Stabilisation of the [SiH6]2- Anion within a Supramolecular Assembly

The hypercoordinate [SiH6]2- anion is not stable in solution. Here, we report the room temperature, solution stable molecular [SiH6]2- complex, [{KCa(NON)(OEt2)}2][SiH6] (NON=4,5-bis(2,6-diisopropylanilido)-2,7-di-tert-butyl-9,9-dimethyl-xanthene)), where the [SiH6]2- anion is stabilised within a supramolecular assembly that mimics the solid-state environment of the anion in the lattice of K2SiH6. Solution-state reactivity of the complex towards carbon monoxide, benzaldehyde, azobenzene and acetonitrile is reported, yielding a range of reduction and C-C coupled products.

Classification of battery compounds using structure-free Mendeleev encodings

Machine learning is a valuable tool that can accelerate the discovery and design of materials occupying combinatorial chemical spaces. However, the prerequisite need for vast amounts of training data can be prohibitive when significant resources are needed to characterize or simulate candidate structures. Recent results have shown that structure-free encoding of complex materials, based entirely on chemical compositions, can overcome this impediment and perform well in unsupervised learning tasks. In this study, we extend this exploration to supervised classification, and show how structure-free encoding can accurately predict classes of material compounds for battery applications without time consuming measurement of bonding networks, lattices or densities. SCIENTIFIC CONTRIBUTION: The comprehensive evaluation of structure-free encodings of complex materials in classification tasks, including binary and multi-class separation, inclusive of three classifiers based on different logic function, is measured four metrics and learning curves. The encoding is applied to two data sets from computational and experimental sources, and the outcomes visualised using 5 approaches to confirms the suitability and superiority of Mendeleev encoding. These methods are general and accessible using source software, to provide simple, intuitive and interpretable materials informatics outcomes to accelerate materials design.

Predicting valence tautomerism in diverse cobalt-dioxolene complexes: elucidation of the role of ligands and solvent

The ability of molecular switches to reversibly interconvert between different forms promises potential applications at the scale of single molecules up to bulk materials. One type of molecular switch comprises cobalt-dioxolene compounds that exhibit thermally-induced valence tautomerism (VT) interconversions between low spin Co(iii)-catecholate (LS-CoIII-cat) and high spin Co(ii)-semiquinonate (HS-CoII-sq) forms. Two families of these compounds have been investigated for decades but have generally been considered separately: neutral [Co(diox)(sq)(N2L)] and cationic [Co(diox)(N4L)]+ complexes (diox = generic dioxolene, N2L/N4L = bidentate/tetradentate N-donor ancillary ligand). Computational identification of promising new candidate compounds prior to experimental exploration is beneficial for environmental and cost considerations but requires a thorough understanding of the underlying thermochemical parameters that influence the switching. Herein, we report a robust approach for the analysis of both cobalt-dioxolene families, which involved a quantitative density functional theory-based study benchmarked with reliable quasi-experimental references. The best-performing M06L-D4/def2-TZVPP level of theory has subsequently been verified by the synthesis and experimental investigation of three new complexes, two of which exhibit thermally-induced VT, while the third remains in the LS-CoIII-cat form across all temperatures, in agreement with prediction. Valence tautomerism in solution is markedly solvent-dependent, but the origin of this has not been definitively established. We have extended our computational approach to elucidate the correlation of VT transition temperature with solvent stabilisation energy and change in dipole moment. This new understanding may inform the development of VT compounds for applications in soft materials including films, gels, and polymers.

Rare SH2B3 coding variants in lupus patients impair B cell tolerance and predispose to autoimmunity

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with a clear genetic component. While most SLE patients carry rare gene variants in lupus risk genes, little is known about their contribution to disease pathogenesis. Amongst them, SH2B3-a negative regulator of cytokine and growth factor receptor signaling-harbors rare coding variants in over 5% of SLE patients. Here, we show that unlike the variant found exclusively in healthy controls, SH2B3 rare variants found in lupus patients are predominantly hypomorphic alleles, failing to suppress IFNGR signaling via JAK2-STAT1. The generation of two mouse lines carrying patients' variants revealed that SH2B3 is important in limiting the number of immature and transitional B cells. Furthermore, hypomorphic SH2B3 was shown to impair the negative selection of immature/transitional self-reactive B cells and accelerate autoimmunity in sensitized mice, at least in part due to increased IL-4R signaling and BAFF-R expression. This work identifies a previously unappreciated role for SH2B3 in human B cell tolerance and lupus risk.

