Formation of a two-dimensional helical square tube ice in hydrophobic nanoslit using the TIP5P water model.

In extreme and nanoconfinement conditions, the tetrahedral arrangement of water molecules is challenged, resulting in a rich and new phase behavior unseen in bulk phases. The unique phase behavior of water confined in hydrophobic nanoslits has been previously observed, such as the formation of a variety of two-dimensional (2D) ices below the freezing temperature. The primary identified 2D ice phase, termed square tube ice (STI), represents a unique arrangement of water molecules in 2D ice, which can be viewed as an array of 1D ice nanotubes stacked in the direction parallel to the confinement plane. In this study, we report the molecular dynamics (MD) simulations evidence of a novel 2D ice phase, namely, helical square tube ice (H-STI). H-STI is characterized by the stacking of helical ice nanotubes in the direction parallel to the confinement plane. Its structural specificity is evident in the presence of helical square ice nanotubes, a configuration unseen in both STI and single-walled ice nanotubes. A detailed analysis of the hydrogen bonding strength showed that H-STI is a 2D ice phase diverging from the Bernal-Fowler-Pauling ice rules by forming only two strong hydrogen bonds between adjacent molecules along its helical ice chain. This arrangement of strong hydrogen bonds along ice nanotube and weak bonds between the ice nanotube shows a similarity to quasi-one-dimensional van der Waals materials. Ab initio molecular dynamics simulations (over a 30 ps) were employed to further verify H-STI's stability at 1 GPa and temperature up to 200 K.

Topological wetting states of microdroplets on closed-loop structured surfaces: Breakdown of the Gibbs equation at the microscale.

Microdroplets are a class of soft matter that has been extensively employed for chemical, biochemical, and industrial applications. However, fabricating microdroplets with largely controllable contact-area shape and apparent contact angle, a key prerequisite for their applications, is still a challenge. Here, by engineering a type of surface with homocentric closed-loop microwalls/microchannels, we can achieve facile size, shape, and contact-angle tunability of microdroplets on the textured surfaces by design. More importantly, this class of surface topologies (with universal genus value = 1) allows us to reveal that the conventional Gibbs equation (widely used for assessing the edge effect on the apparent contact angle of macrodroplets) seems no longer applicable for water microdroplets or nanodroplets (evidenced by independent molecular dynamics simulations). Notably, for the flat surface with the intrinsic contact angle ~0°, we find that the critical contact angle on the microtextured counterparts (at edge angle 90°) can be as large as >130°, rather than 90° according to the Gibbs equation. Experiments show that the breakdown of the Gibbs equation occurs for microdroplets of different types of liquids including alcohol and hydrocarbon oils. Overall, the microtextured surface design and topological wetting states not only offer opportunities for diverse applications of microdroplets such as controllable chemical reactions and low-cost circuit fabrications but also provide testbeds for advancing the fundamental surface science of wetting beyond the Gibbs equation.

Electrochemical Lithium Deposition on LixTi5O12.

Lithium metal batteries (LMBs) have been regarded as one of the most promising next-generation high-energy-density storage devices. However, uncontrolled lithium dendrite growth leads to low Coulombic efficiencies and severe safety issues, hindering the commercialization of LMBs. Reducing the diffusion barrier of lithium is beneficial for uniform lithium deposition. Herein, a composite is constructed with Li4Ti5O12 as the skeleton of metallic lithium (Li@LixTi5O12) because Li4Ti5O12 is a "zero-strain" material and exhibits a low lithium diffusion barrier. It was found that the symmetric cells of Li@LixTi5O12 can stably cycle for over 400 h at 1 mA cm-2 in the carbonate electrolyte, significantly exceeding the usual lifespan (∼170 h) of the symmetric cell using a lithium metal electrode. In a full cell with Li@LixTi5O12 as the anode, the cathode LiFePO4 delivers a capacity retention of 78.2% after 550 cycles at 3.6C rate and an N/P ratio = 8.0. This study provides new insights for designing a practical lithium anode.

Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging.

Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.

Identification of functional white matter networks in BOLD fMRI.

