Reassessing evidence of life in 3,700-million-year-old rocks of Greenland
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The ability of proteins and other macromolecules to interact with inorganic surfaces is critical to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains1–5, but the structures of most protein-inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein-mineral interfaces guided by the example of ice-binding proteins, which present arrays of threonine residues matched to the ice lattice that order clathrate waters into an ice-like structure6. We designed proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the K+ sub-lattice on muscovite mica (001). At low [K+] individual molecules bind independently to mica in the designed orientations, while at high [K+], the designs form 2D liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimeters. Incorporation of designed protein-protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micron long single protein-diameter wires, and a designed trimeric interface yielded extensive honeycomb arrays. The nearest neighbor distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nm with 2.1 nm selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein-inorganic lattice interactions can be systematically programmed and set the stage for designing protein-inorganic hybrid materials.
Soils store more carbon than other terrestrial ecosystems. How soil organic carbon (SOC) forms and persists remains uncertain, which makes it challenging to understand how it will respond to climatic change. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.
Abstract Both intra-pore hydrate morphology and inter-pore hydrate distribution influence the physical properties of hydrate-bearing sediments, yet there has been no pore-scale observations of hydrate habit under pressure in preserved pressure core samples so far. We present for the first time a pore-scale micro-CT study of natural hydrate-bearing cores that were acquired from Green Canyon Block 955 in UT-GOM2-1 Expedition and preserved within hydrate pressure–temperature stability conditions throughout sub-sampling and imaging processes. Measured hydrate saturation in the sub-samples, taken from units expected to have in-situ saturation of 80% or more, ranges from 3 ± 1% to 56 ± 11% as interpreted from micro-CT images. Pore-scale observations of gas hydrate in the sub-samples suggest that hydrate in silty sediments at the Gulf of Mexico is pore-invasive rather than particle displacive, and hydrate particles in these natural water-saturated samples are pore-filling with no evidence of grain-coating. Hydrate can form a connected 3D network and provide mechanical support for the sediments even without cementation. The technical breakthrough to directly visualize particle-level hydrate pore habits in natural sediments reported here sheds light on future investigations of pressure- and temperature-sensitive processes including hydrate-bearing sediments, dissolved gases, and other biochemical processes in the deep-sea environment.
Abstract Realizing the potential of near-term quantum computers to solve industry-relevant constrained-optimization problems is a promising path to quantum advantage. In this work, we consider the extractive summarization constrained-optimization problem and demonstrate the largest-to-date execution of a quantum optimization algorithm that natively preserves constraints on quantum hardware. We report results with the Quantum Alternating Operator Ansatz algorithm with a Hamming-weight-preserving XY mixer (XY-QAOA) on trapped-ion quantum computer. We successfully execute XY-QAOA circuits that restrict the quantum evolution to the in-constraint subspace, using up to 20 qubits and a two-qubit gate depth of up to 159. We demonstrate the necessity of directly encoding the constraints into the quantum circuit by showing the trade-off between the in-constraint probability and the quality of the solution that is implicit if unconstrained quantum optimization methods are used. We show that this trade-off makes choosing good parameters difficult in general. We compare XY-QAOA to the Layer Variational Quantum Eigensolver algorithm, which has a highly expressive constant-depth circuit, and the Quantum Approximate Optimization Algorithm. We discuss the respective trade-offs of the algorithms and implications for their execution on near-term quantum hardware.