Engineering Spin-Orbit Interactions in Silicon Qubits at the Atomic-Scale

Spin-orbit interactions arise whenever the bulk inversion symmetry and/or structural inversion symmetry of a crystal is broken providing a bridge between a qubit's spin and orbital degree of freedom. While strong interactions can facilitate fast qubit operations by all-electrical control, they also provide a mechanism to couple charge noise thereby limiting qubit lifetimes. Previously believed to be negligible in bulk silicon, recent silicon nano-electronic devices have shown larger than bulk spin-orbit coupling strengths from Dresselhaus and Rashba couplings. Here, it is shown that with precision placement of phosphorus atoms in silicon along the [110] direction (without inversion symmetry) or [111] direction (with inversion symmetry), a wide range of Dresselhaus and Rashba coupling strength can be achieved from zero to 1113 × 10-13eV-cm. It is shown that with precision placement of phosphorus atoms, the local symmetry (C2v, D2d, and D3d) can be changed to engineer spin-orbit interactions. Since spin-orbit interactions affect both qubit operation and lifetimes, understanding their impact is essential for quantum processor design.

Atomic Scale Structure of Self-Assembled Lipidated Peptide Nanomaterials

β-Peptides have great potential as novel biomaterials and therapeutic agents, due to their unique ability to self-assemble into low dimensional nanostructures, and their resistance to enzymatic degradation in vivo. However, the self-assembly mechanisms of β-peptides, which possess increased flexibility due to the extra backbone methylene groups present within the constituent β-amino acids, are not well understood due to inherent difficulties of observing their bottom-up growth pathway experimentally. A computational approach is presented for the bottom-up modelling of the self-assembled lipidated β3-peptides, from monomers, to oligomers, to supramolecular low-dimensional nanostructures, in all-atom detail. The approach is applied to elucidate the self-assembly mechanisms of recently discovered, distinct structural morphologies of low dimensional nanomaterials, assembled from lipidated β3-peptide monomers. The resultant structures of the nanobelts and the twisted fibrils are stable throughout subsequent unrestrained all-atom molecular dynamics simulations, and these assemblies display good agreement with the structural features obtained from X-ray fiber diffraction and atomic force microscopy data. This is the first reported, fully-atomistic model of a lipidated β3-peptide-based nanomaterial, and the computational approach developed here, in combination with experimental fiber diffraction analysis and atomic force microscopy, will be useful in elucidating the atomic scale structure of self-assembled peptide-based and other supramolecular nanomaterials.

A binding site for phosphoinositides described by multiscale simulations explains their modulation of voltage-gated sodium channels

Voltage-gated sodium channels (Naᵥ) are membrane proteins which open to facilitate the inward flux of sodium ions into excitable cells. In response to stimuli, Naᵥ channels transition from the resting, closed state to an open, conductive state, before rapidly inactivating. Dysregulation of this functional cycle due to mutations causes diseases including epilepsy, pain conditions, and cardiac disorders, making Naᵥ channels a significant pharmacological target. Phosphoinositides are important lipid cofactors for ion channel function. The phosphoinositide PI(4,5)P2 decreases Naᵥ1.4 activity by increasing the difficulty of channel opening, accelerating fast inactivation and slowing recovery from fast inactivation. Using multiscale molecular dynamics simulations, we show that PI(4,5)P2 binds stably to inactivated Naᵥ at a conserved site within the DIV S4-S5 linker, which couples the voltage-sensing domain (VSD) to the pore. As the Naᵥ C-terminal domain is proposed to also bind here during recovery from inactivation, we hypothesize that PI(4,5)P2 prolongs inactivation by competitively binding to this site. In atomistic simulations, PI(4,5)P2 reduces the mobility of both the DIV S4-S5 linker and the DIII-IV linker, responsible for fast inactivation, slowing the conformational changes required for the channel to recover to the resting state. We further show that in a resting state Naᵥ model, phosphoinositides bind to VSD gating charges, which may anchor them and impede VSD activation. Our results provide a mechanism by which phosphoinositides alter the voltage dependence of activation and the rate of recovery from inactivation, an important step for the development of novel therapies to treat Naᵥ-related diseases.

Long-term Musculoskeletal Consequences of Chemotherapy in Pediatric Mice

Thanks to recent progress in cancer research, most children treated for cancer survive into adulthood. Nevertheless, the long-term consequences of anticancer agents are understudied, especially in the pediatric population. We and others have shown that routinely administered chemotherapeutics drive musculoskeletal alterations, which contribute to increased treatment-related toxicity and long-term morbidity. Yet, the nature and scope of these enduring musculoskeletal defects following anticancer treatments and whether they can potentially impact growth and quality of life in young individuals remain to be elucidated. Here, we aimed at investigating the persistent musculoskeletal consequences of chemotherapy in young (pediatric) mice. Four-week-old male mice were administered a combination of 5-FU, leucovorin, irinotecan (a.k.a., Folfiri) or the vehicle for up to 5 wk. At time of sacrifice, skeletal muscle, bones, and other tissues were collected, processed, and stored for further analyses. In another set of experiments, chemotherapy-treated mice were monitored for up to 4 wk after cessation of treatment. Overall, the growth rate was significantly slower in the chemotherapy-treated animals, resulting in diminished lean and fat mass, as well as significantly smaller skeletal muscles. Interestingly, 4 wk after cessation of the treatment, the animals exposed to chemotherapy showed persistent musculoskeletal defects, including muscle innervation deficits and abnormal mitochondrial homeostasis. Altogether, our data support that anticancer treatments may lead to long-lasting musculoskeletal complications in actively growing pediatric mice and support the need for further studies to determine the mechanisms responsible for these complications, so that new therapies to prevent or diminish chemotherapy-related toxicities can be identified.