White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is growing evidence that these signals are indicative of brain activity. Understanding how these white matter signals capture function can provide insight into brain physiology. Moreover, functional signals could potentially be used as early markers for neurological changes, such as in Alzheimer's Disease. To investigate white matter brain networks, we leveraged the OASIS-3 dataset to extract white matter signals from resting state BOLD-FMRI data on 711 subjects. The imaging was longitudinal with a total of 2,026 images. Hierarchical clustering was performed to investigate clusters of voxel-level correlations on the timeseries data. The stability of clusters was measured with the average Dice coefficients on two different cross fold validations. The first validated the stability between scans, and the second validated the stability between subject populations. Functional clusters at hierarchical levels 4, 9, 13, 18, and 24 had local maximum stability, suggesting better clustered white matter. In comparison with JHU-DTI-SS Type-I Atlas defined regions, clusters at lower hierarchical levels identified well defined anatomical lobes. At higher hierarchical levels, functional clusters mapped motor and memory functional regions, identifying 50.00%, 20.00%, 27.27%, and 35.14% of the frontal, occipital, parietal, and temporal lobe regions respectively.

Assisted Self-Assembly of Nanoporous Ices via Carbon Nanomaterial Templates.

Self-assembly is a widely used synthetic method in nanoscience to assemble well-organized structures. Self-assembly processes usually occur in a water solvent environment. However, the self-assembly of water molecules is rarely studied. Herein, we show a strategy to fabricate porous ice via carbon nanomaterial-assisted self-assembly. Diverse frameworks of nanoporous ice are formed by using orthorhombic and tetragonal arrays of carbon nanotubes or carbon-atom chains as templates. In contrast to many bulk ices discovered in nature, nanoporous ices are shown to be stable only under negative pressure. Hence, nanoporous ices cannot be produced through the direct nucleation of water at negative pressure. The template-assisted self-assembly method is shown to be the most effective method to fabricate nanoporous ice in quantity. Several key factors for the self-assembly of nanoporous ices are identified, including proper gap spacings in the carbon nanomaterial template and suitable interactions between water and the carbon nanomaterials.

The missing third dimension-Functional correlations of BOLD signals incorporating white matter.

Correlations between magnetic resonance imaging (MRI) blood oxygenation level-dependent (BOLD) signals from pairs of gray matter areas are used to infer their functional connectivity, but they are unable to describe how white matter is engaged in brain networks. Recently, evidence that BOLD signals in white matter are robustly detectable and are modulated by neural activities has accumulated. We introduce a three-way correlation between BOLD signals from pairs of gray matter volumes (nodes) and white matter bundles (edges) to define the communication connectivity through each white matter bundle. Using MRI images from publicly available databases, we show, for example, that the three-way connectivity is influenced by age. By integrating functional MRI signals from white matter as a third component in network analyses, more comprehensive descriptions of brain function may be obtained.

Evidence of Spontaneous Formation of Two-Dimensional Amorphous Clathrates on Superhydrophilic Surfaces.

Clathrate hydrates reserved in the seabed are often dispersed in the pores of coarse-grained sediments; hence, their formation typically occurs under nanoconfinement. Herein, we show the first molecular dynamics (MD) simulation evidence of the spontaneous formation of two-dimensional (2D) clathrate hydrates on crystal surfaces without conventional nanoconfinement. The kinetic process of 2D clathrate formation is illustrated via simulated single-molecule deposition. 2D amorphous patterns are observed on various superhydrophilic face-centered cubic surfaces. Notably, the formation of 2D amorphous clathrate can occur over a wide range of temperatures, even at room temperature. The strong water-surface interaction, the characteristic properties of guest-gas molecules, and the underlying surface structure dictate the formation of 2D amorphous clathrates. Semiquantitative phase diagrams of 2D clathrates are constructed where representative patterns of 2D clathrates for characteristic gas molecules on prototypical Pd(111) and Pt(111) surfaces are confirmed by independent MD simulations. A tunable pattern of 2D amorphous clathrates is demonstrated by changing the lattice strain of the underlying substrate. Moreover, ab initio MD simulations confirm the stability of 2D amorphous clathrate. The underlining physical mechanism for 2D clathrate formation on superhydrophilic surfaces is elucidated, which offers deeper insight into the crucial role of water-surface interaction.