Abstract Weak form equation learning and surrogate modeling has proven to be computationally efficient and robust to measurement noise in a wide range of applications including ODE, PDE, and SDE discovery, as well as in coarse-graining applications, such as homogenization and mean-field descriptions of interacting particle systems. In this work we extend this coarse-graining capability to the setting of Hamiltonian dynamics which possess approximate symmetries associated with timescale separation. A smooth $$\varepsilon$$ ε -dependent Hamiltonian vector field $$X_\varepsilon$$ X ε possesses an approximate symmetry if the limiting vector field $$X_0=\lim _{\varepsilon \rightarrow 0}X_\varepsilon$$ X 0 = lim ε → 0 X ε possesses an exact symmetry. Such approximate symmetries often lead to the existence of a Hamiltonian system of reduced dimension that may be used to efficiently capture the dynamics of the symmetry-invariant dependent variables. Deriving such reduced systems, or approximating them numerically, is an ongoing challenge. We demonstrate that WSINDy can successfully identify this reduced Hamiltonian system in the presence of large perturbations imparted in the $$\varepsilon >0$$ ε > 0 regime, while remaining robust to extrinsic noise. This is significant in part due to the nontrivial means by which such systems are derived analytically. WSINDy naturally preserves the Hamiltonian structure by restricting to a trial basis of Hamiltonian vector fields. The methodology is computationally efficient, often requiring only a single trajectory to learn the global reduced Hamiltonian, and avoiding forward solves in the learning process. In this way, we argue that weak-form equation learning is particularly well-suited for Hamiltonian coarse-graining. Using nearly-periodic Hamiltonian systems as a prototypical class of systems with approximate symmetries, we show that WSINDy robustly identifies the correct leading-order system, with dimension reduced by at least two, upon observation of the relevant degrees of freedom. While our main contribution is computational, we also provide a contribution to the literature on averaging theory by proving that first-order averaging at the level of vector fields preserves Hamiltonian structure in nearly-periodic Hamiltonian systems. This provides theoretical justification for our approach as WSINDy’s computations occur at the level of Hamiltonian vector fields. We illustrate the efficacy of our proposed method using physically relevant examples, including coupled oscillator dynamics, the Hénon–Heiles system for stellar motion within a galaxy, and the dynamics of charged particles.
Biomass incorporates carbon captured from the atmosphere and can serve as a renewable feedstock for producing valuable chemicals and fuels. Here we look at how electrochemical approaches can impact biomass valorization, focusing on identifying chemical transformations that leverage renewable electricity and feedstocks to produce valorized products via electro-privileged transformations. First, we recommend that the field should explore widening the spectrum of platform chemicals derived from bio-feedstocks, thus offering pathways to molecules that have historically been derived from petroleum. Second, we identify opportunities in electrocatalytic production of energy-dense fuels from biomass that utilize water as the hydrogen source and renewable electricity as the driving force. Finally, we look at the potential in electrochemical depolymerization to preserve key functional groups in raw feedstocks that would otherwise be lost during harsh pre-treatments in traditional depolymerization routes. Finally, on the basis of these priorities, we suggest a roadmap for the integration of biomass and electrochemistry and offer milestones required to tap further into the potential of electrochemical biomass valorization.
In Newtonian mechanics, studying a system in a non-Galilean reference frame can lead to inertial pseudoforces appearing, such as the centrifugal force that seems to arise in dynamics analysed in a rotating frame. Likewise, artificial effects may arise in relativistic quantum field theory (QFT) if a system is studied in a framework that violates Poincaré invariance. Here, we highlight how such issues complicate the traditional canonical quantization of QFTs and can lead to a subjective description of natural phenomena. By contrast, the treatment of the same problem using light-front quantization is free from spurious pseudoeffects because Poincaré invariance is effectively preserved for all practical intents and purposes. We illustrate these statements using several examples: the Gerasimov-Drell-Hearn (GDH) relation, a fundamental feature of QFT; the absence of any measurable impact of Lorentz contraction in high-energy collisions; and the fictitious character of vacuum fluctuation contributions to the cosmological constant.
In this study, we briefly review single-qubit quantum process tomography for trace-preserving and nontrace-preserving processes, and derive explicit forms of the general constraints for fitting experimental data. These forms provide additional insight into the structure of the process matrix. We illustrate this with several examples, including a discussion of qubit leakage error models and the intuition which can be gained from their process matrices.
N1-methyl-deoxyadenosine (1-MeA) is formed by methylation of deoxyadenosine at the N1 atom. 1-MeA presents a block to replicative DNA polymerases due to its inability to participate in Watson-Crick (W-C) base pairing. Here we determine how human DNA polymerase-ι (Pol$\iota$) promotes error-free replication across 1-MeA. Steady state kinetic analyses indicate that Pol$\iota$ is ~100 fold more efficient in incorporating the correct nucleotide T versus the incorrect nucleotide C opposite 1-MeA. To understand the basis of this selectivity, we determined ternary structures of Polι bound to template 1-MeA and incoming dTTP or dCTP. In both structures, template 1-MeA rotates to the syn conformation but pairs differently with dTTP versus dCTP. Thus, whereas dTTP partakes in stable Hoogsteen base pairing with 1-MeA, dCTP fails to gain a “foothold” and is largely disordered. Together, our kinetic and structural studies show how Polι maintains discrimination between correct and incorrect incoming nucleotide opposite 1-MeA in preserving genome integrity.