Hybrid Organic-Inorganic Additive for Robust Al Anode in Alkaline Aluminum-Air Battery

Aluminum-air batteries (AABs), known for their high energy density, environmental friendliness, and cost-effectiveness, show immense promise in the realm of energy conversion applications. Nonetheless, their commercialization has encountered inherent challenges of Al anode corrosion and material degradation. In this study, economical hybrid electrolyte additives to inhibit the Al corrosion are developed, safeguarding the integrity of the Al anode. Due to the synergistic interplay between the organic compound dithiothreitol, and inorganic compounds zinc chloride, a robust zinc film is formed on the Al surface This Zn film plays a pivotal role in quelling parasitic hydrogen evolution reactions that typically can plague the Al electrode. Consequently, the as-prepared hybrid additive culminates in a remarkable enhancement to AABs, delivering exceptional discharge capacity of 1793.37 mAh g-1 , high energy density of 2047 Wh kg-1 , and excellent battery longevity (over 20 h in on/off cycling tests). This study, therefore, introduces a novel approach in utilizing hybrid electrolyte additives to effectively counteract corrosion-related challenges and boost the stability and performance of AABs.

Noncovalently bound excited-state dimers: a perspective on current time-dependent density functional theory approaches applied to aromatic excimer models

Excimers are supramolecular systems whose binding strength is influenced by many factors that are ongoing challenges for computational methods, such as charge transfer, exciton coupling, and London dispersion interactions. Treating the various intricacies of excimer binding at an adequate level is expected to be particularly challenging for time-dependent Density Functional Theory (TD-DFT) methods. In addition to well-known limitations for some TD-DFT methods in the description of charge transfer or exciton coupling, the inherent London dispersion problem from ground-state DFT translates to TD-DFT. While techniques to appropriately treat dispersion in DFT are well-developed for electronic ground states, these dispersion corrections remain largely untested for excited states. Herein, we aim to shed light on current TD-DFT methods, including some of the newest developments. The binding of four model excimers is studied across nine density functionals with and without the application of additive dispersion corrections against a wave function reference of SCS-CC2/CBS(3,4) quality, which approximates select CCSDR(3)/CBS data adequately. To our knowledge, this is the first study that presents single-reference wave function dissociation curves at the complete basis set level for the assessed model systems. It is also the first time range-separated double-hybrid density functionals are applied to excimers. In fact, those functionals turn out to be the most promising for the description of excimer binding followed by global double hybrids. Range-separated and global hybrids-particularly with large fractions of Fock exchange-are outperformed by double hybrids and yield worse dissociation energies and inter-molecular equilibrium distances. The deviation between each assessed functional and reference increases with system size, most likely due to missing dispersion interactions. Additive dispersion corrections of the DFT-D3(BJ) and DFT-D4 types reduce the average errors for TD-DFT methods but do so inconsistently and therefore do not offer a black-box solution in their ground-state parametrised form. The lack of appropriate description of dispersion effects for TD-DFT methods is likely hindering the practical application of the herein identified more efficient methods. Dispersion corrections parametrised for excited states appear to be an important next step to improve the applicability of TD-DFT methods and we hope that our work assists with the future development of such corrections.

Defect-Promoted Ni-Based Layer Double Hydroxides with Enhanced Deprotonation Capability for Efficient Biomass Electrooxidation

Ni-based hydroxides are promising electrocatalysts for biomass oxidation reactions, supplanting the oxygen evolution reaction (OER) due to lower overpotentials while producing value-added chemicals. The identification and subsequent engineering of their catalytically active sites are essential to facilitate these anodic reactions. Herein, the proportional relationship between catalysts' deprotonation propensity and Faradic efficiency of 5-hydroxymethylfurfural (5-HMF)-to-2,5 furandicarboxylic acid (FDCA, FEFDCA ) is revealed by thorough density functional theory (DFT) simulations and atomic-scale characterizations, including in situ synchrotron diffraction and spectroscopy methods. The deprotonation capability of ultrathin layer-double hydroxides (UT-LDHs) is regulated by tuning the covalency of metal (M)-oxygen (O) motifs through defect site engineering and selection of M3+ co-chemistry. NiMn UT-LDHs show an ultrahigh FEFDCA of 99% at 1.37 V versus reversible hydrogen electrode (RHE) and retain a high FEFDCA of 92.7% in the OER-operating window at 1.52 V, about 2× that of NiFe UT-LDHs (49.5%) at 1.52 V. Ni-O and Mn-O motifs function as dual active sites for HMF electrooxidation, where the continuous deprotonation of Mn-OH sites plays a dominant role in achieving high selectivity while suppressing OER at high potentials. The results showcase a universal concept of modulating competing anodic reactions in aqueous biomass electrolysis by electronically engineering the deprotonation behavior of metal hydroxides, anticipated to be translatable across various biomass substrates.

