, this layer can be tailored to accommodate a diverse range of functional groups, which both further controlled the pore size to enhance the sieving effect as well as imparting precisely controlled targeted selectivity through biomimetic molecular interactions. In this Phase II, we established and scaled up a platform approach to both tune the pore size and chemistry as well as scale it to produce membranes that can be applied to a wide range of industries. In future development, the project team expects to scale up both the macrocycle building block production and interfacial polymerization process to produce the atomically precise membrane with targeted pore sizes and pore chemistries.

36 MATERIALS SCIENCE↗

Redox-Induced Structural Reorganization Dictates Kinetics of Cobalt(III) Hydride Formation via Proton-Coupled Electron Transfer

Two-electron, one-proton reactions of a family of [CoCp(dxpe)(NCCH 3 )] 2+ complexes (Cp = cyclopentadienyl, dxpe = 1,2-bis(di(aryl/alkyl)phosphino)ethane) form the corresponding hydride species [HCoCp(dxpe)] + through a stepwise proton-coupled electron transfer process. For three [CoCp(dxpe)(NCCH 3 )] 2+ complexes (dxpe = dppe (1,2-bis(diphenylphosphino)ethane), depe (1,2-bis(diethylphosphino)ethane), and dcpe (1,2-bis(dicyclohexylphosphino)ethane)), peak shift analysis was employed to quantify apparent proton transfer rate constants from cyclic voltammograms recorded with acids ranging 22 pK a units. The apparent proton transfer rate constants correlate with the strength of the proton source for weak acids, but these apparent proton transfer rate constants curiously plateau (k pl ) as the reaction becomes increasingly exergonic. The absolute apparent proton transfer rate constants across both these regions correlate with the steric bulk of the chelating diphosphine ligand, with bulkier ligands leading to slower kinetics (k plateau,depe = 3.5 x 10 7 M -1 s -1 , k plateau,dppe = 1.7 x 10 7 M -1 s -1 , k plateau,dcpe = 7.1 x 10 4 M -1 s -1 ). Mechanistic studies were conducted to identify the cause of the aberrant $k_PT^{app}$–ΔpK a trends. When the deuterated acids are employed, deuterium incorporation in the Cp ring is observed, indicating protonation of the CoCp(dxpe) species to form the corresponding hydride proceeds via initial ligand protonation. Digital simulations of cyclic voltammograms show ligand loss accompanying initial reduction gates subsequent PCET activity at higher driving forces. Together, these experiments reveal the details of the reaction mechanism: reduction of the Co(III) species is followed by dissociation of the bound acetonitrile ligand, subsequent reduction of the unligated Co(II) species to form a Co(I) species is followed by protonation, which occurs at the Cp ring, followed by tautomerization to generate the stable Co(III)-hydride product [HCoCp(dxpe)] + . Analysis as a function of chelating disphosphine ligand, solvent, and acid strength reveals that the ligand dissociation equilibrium is directly influenced by the steric bulk of the phosphine ligands and gates protonation, giving rise to the plateau of apparent proton transfer rate constant with strong acids. The complexity of the reaction mechanism underpinning hydride formation, encompassing dynamic behavior of the entire ligand set, highlights the critical need to understand elementary reaction steps in proton-coupled electron transfer reactions.

14 SOLAR ENERGY↗

The HypA and HypB metallochaperones from Methanococcus maripaludis have unique metal-binding properties and a distinct nickel transfer mechanism

[NiFe] hydrogenases are widespread microbial metalloenzymes that catalyze the reversible conversion of hydrogen (H2) to protons and electrons, playing key roles in energy metabolism. The biosynthesis of the NiFe(CN) 2 CO cofactor involves a suite of maturation proteins, including the HypA and HypB nickel metallochaperones. Here, we define the metal-binding properties, nucleotide-dependent behavior, and functional interplay of HypA and HypB from the hydrogenotrophic methanogenic archaeon, Methanococcus maripaludis . Methanogens have multiple essential nickel-dependent enzymes, so they require efficient systems for nickel delivery that remain largely unexplored. Purified M. maripaludis HypA binds zinc or mononuclear iron at the C-terminal metal binding site, the latter of which has not been reported in other HypA proteins and may serve a unique regulatory role in methanogens. The G-protein metallochaperone HypB binds nickel at the G-domain, which stimulates GTPase activity. Size exclusion chromatography experiments reveal that HypA and HypB form complexes in the presence of nickel, and zinc-bound HypA is optimized for nickel transfer from HypB. The identity of the nucleotide bound to HypB (GDP or GTP) alters the oligomeric state of HypA-HypB complexes, supporting a GTPase-mediated nickel delivery pathway. The HypA-HypB 2 complex configuration is enriched and stable in the presence of GDP and nickel, indicating that this complex delivers nickel to the hydrogenase as opposed to HypA alone. Interestingly, affinity purification-mass spectrometry revealed that HypB interacts with several nickel-dependent proteins, suggesting that HypB may play a broader role in nickel homeostasis in M. maripaludis . Together, this work establishes a biochemical framework for HypAB-mediated nickel trafficking in methanogens.