Synchronously sexual maturity in hermaphrodite fish as revealed by transcriptome analysis in Plectropomus leopardus.

Leopard coral grouper (Plectropomus leopardus) is a type of hermaphrodite fish, but the mechanisms of gonadal development and gametogenesis remain unclear. In the present study, we performed histological observation and transcriptomic analysis during the process of sexual differentiation in P. leopardus. According to the histological results, sexual differentiation was completed at 15 months old, developed synchronously in male and female individuals at 2 years old, and matured synchronously at 3 years old. Comparative transcriptomic analyses showed that the gonadal had differentiated by 15 months old, with enrichment of pathways associated with cell proliferation, transcriptional metabolism, and germline stem cell differentiation. Furthermore, cilium movement and fatty acid anabolism, which are associated with spermatogenesis and oocyte growth, were significantly enriched at 3 years old. In addition, key genes associated with male and female sex differentiation, such as amh, dmrt1, dmrt2a, zp4, sox3, gdf9, and gsdf, were identified by weighted gene co-expression network analysis (WGCNA). Finally, the localization and expression of the key genes amh and sox3 were observed in different cell types within the testes and ovaries, reflecting the development of the testes and ovaries, respectively. All the evidence indicates that P. leopardus is a hermaphrodite and synchronously sexually mature fish. Our study complements the gonadal development patterns of hermaphroditic fish by providing new insights into the molecular mechanisms underlying sexual differentiation and sex change in hermaphroditic groupers.

High, Multiple, and Nonvolatile Polarizations in Organic-Inorganic Hybrid [(CH3)3(CH2CH2Cl)N]2InCl5·H2O for Memcapacitor.

Dielectrics with high, nonvolatile, and multiple polarizations are required for fabricating memcapacitors that enable high parallelism and low energy consumption in artificial neuromorphic computing systems as artificial synapses. Conventional ferroelectric materials based on displacive and order-disorder types generally have difficulty meeting these requirements due to their low polarization values (∼150 µC/cm2) and persistent electrical hysteresis loops. In this study, we report a novel organic-inorganic hybrid (CETM)2InCl5·H2O (CETM = (CH3)3(CH2CH2Cl)N) exhibiting an intriguing polarization vs electric field (charge vs voltage) "hysteresis loop" and a record-high nonvolatile polarization over 30 000 µC/cm2 at room temperature. The polarization is highly dependent on the period and amplitude of the ac voltage, showing multiple nonvolatile states. Electrochemical impedance spectroscopy, time-dependent current behavior, disparate resistor response in the dehydrated derivative (CETM)2InCl5, and the negative temperature dependence of ionic conductance support that the memcapacitor behavior of (CETM)2InCl5·H2O stems from irreversible long-range migration of protons. First-principles calculations further confirm this and clarify the microscale mechanism of anisotropic polarization response. Our findings may open up a new avenue for developing memcapacitors by harnessing the benefits of ion migration in organic-inorganic hybrids.

Seasonal variations of functional connectivity of human brains.

Seasonal variations have long been observed in various aspects of human life. While there is an abundance of research that has characterized seasonality effects in, for example, cognition, mood, and behavior, including studies of underlying biophysical mechanisms, direct measurements of seasonal variations of brain functional activities have not gained wide attention. We have quantified seasonal effects on functional connectivity as derived from MRI scans. A cohort of healthy human subjects was divided into four groups based on the seasons of their scanning dates as documented in the image database of the Human Connectome Project. Sinusoidal functions were used as regressors to determine whether there were significant seasonal variations in measures of brain activities. We began with the analysis of seasonal variations of the fractional amplitudes of low frequency fluctuations of regional functional signals, followed by the seasonal variations of functional connectivity in both global- and network-level. Furthermore, relevant environmental factors, including average temperature and daylength, were found to be significantly associated with brain functional activities, which may explain how the observed seasonal fluctuations arise. Finally, topological properties of the brain functional network also showed significant variations across seasons. All the observations accumulated revealed seasonality effects of human brain activities in a resting-state, which may have important practical implications for neuroimaging research.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan.

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

Whole-brain, gray, and white matter time-locked functional signal changes with simple tasks and model-free analysis.