Predicting molecular vibronic spectra using time-domain analog quantum simulation

Spectroscopy is one of the most accurate probes of the molecular world. However, predicting molecular spectra accurately is computationally difficult because of the presence of entanglement between electronic and nuclear degrees of freedom. Although quantum computers promise to reduce this computational cost, existing quantum approaches rely on combining signals from individual eigenstates, an approach whose cost grows exponentially with molecule size. Here, we introduce a method for scalable analog quantum simulation of molecular spectroscopy: by performing simulations in the time domain, the number of required measurements depends on the desired spectral range and resolution, not molecular size. Our approach can treat more complicated molecular models than previous ones, requires fewer approximations, and can be extended to open quantum systems with minimal overhead. We present a direct mapping of the underlying problem of time-domain simulation of molecular spectra to the degrees of freedom and control fields available in a trapped-ion quantum simulator. We experimentally demonstrate our algorithm on a trapped-ion device, exploiting both intrinsic electronic and motional degrees of freedom, showing excellent quantitative agreement for a single-mode vibronic photoelectron spectrum of SO2.

A Systematic Exploration of B-F Bond Dissociation Enthalpies of Fluoroborane-Type Molecules at the CCSD(T)/CBS Level

Fluoroborane-type molecules (R1R2B-F) are of interest in synthetic chemistry, but to date, apart from a handful of small species (such as H2BF, HBF2, and BF3), little is known concerning the effect of substituents in governing the strength of the B-F bonds of such species toward homolytic dissociation in the gas phase. In this study, we have calculated the bond dissociation enthalpies (BDEs) of thirty unique B-F bonds at the CCSD(T)/CBS level using the high-level W1w thermochemical protocol. The B-F bonds in all species considered are very strong, ranging from 545.9 kJ mol-1 in (H2B)2B-F to 729.2 kJ mol-1 HBF2. Nevertheless, these BDEs still vary over a wide range of 183.3 kJ mol-1. The structural properties that affect the BDEs are examined in detail, and the homolytic BDEs are rationalized based on molecule stabilization enthalpies and radical stabilization enthalpies. Since polar B-F bonds may represent a challenging test case for density functional theory (DFT) methods, we proceed to examine the performance of a wide range of DFT methods across the rungs of Jacob's Ladder for their ability to compute B-F BDEs. We find that only a handful of DFT methods can reproduce the CCSD(T)/CBS BDEs with mean absolute deviations (MADs) below the threshold of chemical accuracy (i.e., with average deviations below 4.2 kJ mol-1). The only functionals capable of achieving this feat were (MADs given in parentheses): ωB97M-V (4.0), BMK (3.5), DSD-BLYP (3.8), and DSD-PBEB95 (1.8 kJ mol-1).

The functional evolution of architecturally different plant geranyl diphosphate synthases from geranylgeranyl diphosphate synthase

Terpenoids constitute the largest class of plant primary and secondary metabolites with a broad range of biological and ecological functions. They are synthesized from isopentenyl diphosphate and dimethylallyl diphosphate, which in plastids are condensed by geranylgeranyl diphosphate synthases (GGPPSs) to produce GGPP (C20) for diterpene biosynthesis and by geranyl diphosphate synthases (GPPSs) to form GPP (C10) for monoterpene production. Depending on the plant species, unlike homomeric GGPPSs, GPPSs exist as homo- and heteromers, the latter of which contain catalytically inactive GGPPS-homologous small subunits (SSUs) that can interact with GGPPSs. By combining phylogenetic analysis with functional characterization of GGPPS homologs from a wide range of photosynthetic organisms, we investigated how different GPPS architectures have evolved within the GGPPS protein family. Our results reveal that GGPPS gene family expansion and functional divergence began early in nonvascular plants, and that independent parallel evolutionary processes gave rise to homomeric and heteromeric GPPSs. By site-directed mutagenesis and molecular dynamics simulations, we also discovered that Leu-Val/Val-Ala pairs of amino acid residues were pivotal in the functional divergence of homomeric GPPSs and GGPPSs. Overall, our study elucidated an evolutionary path for the formation of GPPSs with different architectures from GGPPSs and uncovered the molecular mechanisms involved in this differentiation.

Engineering Flexible Metal-Phenolic Networks with Guest Responsiveness via Intermolecular Interactions

Flexible metal-organic materials are of growing interest owing to their ability to undergo reversible structural transformations under external stimuli. Here, we report flexible metal-phenolic networks (MPNs) featuring stimuli-responsive behavior to diverse solute guests. The competitive coordination of metal ions to phenolic ligands of multiple coordination sites and solute guests (e.g., glucose) primarily determines the responsive behavior of the MPNs, as revealed experimentally and computationally. Glucose molecules can be embedded into the dynamic MPNs upon mixing, leading to the reconfiguration of the metal-organic networks and thus changes in their physicochemical properties for targeting applications. This study expands the library of stimuli-responsive flexible metal-organic materials and the understanding of intermolecular interactions between metal-organic materials and solute guests, which is essential for the rational design of responsive materials for various applications.