[NiFe] hydrogenase↗

Balancing Panchromatic Absorption and Multistep Charge Separation in a Compact Molecular Architecture

A panchromatic triad and a charge-separation triad are joined in a crossbar architecture to capture solar energy. The panchromatic triad (T) is comprised of a central free-base porphyrin that is strongly coupled via direct ethyne linkages to two perylene-monoimides. Here, the charge-separation unit incorporates a free-base or zinc chlorin (C or ZnC) as a hole acceptor (or electron donor) and a perylene-diimide (PDI) as an electron acceptor, both attached to the porphyrin via diphenylethyne linkers. The free-base porphyrin is common to both light-harvesting and charge-separation motifs. The chlorin and PDI also function as ancillary light absorbers, complementing direct excitation of the panchromatic triad to produce the discrete lowest excited state of the array (T*). Attainment of full charge separation across the pentad entails two steps: (1) an initial excited-state hole/electron transfer process to oxidize the chlorin (and reduce the triad) or reduce the PDI (and oxidize the triad); and (2) subsequent ground-state electron/hole migration to produce oxidized chlorin and reduced PDI. Full charge separation for pentad ZnC-T-PDI to generate ZnC + -T-PDI¯ occurs with a quantum yield of ~30% and mean lifetime ~1 μs in dimethyl sulfoxide. For C-T-PDI, initial charge separation is followed by rapid charge recombination. The molecular designs and studies reported here reveal the challenges of balancing the demands for charge separation (linker length and composition, excited-state energies, redox potentials, and medium polarity) with the constraints for panchromatic absorption (strong electronic coupling of the porphyrin and two perylene-monoimide units) for integrated function in solar-energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cross Inference of Throughput Profiles Using Micro Kernel Network Method

Dedicated network connections are being increasingly deployed in cloud, centralized and edge computing and data infrastructures, whose throughput profiles are critical indicators of the underlying data transfer performance. Due to the cost and disruptions to physical infrastructures, network emulators, such as Mininet, are often used to generate measurements needed to estimate throughput profiles, typically expressed as a function of the connection round trip time. The profiles estimated using measurements from such emulated networks are usually inaccurate for high bandwidth and high latency connections, since they do not accurately reflect the critical network transport dynamics mainly due to computing and memory constraints of the host. We present a machine learning (ML) method to estimate the throughput profiles using emulation measurements to closely match the testbed and production network profiles. In particular, we propose a micro Kernel Network (mKN) that provides baseline throughput measurements on the host running Mininet emulations, which are used to learn a regression map that converts them to the corresponding testbed measurement estimates. Once initially learned, this map is applied to measurements from subsequent network emulations on the same host. We present experimental measurements to illustrate this approach, and derive generalization equations for the proposed mKN-ML method. Using a four-site scenario emulation, we show the effectiveness of this method in providing accurate concave throughput profiles from inaccurate convex or non-smooth ones indicated by Mininet emulation.

Rao, Nageswara↗

Mechanisms of water oxidation on heterogeneous catalyst surfaces

Water oxidation, an essential step in photosynthesis, has attracted intense research attention. Understanding the reaction pathways at the electrocatalyst/water interface is of great importance for the development of water oxidation catalysts. How the water is oxidized on the electrocatalyst surface by the positive charges is still an open question. This review summarizes current advances in studies on surface chemistry within the context of water oxidation, including the intermediates, reaction mechanisms, and their influences on the reaction kinetics. The Tafel analyses of some electrocatalysts and the rate-laws relative to charge consumption rates are also presented. Moreover, how the multiple charge transfer relies on the intermediate coverage and the accumulated charge numbers is outlined. Finally, the intermediates and rate-determining steps on some water oxidation catalysts are discussed based on density functional theories.

14 SOLAR ENERGY↗

Mapping valence electron distributions with multipole density formalism using 4D-STEM

Recent advancement in aberration correction and detector technology opened a door to various applications using 4D-STEM, which yields a diffraction pattern for each scanning position within a crystal unit-cell in scanning transmission electron microscopy (STEM) and generates incredible amounts of data in momentum space. Currently 4D-STEM analysis relies on the center-of-mass of the diffraction patterns in electric field and charge density mapping. It only derives the total projected charge density and is limited to phase objects, e.g. extremely thin samples. Here, we propose a new analytical method to accurately map aspherical valence electron distributions with atom-centered multipolar functions formalism using the whole 4D-STEM dataset. We demonstrate that, with the full dynamical calculations for various sample thicknesses, the method is sensitive not only to the miniscule charge transfer, but also to the atomic site symmetry and aspherical electron orbitals. The process of the refinement is much more robust and reliable than quantitative convergent beam electron diffraction.

4D-STEM↗

Enabling selective zinc-ion intercalation by a eutectic electrolyte for practical anodeless zinc batteries

Abstract Two major challenges hinder the advance of aqueous zinc metal batteries for sustainable stationary storage: (1) achieving predominant Zn-ion (de)intercalation at the oxide cathode by suppressing adventitious proton co-intercalation and dissolution, and (2) simultaneously overcoming Zn dendrite growth at the anode that triggers parasitic electrolyte reactions. Here, we reveal the competition between Zn 2+ vs proton intercalation chemistry of a typical oxide cathode using ex-situ/ operando techniques, and alleviate side reactions by developing a cost-effective and non-flammable hybrid eutectic electrolyte. A fully hydrated Zn 2+ solvation structure facilitates fast charge transfer at the solid/electrolyte interface, enabling dendrite-free Zn plating/stripping with a remarkably high average coulombic efficiency of 99.8% at commercially relevant areal capacities of 4 mAh cm −2 and function up to 1600 h at 8 mAh cm −2 . By concurrently stabilizing Zn redox at both electrodes, we achieve a new benchmark in Zn-ion battery performance of 4 mAh cm −2 anode-free cells that retain 85% capacity over 100 cycles at 25 °C. Using this eutectic-design electrolyte, Zn | |Iodine full cells are further realized with 86% capacity retention over 2500 cycles. The approach represents a new avenue for long-duration energy storage.

25 ENERGY STORAGE↗