Recent studies have revealed the production of time-locked blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to tasks, challenging the existence of sparse and localized brain functions and highlighting the pervasiveness of potential false negative fMRI findings. "Whole-brain" actually refers to gray matter, the only tissue traditionally studied with fMRI. However, several reports have demonstrated reliable detection of BOLD signals in white matter, which have previously been largely ignored. Using simple tasks and analyses, we demonstrate BOLD signal changes across the whole brain, in both white and gray matters, in similar manner to previous reports of whole brain studies. We investigated whether white matter displays time-locked BOLD signals across multiple structural pathways in response to a stimulus in a similar manner to the cortex. We find that both white and gray matter show time-locked activations across the whole brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that, just like all gray matter, essentially all white matter in the brain shows time-locked BOLD signal changes in response to multiple stimuli, challenging the idea of sparse functional localization and the prevailing wisdom of treating white matter BOLD signals as artifacts to be removed.

Automatic Preprocessing Pipeline for White Matter Functional Analyses of Large-Scale Databases.

Recently, increasing evidence suggests that fMRI signals in white matter (WM), conventionally ignored as nuisance, are robustly detectable using appropriate processing methods and are related to neural activity, while changes in WM with aging and degeneration are also well documented. These findings suggest variations in patterns of BOLD signals in WM should be investigated. However, existing fMRI analysis tools, which were designed for processing gray matter signals, are not well suited for large-scale processing of WM signals in fMRI data. We developed an automatic pipeline for high-performance preprocessing of fMRI images with emphasis on quantifying changes in BOLD signals in WM in an aging population. At the image processing level, the pipeline integrated existing software modules with fine parameter tunings and modifications to better extract weaker WM signals. The preprocessing results primarily included whole-brain time-courses, functional connectivity, maps and tissue masks in a common space. At the job execution level, this pipeline exploited a local XNAT to store datasets and results, while using DAX tool to automatic distribute batch jobs that run on high-performance computing clusters. Through the pipeline, 5,034 fMRI/T1 scans were preprocessed. The intraclass correlation coefficient (ICC) of test-retest experiment based on the preprocessed data is 0.52 - 0.86 (N=1000), indicating a high reliability of our pipeline, comparable to previously reported ICC in gray matter experiments. This preprocessing pipeline highly facilitates our future analyses on WM functional alterations in aging and may be of benefit to a larger community interested in WM fMRI studies.

Functional alterations in bipartite network of white and grey matters during aging.

The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22-96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

Changes in white matter functional networks across late adulthood.

Introduction: The aging brain is characterized by decreases in not only neuronal density but also reductions in myelinated white matter (WM) fibers that provide the essential foundation for communication between cortical regions. Age-related degeneration of WM has been previously characterized by histopathology as well as T2 FLAIR and diffusion MRI. Recent studies have consistently shown that BOLD (blood oxygenation level dependent) effects in WM are robustly detectable, are modulated by neural activities, and thus represent a complementary window into the functional organization of the brain. However, there have been no previous systematic studies of whether or how WM BOLD signals vary with normal aging. We therefore performed a comprehensive quantification of WM BOLD signals across scales to evaluate their potential as indicators of functional changes that arise with aging. Methods: By using spatial independent component analysis (ICA) of BOLD signals acquired in a resting state, WM voxels were grouped into spatially distinct functional units. The functional connectivities (FCs) within and among those units were measured and their relationships with aging were assessed. On a larger spatial scale, a graph was reconstructed based on the pair-wise connectivities among units, modeling the WM as a complex network and producing a set of graph-theoretical metrics. Results: The spectral powers that reflect the intensities of BOLD signals were found to be significantly affected by aging across more than half of the WM units. The functional connectivities (FCs) within and among those units were found to decrease significantly with aging. We observed a widespread reduction of graph-theoretical metrics, suggesting a decrease in the ability to exchange information between remote WM regions with aging. Discussion: Our findings converge to support the notion that WM BOLD signals in specific regions, and their interactions with other regions, have the potential to serve as imaging markers of aging.

Polymer Competitive Solvation Reduced Propylene Carbonate Cointercalation in a Graphitic Anode.