Delafossite oxides are promising hole transport layer (HTL) candidates for perovskite solar cells, due to their wide band gap, favorable energy band alignment relative to the perovskite absorber and simplicity of processing. In this paper, we investigate the properties of CuCrO2 (CCO) delafossite films using an integration of experimental and computational techniques. Phase-pure CCO films are deposited at room temperature by spin-casting suspensions of hydrothermally-synthesized nanoparticles, for use in a glass/ITO/CCO/CH3NH3PbI3/C60/BCP/Ag device structure. Although density functional theory (DFT) calculations predict an elevated hole effective mass along certain crystallographic directions, the nearly isotropic shape and small size of the CCO nanoparticles preserves transport properties within the films by randomizing particle orientation, preventing these unfavorable directions from dominating the film conductivity. Experimental measurements confirm that the CCO films display appropriate optical and electrical properties for use as an HTL, in good agreement with the DFT calculations. Solar cells made using these films exhibit stabilized power conversion efficiencies exceeding 14%, with only minor hysteresis in the current–voltage characteristics.
Photosynthetic flavodiiron (Flv) proteins bind flavin and non-heme Fe cofactors and catalyze the oxygen reduction reaction (ORR) coupled to oxidation of reduced pyridine nucleotides during photosynthetic growth. The activity of Flvs have also been observed to form an important catalytic redox loop with water oxidation necessary for preserving photosynthetic electron transport function in cyanobacteria. To determine how these functions may be related, we investigated the kinetic properties of Flv1 and Flv3 from Synechocystis sp. PCC 6803. Under an oxygen atmosphere, Flv1 and Flv3 were found to catalyze ORR with either NADH or NADPH as the electron donor. Reaction velocity curves were sigmoidal and Flv binding of NAD(P)H was cooperative. Based on mass spectrometry generated structural models, each Flv assembles as a homodimer with two oxidoreductase domains capable of binding two molecules of NAD(P)H per subunit, and the flavins are arranged to support electron transfer to the diiron sites for oxygen reduction. Titrations with NAD(P)H resulted in reduction of the diiron site without the accumulation of stable, reduced flavin intermediates. Altogether, the results provide new insights on the properties of Flv1 and Flv3 that enable tight control of reactivity for the complete reduction of oxygen to water, and in this capacity help preserve photosynthetic electron transport function.
Quantum information processors based on trapped atoms utilize laser-induced optical cycling transitions for state preparation and measurement. These transitions consist of an electronic excitation from the ground to an excited state and a decay back to the initial ground state, associated with a photon emission. While this technique has been used primarily with atoms, it has also recently been shown to work for some divalent metal hydroxides ( e.g. SrOH) and alkoxides ( e.g. SrOCH 3 ). Additionally, this extension to molecules is possible because these molecules feature nearly isolated, atomic-like ground and first-excited electronic states centered on the radical metal atom. We theoretically investigate the extension of this idea to a larger scale by growing the alkyl group, R, beyond the initial methyl group, CH 3 , while preserving the isolated and highly vertical character of the electronic excitation on the radical metal atom, M. Theory suggests that in the limit as the size of the ligand carbon chain increases, it can be considered a functionalized diamond (or cubic boron nitride) surface. Several requirements must be observed for the cycling centers to function when bound to the surface. First, the surface must have a significant band gap that fully encapsulates both the ground and excited states of the cycling center. Second, while the surface lattice imposes strict limits on the achievable spacing between the SrO– groups, at high coverage, SrO– centers can interact, and show geometric changes and/or electronic state mixing. We show that the coverage of the diamond surface with SrO– cycling centers needs to be significantly sub-monolayer for the functionality of the cycling center to be preserved. Having the lattice-imposed spatial control of SrO– placements will allow nanometer-scale proximity between qubits and will eliminate the need for atom traps for localized cycling emitters. Our results also imply that a functionalization could be done on a scanning microscope tip for local quantum sensing or on photonic structures for optically-mediated quantum information processing.
Since the first reports of metal–organic frameworks (MOFs), this unique class of crystalline, porous materials has garnered increasing attention in a wide variety of applications such as gas storage and separation, catalysis, enzyme immobilization, drug delivery, water capture, and sensing. A fundamental feature of MOFs is their porosity which provides space on the micro- and meso-scale for confining and exposing their functionalities. Therefore, designing MOFs with high porosity and developing suitable activation methods for preserving and accessing their pore space have been a common theme in MOF research. Reticular chemistry allows for the facile design of MOFs from highly tunable metal nodes and organic linkers in order to realize different pore structures, topologies, and functionalities. With the hope of shedding light on future research endeavors in MOF porosity, it is worthwhile to examine the development of MOFs, with an emphasis on their porosity and how to properly access their pore space. In this review, we will provide an overview of the historic evolution of porosity and activation of MOFs, followed by a synopsis of the strategies to design and preserve permanent porosity in MOFs.