Environmental variation of the low-mass IMF

We use a series of magnetohydrodynamic simulations including both radiative and protostellar outflow feedback to study environmental variation of the initial mass function (IMF). The simulations represent a carefully-controlled experiment whereby we keep all dimensionless parameters of the flow constant except for those related to feedback. We show that radiation feedback suppresses the formation of lower mass objects more effectively as the surface density increases, but this only partially compensates for the decreasing Jeans mass in denser environments. Similarly, we find that protostellar outflows are more effective at suppressing the formation of massive stars in higher surface density environments. The combined effect of these two trends is towards an IMF with a lower characteristic mass and a narrower overall mass range in high surface density environments. We discuss the implications for these findings for the interpretation of observational evidence of IMF variation in early type galaxies.

Even a little delocalization produces large kinetic enhancements of charge-separation efficiency in organic photovoltaics

In organic photovoltaics, charges can separate efficiently even if their Coulomb attraction is an order of magnitude greater than the available thermal energy. Delocalization has been suggested to explain this fact, because it could increase the initial separation of charges in the charge-transfer (CT) state, reducing their attraction. However, understanding the mechanism requires a kinetic model of delocalized charge separation, which has proven difficult because it involves tracking the correlated quantum-mechanical motion of the electron and the hole in large simulation boxes required for disordered materials. Here, we report the first three-dimensional simulations of charge-separation dynamics in the presence of disorder, delocalization, and polaron formation, finding that even slight delocalization, across less than two molecules, can substantially enhance the charge-separation efficiency, even starting with thermalized CT states. Delocalization does not enhance efficiency by reducing the Coulomb attraction; instead, the enhancement is a kinetic effect produced by the increased overlap of electronic states.

Noncovalently bound excited-state dimers: a perspective on current time-dependent density functional theory approaches applied to aromatic excimer models

Excimers are supramolecular systems whose binding strength is influenced by many factors that are ongoing challenges for computational methods, such as charge transfer, exciton coupling, and London dispersion interactions. Treating the various intricacies of excimer binding at an adequate level is expected to be particularly challenging for Time-Dependent Density Functional Theory (TD-DFT) methods. In addition to well-known limitations for some TD-DFT methods in the description of charge transfer or exciton coupling, the inherent London dispersion problem from ground-state DFT translates to TD-DFT. While techniques to appropriately treat dispersion in DFT are well-developed for electronic ground states, these dispersion corrections remain largely untested for excited states. Herein, we aim to shed light on current TD-DFT methods, including some of the newest developments. The binding of four model excimers is studied across nine density functionals with and without the application of additive dispersion corrections against a wave function reference of SCS-CC2/CBS(3,4) quality, which approximates select CCSDR(3)/CBS data adequately. To our knowledge, this is the first study that presents single-reference wave function dissociation curves at the complete basis set level for the assessed model systems. It is also the first time range-separated double-hybrid density functionals are applied to excimers. In fact, those functionals turn out to be the most promising for the description of excimer binding followed by global double hybrids. Range-separated and global hybrids-particularly with large fractions of Fock exchange-are outperformed by double hybrids and yield worse dissociation energies and inter-molecular equilibrium distances. The deviation between each assessed functional and reference increases with system size, most likely due to missing dispersion interactions. Additive dispersion corrections of the DFT-D3(BJ) and DFT-D4 types reduce the average errors for TD-DFT methods but do so inconsistently and therefore do not offer a black-box solution in their ground-state parametrised form. The lack of appropriate description of dispersion effects for TD-DFT methods is likely hindering the practical application of the herein identified more efficient methods. Dispersion corrections parametrised for excited states appear to be an important next step to improve the applicability of TD-DFT methods and we hope that our work assists with the future development of such corrections.

The extent of ionization in simulations of radio-loud AGNs impacting kpc gas discs

We use the results of relativistic hydrodynamic simulations of jet-interstellar medium (ISM) interactions in a galaxy with a radio-loud AGN to quantify the extent of ionization in the central few kpcs of the gaseous galactic disc. We perform post-process radiative transfer of AGN radiation through the simulated gaseous jet-perturbed disc to estimate the extent of photo-ionization by the AGN with an incident luminosity of 10⁴⁵ erg s^-1. We also map the gas that is collisionally ionized due to shocks driven by the jet. The analysis was carried out for simulations with similar jet power (10⁴⁵ erg s^-1) but different jet orientations with respect to the gas disc. We find that the shocks from the jets can ionize a significant fraction (up to 33 [Formula: see text]) of dense gas ([Formula: see text]) in the disc, and that the jets clear out the central regions of gas for AGN radiation to penetrate to larger distances in the disc. Jets inclined towards the disc plane couple more strongly with the ISM and ionize a larger fraction of gas in the disc as compared to the vertical jet. However, similar to previous studies, we find that the AGN radiation is quickly absorbed by the outer layers of dense clouds in the disc, and is not able to substantially ionize the disc on a global scale. Thus, compared to jet-ISM interactions, we expect that photo-ionization by the AGN radiation only weakly affects the star-formation activity in the central regions of the galactic disc (≲ 1 kpc), although the jet-induced shocks can spread farther out.

