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Join open writing teams to collaborate on commentaries for a special collection describing approaches that embody synthesis, cross-disciplinary integration, and open science across geosciences.
Marine cold-air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. To more deeply understand BL and mixed-phase cloud properties during CAO conditions, the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy's first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (~1,000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular with high (~3–5 km) and cold (–30 to –50 °C) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ~1,000 g m –2 ) associated with strong updrafts and enhanced turbulence. We use a high-resolution mesoscale model to explore how well four turbulence closure methods represent open cellular clouds. After applying a radar simulator to model outputs for direct evaluation, cloud top properties agree well with AMF1 observations (within ~10%), but radar reflectivity and LWP agreement is more variable. Results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties. All simulations produce enhanced precipitation rates that are well-correlated with a cloud transition. Finally, the eddy-diffusivity/mass-flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. Furthermore, we recommend the use of a non-local turbulence closure approach to better capture turbulent processes in intense CAOs.
TrkH is a bacterial ion channel implicated in K + uptake and pH regulation. TrkH assembles with its regulatory protein, TrkA, which closes the channel when bound to ADP and opens it when bound to ATP. However, it is unknown how nucleotides control the gating of TrkH through TrkA. Here we report the structures of the TrkH-TrkA complex in the presence of ADP or ATP. TrkA forms a tetrameric ring when bound to ADP and constrains TrkH to a closed conformation. The TrkA ring splits into two TrkA dimers in the presence of ATP and releases the constraints on TrkH, resulting in an open channel conformation. Functional studies show that both the tetramer-to-dimer conversion of TrkA and the loss of constraints on TrkH are required for channel gating. In addition, deletion of TrkA in Escherichia coli depolarizes the cell, suggesting that the TrkH-TrkA complex couples changes in intracellular nucleotides to membrane potential.
Abstract Due to the non-flammable nature of water-based electrolytes, aqueous lithium-ion batteries are resistant to catching fire. However, they are not immune to the risk of explosion, since the sealing structure adopted by current batteries limits the dissipation of heat and pressure within the cells. Here, we report a safe aqueous lithium-ion battery with an open configuration using water-in-salt electrolytes and aluminum oxide coated anodes. The design can inhibit the self-discharge by substantially suppressing the oxygen reduction reaction on lithiated anodes and enable good cycle performance over 1000 times. Our study may open a pathway towards safer lithium-ion battery designs.
Single particle cryo-EM often yields multiple protein conformations within a single dataset, but experimentally deducing the temporal relationship of these conformers within a conformational trajectory is not trivial. Here, we use thermal titration methods and cryo-EM in an attempt to obtain temporal resolution of the conformational trajectory of the vanilloid receptor TRPV1 with resiniferatoxin (RTx) bound. Based on our cryo-EM ensemble analysis, RTx binding to TRPV1 appears to induce intracellular gate opening first, followed by selectivity filter dilation, then pore loop rearrangement to reach the final open state. This apparent conformational wave likely arises from the concerted, stepwise, additive structural changes of TRPV1 over many subdomains. Greater understanding of the RTx-mediated long-range allostery of TRPV1 could help further the therapeutic potential of RTx, which is a promising drug candidate for pain relief associated with advanced cancer or knee arthritis.
Abstract Electrodes made of commercially pure titanium (CP-Ti) and a CoCrMo alloy are immersed at an open circuit in a phosphate buffer saline electrolyte at room temperature for different durations prior to electrochemical analyses. Open circuit potential measurements, electrochemical impedance spectroscopy measurements, and cyclic potentiodynamic polarization (CPP) scans are used to assess the impact of the immersion time on derived property values. Stable passivation layers formed on both materials during immersion. The corrosion potentials determined from the anodic legs of CPP scans become more cathodic, and the corrosion currents decrease to lower values after longer immersion times. Measured currents indicate the layers formed on CP-Ti stabilize during forward anodic scans and persist to the vertex potential, whereas passivation breakdown occurs during anodic scans with CoCrMo with active corrosion at voltages up to the vertex potential. The characteristics of the return cathodic legs of CPP scans represent the surface conditions at the vertex potential: characteristic corrosion property values derived from the test responses represent passive surfaces on CP-Ti and leached surfaces on CoCrMo rather than intrinsic properties of those materials.
The majority of scenarios in the IPCC database are generated by integrated assessment models (IAMs) and come from model intercomparison projects. However, the way in which the current model intercomparison projects are organized is not open to all IAM teams worldwide. Here we propose a transparent and inclusive platform that is open to anyone with an IAM regarding protocols development, scenario submissions and results evaluation. We discuss the challenges of this approach, particularly human resources and financial support. Here, we identify diversity in the level of model capability and quality of model output as possibly critical issues. Despite such challenges, the IAM community and its scientific activities can improve and benefit from the proposed platform, ultimately contributing to better climate policymaking.
Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences.
Understanding the response of faults to the injection of high-pressure fluids is important for several subsurface applications, for example, geologic carbon sequestration or energy storage. Lab-based experiments suggest that fluid injection can activate fault slip and that this slip can lead to increased fluid transmission along low-permeability faults. Here we present in situ observations from a cross-borehole fluid-injection experiment in a low-permeability shale-bearing fault, which show fault displacement occurring before fluid-pressure build-up. Comparing these observations with numerical models with differing permeability evolution histories, we find that the observed variation in fluid pressure is best explained by a change in permeability only after the fault fails and slips beyond the pressurized area. Once fluid migration occurs along the fault as a result of slip-induced permeability increase, the fault experiences further opening due to a decrease in the effective normal stress. We then suggest that decoupling of fault slip and opening, leading to a rapid increase in fluid pressurization following the initial fault slip, could be an efficient driver for fluid migration in low-permeability faults.
This paper introduces CORE, a widely used scholarly service, which provides access to the world’s largest collection of open access research publications, acquired from a global network of repositories and journals. CORE was created with the goal of enabling text and data mining of scientific literature and thus supporting scientific discovery, but it is now used in a wide range of use cases within higher education, industry, not-for-profit organisations, as well as by the general public. Through the provided services, CORE powers innovative use cases, such as plagiarism detection, in market-leading third-party organisations. CORE has played a pivotal role in the global move towards universal open access by making scientific knowledge more easily and freely discoverable. In this paper, we describe CORE’s continuously growing dataset and the motivation behind its creation, present the challenges associated with systematically gathering research papers from thousands of data providers worldwide at scale, and introduce the novel solutions that were developed to overcome these challenges. The paper then provides an in-depth discussion of the services and tools built on top of the aggregated data and finally examines several use cases that have leveraged the CORE dataset and services.
Protein structure prediction is an important problem in bioinformatics and has been studied for decades. However, there are still few open-source comprehensive protein structure prediction packages publicly available in the field. In this paper, we present our latest open-source protein tertiary structure prediction system—MULTICOM2, an integration of template-based modeling (TBM) and template-free modeling (FM) methods. The template-based modeling uses sequence alignment tools with deep multiple sequence alignments to search for structural templates, which are much faster and more accurate than MULTICOM1. The template-free (ab initio or de novo) modeling uses the inter-residue distances predicted by DeepDist to reconstruct tertiary structure models without using any known structure as template. In the blind CASP14 experiment, the average TM-score of the models predicted by our server predictor based on the MULTICOM2 system is 0.720 for 58 TBM (regular) domains and 0.514 for 38 FM and FM/TBM (hard) domains, indicating that MULTICOM2 is capable of predicting good tertiary structures across the board. It can predict the correct fold for 76 CASP14 domains (95% regular domains and 55% hard domains) if only one prediction is made for a domain. The success rate is increased to 3% for both regular and hard domains if five predictions are made per domain. Moreover, the prediction accuracy of the pure template-free structure modeling method on both TBM and FM targets is very close to the combination of template-based and template-free modeling methods. This demonstrates that the distance-based template-free modeling method powered by deep learning can largely replace the traditional template-based modeling method even on TBM targets that TBM methods used to dominate and therefore provides a uniform structure modeling approach to any protein. Finally, on the 38 CASP14 FM and FM/TBM hard domains, MULTICOM2 server predictors (MULTICOM-HYBRID, MULTICOM-DEEP, MULTICOM-DIST) were ranked among the top 20 automated server predictors in the CASP14 experiment. After combining multiple predictors from the same research group as one entry, MULTICOM-HYBRID was ranked no. 5. The source code of MULTICOM2 is freely available at https://github.com/multicom-toolbox/multicom/tree/multicom_v2.0 .
We report a scalable, low-temperature TiO x electron transport layer (ETL) produced directly on top of perovskite in an inverted architecture device by an open-air chemical vapor deposition (OA-CVD) process. The OA-CVD pyrolysis of a titanium ethoxide precursor forms a fully inorganic, conformal, and compact TiO x film. The resultant film is mechanically robust and exhibits a fracture toughness 30-fold higher than commonly used fullerene-based ETL films. The TiO x is an effective barrier layer against environmental degradation—unencapsulated devices with the TiO x ETL retain 60% of their initial efficiency after 1000 hours in ambient aging conditions—compared to devices with a fullerene ETL which were inoperable after 144 hours. Inverted architecture devices with an optimized TiO x ETL thickness of 70 nm exhibited high open-circuit voltages of 1.08 V. We comment on the photocatalytic properties of TiO x and the influence of an amorphous film on maximum power point stability.