Zirconia supported tungstates catalyze octadecanol dehydration, an important step in the carbon preserving conversion of triglycerides to fuels.
The biggest obstacle to the widespread implementation of polymer electrolyte membrane fuel cells (PEMFCs) is their cost, primarily due to the use of platinum catalysts. The high intrinsic catalyst activity exhibited on a rotating disk electrode (RDE) is rarely realized in a membrane electrode assembly (MEA), which is a long-standing challenge for PEMFCs and a cause of low catalyst utilization. To translate the high RDE performance of a catalyst into a MEA, the design of an ideal ionomer/catalyst interface is proposed: a thin, conformal ionomer film covers the maximum surface of a Pt nanoparticle and thus simultaneously maximizes catalyst utilization, (i.e., high mass activity and electrochemically active surface area) and O 2 diffusion rate (i.e., high current density performance) without compromising proton conduction. Building such an interface is a long-standing challenge due to the lack of interaction between the ionomer and catalyst particles, resulting in large ionomer agglomerates and inhomogeneous ionomer coverage over the catalyst nanoparticle, with consequent poor fuel cell performance. In this work, this ionomer/catalyst interface has been engineered, utilizing the electrostatic attraction between positively charged catalyst and negatively charged ionomer particles in a catalyst ink and preserved in a solid catalyst layer. As a result, this interface leads to previously unachieved proton exchange membrane fuel cell performance in terms of both catalyst utilization (75% vs. 45%) and peak/rated power density (i.e., 1.430/0.930 W cm -2 , H 2 /air, cathode Pt loading: 0.1 mgPt cm -2 ) for pure Pt catalysts, even better than those of Pt alloy catalysts. This work demonstrates the formation of an interface in the liquid phase (using ultra-small-angle X-ray scattering in combination with cryo-TEM, isothermal–titration–calorimetry) and the preservation of the interface in the solid catalyst layer (using TEM) and estimates the effective coverage and thickness of the ionomer film (using limiting current density, RDE and fuel cell performance).
Current studies concerning liquid hot water pretreatment (LHWP) usually focus on cellulose saccharification or hemicellulose conversion, while the appropriate extraction and utilization of LHWP-induced lignin have not been addressed. To valorize whole biomass, here, in this study, a series of LHWP-based combinatorial pretreatments are proposed using advanced solvent systems. The first LHWP stage removed 73.74% of xylan at the optimized pretreatment severity (~4.0), at the same time preserving almost all the cellulose and lignin. As a result, 9.04 g L –1 xylo-oligosaccharides (XOSs) were obtained in the prehydrolyzate, representing 63.31% of the degraded xylan. The LHWP also caused the migration and partial degradation of the lignin which benefits the delignification in the second stage of pretreatment utilizing NaOH, deep eutectic solvent (DES) and 1,4-butanediol (BDO) under relatively mild conditions. The proposed combinatorial pretreatment significantly enhanced glucan conversion. The physiochemical structural properties of the untreated and pretreated substrates were investigated with XRD, FTIR, GPC, SEM, and Simons’ staining to understand the mechanisms of different combinatorial pretreatments for overcoming biomass recalcitrance and facilitating integrated biomass valorization. Finally, the physical and chemical properties of the regenerated lignins were analyzed. The results revealed that lignins from LHWP–NaOH pretreatment preserved most of the native β-O-4 structure (37.1%). Thus it could be used as an ideal method for the catalytic production of aromatic monomers. On the other hand, LHWP–DES pretreatment generated lignins with low molecular weight and high phenolic OH content, which is promising for synthesizing resins and antioxidants. In conclusion, the proposed combinatorial pretreatment established a reliable sequential pretreatment methodology for maximizing the output of bamboo biomass and may fit into different biorefinery configurations for various value-added products.
A 2D phospholipid crystal (dark) grows within a fluid vesicle membrane (light), starting as a small flower shape. While the area of the crystal grows progressively, the flower shape is preserved, a result of tension pre-conditioning.