Theoretical understanding of electronic and mechanical properties of 1T' transition metal dichalcogenide crystals

Transition metal dichalcogenides (TMDs) with a 1T' layer structure have recently received intense interest due to their outstanding physical and chemical properties. While the physicochemical behaviors of 1T' TMD monolayers have been widely investigated, the corresponding properties of layered 1T' TMD crystals have rarely been studied. As TMD monolayers do not have interlayer interactions, their physicochemical properties will differ from those of layered TMD materials. In this study, the electronic and mechanical characteristics of a range of 1T' TMDs are systematically examined by means of density functional theory (DFT) calculations. Our results reveal that the properties of 1T' TMDs are mainly affected by their anions. The disulfides are stiffer and more rigid, diselenides are more brittle. In addition, the 1T' polytype is softer than 2H TMDs. Comparison with the properties of the monolayers shows that the interlayer van der Waals forces can slightly weaken the TM-X covalent bonding strength, which can further influence the mechanical properties. These insights revealed by our theoretical studies may boost more applications of 1T' TMD materials.

Density functionals with asymptotic-potential corrections are required for the simulation of spectroscopic properties of materials

Five effects of correction of the asymptotic potential error in density functionals are identified that significantly improve calculated properties of molecular excited states involving charge-transfer character. Newly developed materials-science computational methods are used to demonstrate how these effects manifest in materials spectroscopy. Connection is made considering chlorophyll-a as a paradigm for molecular spectroscopy, 22 iconic materials as paradigms for 3D materials spectroscopy, and the VN - defect in hexagonal boron nitride as an example of the spectroscopy of defects in 2D materials pertaining to nanophotonics. Defects can equally be thought of as being "molecular" and "materials" in nature and hence bridge the relms of molecular and materials spectroscopies. It is concluded that the density functional HSE06, currently considered as the standard for accurate calculations of materials spectroscopy, should be replaced, in most instances, by the computationally similar but asymptotically corrected CAM-B3LYP functional, with some specific functionals for materials-use only providing further improvements.

A scaling relation for the molecular cloud lifetime in Milky Way-like galaxies

We study the time evolution of molecular clouds across three Milky Way-like isolated disc galaxy simulations at a temporal resolution of 1 Myr and at a range of spatial resolutions spanning two orders of magnitude in spatial scale from ∼10 pc up to ∼1 kpc. The cloud evolution networks generated at the highest spatial resolution contain a cumulative total of ∼80 000 separate molecular clouds in different galactic-dynamical environments. We find that clouds undergo mergers at a rate proportional to the crossing time between their centroids, but that their physical properties are largely insensitive to these interactions. Below the gas-disc scale height, the cloud lifetime τlife obeys a scaling relation of the form τlife∝ℓ-0.3 with the cloud size ℓ, consistent with over-densities that collapse, form stars, and are dispersed by stellar feedback. Above the disc scale height, these self-gravitating regions are no longer resolved, so the scaling relation flattens to a constant value of ∼13 Myr, consistent with the turbulent crossing time of the gas disc, as observed in nearby disc galaxies.

The electronic origins of the "rare earth" texture effect in magnesium alloys

Although magnesium alloys are lightweight, recyclable and relatively cheap, they suffer from poor ductility. This can be improved by the addition of rare earth (RE) elements, and this is now a well-established criterion for wrought alloy design. It is notable that this behavior is largely restricted to the lanthanides, but no hypothesis is yet available to explain why other elements do not have the same effect. To answer this question, ab initio simulations of crystallographically complex boundaries have been undertaken to examine the electronic origin of the RE effect. While the electronic structure provided strong bonding between the RE elements and their Mg surroundings, local disruption in atomic arrangement at the grain boundaries was found to modify this effect. This work shows quantifiable changes in electronic structure of solutes resulting from grain boundary crystallography, and is suggested to be a contributing factor to the RE texture effect.