Polymer electrolytes have been studied as an alternative to organic liquid electrolytes but suffer from low ionic conductivity. Propylene carbonate (PC) proves to be an interesting solvent but is incompatible with graphitic anodes due to its cointercalation effect. In this work, adding poly(ethylene oxide) (PEO) into a PC-based electrolyte can alter the solvation structure as well as transform the solution into a polymer electrolyte with high ionic conductivity. By spectroscopic techniques and calculations, we demonstrate that PEO can compete with PC in solvating the Li+ ions, reducing the Li+-PC bond strength, and making it easier for PC to be desolvated. Due to the unique solvation structure, PC-cointercalation-induced graphite exfoliation is inhibited, and the reduction stability of the electrolyte is improved. This work will extend the applications of the PC-based electrolytes, deepen the understandings of the solvation structure, and spur designs of advanced electrolytes.

Whole-brain, gray and white matter time-locked functional signal changes with simple tasks and model-free analysis.

Recent studies have revealed the production of time-locked blood oxygenation-level dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to a task, challenging the idea of sparse and localized brain functions, and highlighting the pervasiveness of potential false negative fMRI findings. In these studies, 'whole-brain' refers to gray matter regions only, which is the only tissue traditionally studied with fMRI. However, recent reports have also demonstrated reliable detection and analyses of BOLD signals in white matter which have been largely ignored in previous reports. Here, using model-free analysis and simple tasks, we investigate BOLD signal changes in both white and gray matters. We aimed to evaluate whether white matter also displays time-locked BOLD signals across all structural pathways in response to a stimulus. We find that both white and gray matter show time-locked activations across the whole-brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing very different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that the whole brain, including both white and gray matter, show time-locked activation to multiple stimuli, not only challenging the idea of sparse functional localization, but also the prevailing wisdom of treating white matter BOLD signals as artefacts to be removed.

Mg Substitution Induced TM/Vacancy Disordering and Enhanced Structural Stability in Layered Oxide Cathode Materials.

Anionic redox is an effective way to increase the capacity of the cathode materials. Na2Mn3O7 [Na4/7[Mn6/7□1/7]O2, □ for the transition metal (TM) vacancies] with native and ordered TM vacancies can conduct a reversible oxygen redox and be a promising high-energy cathode material for sodium-ion batteries (SIBs). However, its phase transition at low potentials (∼1.5 V vs Na+/Na) induces potential decays. Herein, magnesium (Mg) is doped on the TM vacancies to form a disordered Mn/Mg/□ arrangement in the TM layer. The Mg substitution suppresses the oxygen oxidation at ∼4.2 V by reducing the number of the Na-O-□ configurations. Meanwhile, this flexible disordering structure inhibits the generation of the dissolvable Mn2+ ions and mitigates the phase transition at ∼1.6 V. Therefore, the Mg doping improves the structural stability and its cycling performance in 1.5-4.5 V. The disordering arrangement endows Na0.49Mn0.86Mg0.06□0.08O2 with a higher Na+ diffusivity and improved rate performance. Our study reveals that oxygen oxidation is highly dependent on the ordering/disordering arrangements in the cathode materials. This work provides insights into the balance of anionic and cationic redox for enhancing the structural stability and electrochemical performance in the SIBs.

Efficient exploration of complex free energy landscapes by stepwise multi-subphase space metadynamics.

We present an efficient method based on an extension of metadynamics for exploring complex free energy landscapes (FELs). The method employs two-step metadynamics simulations. In the first step, rapid metadynamics simulations using broad and tall Gaussians are performed to identify a free energy pathway (FEP) connecting the two states of interest. The FEP is then divided into a series of independent subphase spaces that comprise selected discrete images of the system. Using appropriate collective variables (CVs) chosen according to the FEP, the accurate FEL of each subphase space is separately calculated in subsequent divide-and-conquer metadynamics simulations with narrow and low Gaussians. Finally, all FELs calculated in each subphase space are merged to obtain the full FEL. We show that the method greatly improves the performance of the metadynamics approach. In particular, we are able to efficiently model chemical systems with complex FELs, such as chemical reactions at the air/water interface. We demonstrate the performance of this method on two model reactions: the hydrolysis of formaldehyde in the gas phase and at the air/water interface.