The use of solid polymer electrolytes has previously proven to be an effective approach to address the lithium polysulfide dissolution and high electrode interfacial impedance of Li–S batteries via an in situ polymerization process. However, the conventional in situ synthesis employs a cationic ring-opening polymerization (CROP) of 1,3-dioxolane (DOL) catalyzed by a strong Lewis acid. New polymerization chemistry that is more compatible with Li–S chemistry needs to be developed to mitigate the disadvantages associated with the CROP process. Herein we report a new approach to in situ polymerize a set of new episulfide monomers in solution with LiTFSI salt via an anionic ring-opening polymerization (AROP). This new polymer system takes advantage of the inherent cell chemistry present in the Li–S cell through the nucleophilic lithium sulfides which are generated during the initial discharge cycle and act as the initiator for the polymerization. Additionally, their presence was shown to initiate the monomer solvents through AROP with no need for additional catalysts, rather than the more commonly utilized cationic systems which require an external Lewis acid catalyst. This work offers an important pathway toward in situ polymer electrolytes for Li–S batteries and offers a new avenue of exploration for polymer electrolyte synthesis.
The Lagrange-based Grassmann interpolation (G-Int) method has been extended for open-shell systems using restricted open-shell methods in building spin contamination-free potential energy surfaces.
The formation of exposed active sites that have high activity and stability for oxygen evolution reaction (OER) catalysis is a significant opportunity for improving water electrolysers. Low-index facets surface Ru can achieve both high activity and stability for OER. Here, we present a new catalyst design where low-index faceted Ru branches are grown off the corners of Pt nanocubes, forming open Ru branched nanoparticles. This open branched structure, exposing low-index facets on its length-tunable branch, enables a high electrochemically active surface area (ECSA), achieving high activity and stability for OER. This design strategy and synthetic control provide a principle for achieving high-performance OER nanocatalysts.
Solid state nanopores have emerged as model systems for understanding transport properties on the nanoscale. They serve as templates for both preparing mimics of biological channels and designing biological sensors. Unlike their biological inspirations, the majority of nanopores prepared thus far, however, have been structurally static devices such that the pore opening diameter is fixed. If we could prepare nanopores whose opening diameter fluctuated in time with controlled amplitude at known locations in the pore, we could create ionic memristors as well as achieve new transport modes. Here we present ∼10 nm diameter single nanopores drilled through a 10 nm thick gold layer positioned on top of a 30 nm thick silicon nitride film. Two types of devices were prepared; one containing single stranded DNA and the other containing hairpin DNA attached to the discrete layer of gold using thiol chemistry. When an external electric field was applied across a nanopore with single stranded DNA, the nanoconfined DNA molecules exhibited steric and electrical constraints that led to memristor-like behavior in the current–voltage curves. The degree of hysteresis was controlled by salt concentration, magnitude of voltage and pore diameter. In contrast, nanopores containing DNA hairpins conducted similar currents in forward and reverse bias in agreement with the rigidity of the hairpin molecule. The experiments are explained by Brownian dynamics simulations that reveal voltage and salt concentration induced changes in DNA extension. The degree of DNA extension was also found to be dependent on the location of the molecules along the pore axis. The nanopores presented here provide the first steps towards preparation of non-equilibrium nanopore systems.
We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. In this study, we use lowlevel detector information from the simulated CMS Open Data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves a ROC-AUC score of 0.975±0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier ROC-AUC score increases to 0.9824±0.0013, serving as the first performance benchmark for these CMS Open Data samples.
Most x-ray sources are inherently polychromatic. Polychromatic (“pink”) x-rays provide an efficient way to conduct diffraction experiments as many more photons can be used and large regions of reciprocal space can be probed without sample rotation during exposure—ideal conditions for time-resolved applications. Analysis of such data is complicated, however, causing most x-ray facilities to discard >99% of x-ray photons to obtain monochromatic data. Key challenges in analyzing polychromatic diffraction data include lattice searching, indexing and wavelength assignment, correction of measured intensities for wavelength-dependent effects, and deconvolution of harmonics. We recently described an algorithm, Careless, that can perform harmonic deconvolution and correct measured intensities for variation in wavelength when presented with integrated diffraction intensities and assigned wavelengths. Here, we present Laue-DIALS, an open-source software pipeline that indexes and integrates polychromatic diffraction data. Laue-DIALS is based on the dxtbx toolbox, which supports the DIALS software commonly used to process monochromatic data. As such, Laue-DIALS provides many of the same advantages: an open-source, modular, and extensible architecture, providing a robust basis for future development. We present benchmark results showing that Laue-DIALS, together with Careless, provides a suitable approach to the analysis of polychromatic diffraction data, including for time-resolved applications.