A numerical study of fish adaption behaviors in complex environments with a deep reinforcement learning and immersed boundary-lattice Boltzmann method

Fish adaption behaviors in complex environments are of great importance in improving the performance of underwater vehicles. This work presents a numerical study of the adaption behaviors of self-propelled fish in complex environments by developing a numerical framework of deep learning and immersed boundary-lattice Boltzmann method (IB-LBM). In this framework, the fish swimming in a viscous incompressible flow is simulated with an IB-LBM which is validated by conducting two benchmark problems including a uniform flow over a stationary cylinder and a self-propelled anguilliform swimming in a quiescent flow. Furthermore, a deep recurrent Q-network (DRQN) is incorporated with the IB-LBM to train the fish model to adapt its motion to optimally achieve a specific task, such as prey capture, rheotaxis and Kármán gaiting. Compared to existing learning models for fish, this work incorporates the fish position, velocity and acceleration into the state space in the DRQN; and it considers the amplitude and frequency action spaces as well as the historical effects. This framework makes use of the high computational efficiency of the IB-LBM which is of crucial importance for the effective coupling with learning algorithms. Applications of the proposed numerical framework in point-to-point swimming in quiescent flow and position holding both in a uniform stream and a Kármán vortex street demonstrate the strategies used to adapt to different situations.

3D NLTE spectral line formation of lithium in late-type stars

Accurately known stellar lithium abundances may be used to shed light on a variety of astrophysical phenomena such as big bang nucleosynthesis, radial migration, ages of stars and stellar clusters, and planet engulfment events. We present a grid of synthetic lithium spectra that are computed in non-local thermodynamic equilibrium (NLTE) across the stagger grid of three-dimensional (3D) hydrodynamic stellar atmosphere models. This grid covers three Li lines at 610.4, 670.8, and 812.6 nm for stellar parameters representative of FGK-type dwarfs and giants, spanning T eff = 4000-7000 K, log g = 1.5-5.0, [Formula: see text]-0.5, and A(Li) = -0.5-4.0. We find that our abundance corrections are up to 0.15 dex more negative than in previous work, due to a previously overlooked NLTE effect of blocking of UV lithium lines by background opacities, which has important implications for a wide range of science cases. We derive a new 3D NLTE solar abundance of A(Li) = 0.96 ± 0.05, which is 0.09 dex lower than the commonly used value. We make our grids of synthetic spectra and abundance corrections publicly available through the breidablik package. This package includes methods for accurately interpolating our grid to arbitrary stellar parameters through methods based on Kriging (Gaussian process regression) for line profiles, and multilayer perceptrons (a class of fully connected feedforward neural networks) for NLTE corrections and 3D NLTE abundances from equivalent widths, achieving interpolation errors of the order of 0.01 dex.

The nuclear piston activates mechanosensitive ion channels to generate cell migration paths in confining microenvironments

Cell migration in confining microenvironments is limited by the ability of the stiff nucleus to deform through pores when migration paths are preexisting and elastic, but how cells generate these paths remains unclear. Here, we reveal a mechanism by which the nucleus mechanically generates migration paths for mesenchymal stem cells (MSCs) in confining microenvironments. MSCs migrate robustly in nanoporous, confining hydrogels that are viscoelastic and plastic but not in hydrogels that are more elastic. To migrate, MSCs first extend thin protrusions that widen over time because of a nuclear piston, thus opening up a migration path in a confining matrix. Theoretical modeling and experiments indicate that the nucleus pushing into the protrusion activates mechanosensitive ion channels, leading to an influx of ions that increases osmotic pressure, which outcompetes hydrostatic pressure to drive protrusion expansion. Thus, instead of limiting migration, the nucleus powers migration by generating migration paths.

MetaBCC-LR: metagenomics binning by coverage and composition for long reads

MOTIVATION

Metagenomics studies have provided key insights into the composition and structure of microbial communities found in different environments. Among the techniques used to analyse metagenomic data, binning is considered a crucial step to characterize the different species of micro-organisms present. The use of short-read data in most binning tools poses several limitations, such as insufficient species-specific signal, and the emergence of long-read sequencing technologies offers us opportunities to surmount them. However, most current metagenomic binning tools have been developed for short reads. The few tools that can process long reads either do not scale with increasing input size or require a database with reference genomes that are often unknown. In this article, we present MetaBCC-LR, a scalable reference-free binning method which clusters long reads directly based on their k-mer coverage histograms and oligonucleotide composition.

RESULTS

We evaluate MetaBCC-LR on multiple simulated and real metagenomic long-read datasets with varying coverages and error rates. Our experiments demonstrate that MetaBCC-LR substantially outperforms state-of-the-art reference-free binning tools, achieving ∼13% improvement in F1-score and ∼30% improvement in ARI compared to the best previous tools. Moreover, we show that using MetaBCC-LR before long-read assembly helps to enhance the assembly quality while significantly reducing the assembly cost in terms of time and memory usage. The efficiency and accuracy of MetaBCC-LR pave the way for more effective long-read-based metagenomics analyses to support a wide range of applications.

AVAILABILITY AND IMPLEMENTATION

The source code is freely available at: https://github.com/anuradhawick/MetaBCC-LR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Warm Circumpolar Deep Water transport toward Antarctica driven by local dense water export in canyons

Poleward transport of warm Circumpolar Deep Water (CDW) has been linked to melting of Antarctic ice shelves. However, even the steady-state spatial distribution and mechanisms of CDW transport remain poorly understood. Using a global, eddying ocean model, we explore the relationship between the cross-slope transports of CDW and descending Dense Shelf Water (DSW). We find large spatial variability in CDW heat and volume transport around Antarctica, with substantially enhanced flow where DSW descends in canyons. The CDW and DSW transports are highly spatially correlated within ~20 km and temporally correlated on subdaily time scales. Focusing on the Ross Sea, we show that the relationship is driven by pulses of overflowing DSW lowering sea surface height, leading to net onshore CDW transport. The majority of simulated onshore CDW transport is concentrated in cold-water regions, rather than warm-water regions, with potential implications for ice-ocean interactions and global sea level rise.

Unravelling the effects of size, volume fraction and shape of nanoparticle additives on crystallization of nanocomposite polymers

We conducted large scale molecular dynamics simulations to understand the effects of size, shape and volume fraction of additive nanoparticles on the crystallization of nanocomposite polymers. We used spherical and cubic gold nanoparticles of various sizes ranging from 2 to 8 nm to create hexacontane (C₆₀H₁₂₂)-gold nanocomposites at various volume fractions of 0.84-19.27%. We show that, regardless of the shape, decreasing the size of particles at the same volume fraction results in decreased final crystallinity. Similarly, for the same particle size, increasing the volume fraction causes a decrease in the crystal growth rate and final crystallinity. We demonstrate that this is a confinement induced phenomenon, and the free interparticle space captures the combined effects of particle size and volume fraction. If this free space is smaller than the extended length of the molecule or the characteristic size of the crystal lamella thickness of the polymer, significant slow-down in crystallinity will emerge. In this confinement limit, the interparticle free space controls the crystal growth rate and final crystallinity. We have developed the equations that predict the critical volume fraction (φ _cr) for a given size or critical size (D _cr) for a given volume fraction. For φ > φ _cr or D < D _cr, one would expect confinement induced retardation of crystallization. We also show that cubic particles result in a higher growth rate and crystallinity in comparison to spherical particles, purely due to their shape. Furthermore, cubic particles due to flat surfaces lead to distinct two-tier crystallisation kinetics manifested by enhanced crystallization at the early stage of crystallization, followed by slow crystallization due to confinement effects. This two-tier crystallization is more distinct at higher volume fractions. For spherical particles, however, this two-tier crystallization is almost absent and molecular crystallization near the particle is frustrated by the curved shape of the nanoparticle.

Volume Averaging for Urban Canopies

When canopy flows are horizontally averaged to obtain mean profiles, the averaging operation can be defined either as an intrinsic average, normalized by the variable fluid volume, or as a superficial average, normalized by the total volume including solid canopy elements. Properties of spatial averages have been explored extensively in the context of flow through plant canopies, albeit with the assumption that the solid volume fraction is negligible. Without this simplification, properties relevant for non-linear terms apply to intrinsic averages while properties of gradients apply to superficial averages. To avoid inconsistencies and inaccuracies the impact of a non-negligible solid volume fraction should be considered carefully when interpreting mean profiles, when deriving mathematical relations for averaged quantities, and when introducing modelling assumptions for such terms. On this basis, we review the definitions and properties of the method of volume averaging, as developed in the more general context of flow through porous media, and discuss its application to urban canopy flows. We illustrate the properties of intrinsic and superficial averages and their effect on mean profiles with example data from a simulation of flow over constant-height cubes.

Validated Alzheimer's Disease Risk Index (ANU-ADRI) is associated with smaller volumes in the default mode network in the early 60s

Strong evidence is available suggesting that effective reduction of exposure to demonstrated modifiable risk factors in mid-life or before could significantly decrease the incidence of Alzheimer's disease (AD) and delay its onset. A key ingredient to achieving this goal is the reliable identification of individuals at risk well before they develop clinical symptoms. The aim of this study was to provide further neuroimaging evidence of the effectiveness of a validated tool, the ANU Alzheimer's Disease Risk Index, for the assessment of future risk of cognitive decline. Participants were 461 (60-64 years, 48% female) community-living individuals free of dementia at baseline. Associations between risk estimates obtained with the ANU-ADRI, total and regional brain volumes including in the default mode network (DMN) measured at the same assessment and diagnosis of MCI/dementia over a 12-year follow-up were tested in a large sample of community-living individuals free of dementia at baseline. Higher risk estimates on the ANU-ADRI were associated with lower cortical gray matter and particularly in the DMN. Importantly, difference in participants with high and low risk scores explained 7-9% of the observed difference in gray matter volume. In this sample, every one additional risk point on the ANU-ADRI was associated with an 8% increased risk of developing MCI/dementia over a 12-year follow-up and this association was partly mediated by a sub-region of the DMN. Risk of cognitive decline assessed with a validated instrument is associated with gray matter volume, particularly in the DMN, a region known to be implicated in the pathological process of the disease.