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Gibbs equation (widely used for assessing the edge effect on the apparent contact angle of macrodroplets) seems no longer applicable for water microdroplets or nanodroplets (evidenced by independent molecular dynamics simulations).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.

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.

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.

Anomalous water transport in narrow-diameter carbon nanotubes.

Carbon nanotubes (CNTs) mimicking the structure of aquaporins support fast water transport, making them strong candidates for building next-generation high-performance membranes for water treatment. The diffusion and transport behavior of water through CNTs or nanoporous graphene can be fundamentally different from those of bulk water through a macroscopic tube. To date, the nanotube-length-dependent physical transport behavior of water is still largely unexplored. Herein, on the basis of molecular dynamics simulations, we show that the flow rate of water through 0.83-nm-diameter (6,6) and 0.96-nm-diameter (7,7) CNTs exhibits anomalous transport behavior, whereby the flow rate increases markedly first and then either slowly decreases or changes slightly as the CNT length l increases. The critical range of l for the flow-rate transition is 0.37 to 0.5 nm. This anomalous water transport behavior is attributed to the l-dependent mechanical stability of the transient hydrogen-bonding chain that connects water molecules inside and outside the CNTs and bypasses the CNT orifice. The results unveil a microscopic mechanism governing water transport through subnanometer tubes, which has important implications for nanofluidic manipulation.

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.

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.

Air-Stable Na3.5C6O6 as a Sodium Compensation Additive in Cathode of Na-Ion Batteries.

Sodium-ion battery (SIB) is a candidate for the stationary energy storage systems because of the low cost and high abundance of sodium. However, the energy density and lifespan of SIBs suffer severely from the irreversible consumption of the Na-ions for the formation of the solid electrolyte interphase (SEI) layer and other side reactions on the electrodes. Here, Na3.5C6O6 is proposed as an air-stable high-efficiency sacrificial additive in the cathode to compensate for the lost sodium. It is characteristic of low desodiation (oxidation) potential (3.4-3.6 V vs. Na+/Na) and high irreversible desodiation capacity (theoretically 378 mAh g-1). The feasibility of using Na3.5C6O6 as a sodium compensation additive is verified with the improved electrochemical performances of a Na2/3Ni1/3Mn1/3Ti1/3O2ǀǀhard carbon cells and cells using other cathode materials. In addition, the structure of Na3.5C6O6 and its desodiation path are also clarified on the basis of comprehensive physical characterizations and the density functional theory (DFT) calculations. This additive decomposes completely to supply abundant Na ions during the initial charge without leaving any electrochemically inert species in the cathode. Its decomposition product C6O6 enters the carbonate electrolyte without bringing any detectable negative effects. These findings open a new avenue for elevating the energy density and/or prolonging the lifetime of the high-energy-density secondary batteries.

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.

Power spectra reveal distinct BOLD resting-state time courses in white matter.

Accurate characterization of the time courses of blood-oxygen-level-dependent (BOLD) signal changes is crucial for the analysis and interpretation of functional MRI data. While several studies have shown that white matter (WM) exhibits distinct BOLD responses evoked by tasks, there have been no comprehensive investigations into the time courses of spontaneous signal fluctuations in WM. We measured the power spectra of the resting-state time courses in a set of regions within WM identified as showing synchronous signals using independent components analysis. In each component, a clear separation between voxels into two categories was evident, based on their power spectra: one group exhibited a single peak, and the other had an additional peak at a higher frequency. Their groupings are location specific, and their distributions reflect unique neurovascular and anatomical configurations. Importantly, the two categories of voxels differed in their engagement in functional integration, revealed by differences in the number of interregional connections based on the two categories separately. Taken together, these findings suggest WM signals are heterogeneous in nature and depend on local structural-vascular-functional associations.

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.

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.

Dynamic variations of resting-state BOLD signal spectra in white matter.

Recent studies have demonstrated that the mathematical model used for analyzing and interpreting fMRI data in gray matter (GM) is inappropriate for detecting or describing blood-oxygenation-level-dependent (BOLD) signals in white matter (WM). In particular the hemodynamic response function (HRF) which serves as the regressor in general linear models is different in WM compared to GM. We recently reported measurements of the frequency contents of resting-state signal time courses in WM that showed distinct power spectra which depended on local structural-vascular-functional associations. In addition, multiple studies of GM have revealed how functional connectivity between regions, as measured by the correlation between BOLD time series, varies dynamically over time. We therefore investigated whether and how BOLD signals from WM in a resting state varied over time. We measured voxel-wise spectrograms, which reflect the time-varying spectral patterns of WM time courses. The results suggest that the spectral patterns are non-stationary but could be categorized into five modes that recurred over time. These modes showed distinct spatial distributions of their occurrences and durations, and the distributions were highly consistent across individuals. In addition, one of the modes exhibited a strong coupling of its occurrence between GM and WM across individuals, and two communities of WM voxels were identified according to the hierarchical structures of transitions among modes. Moreover, these modes are coupled to the shape of instantaneous HRFs. Our findings extend previous studies and reveal the non-stationary nature of spectral patterns of BOLD signals over time, providing a spatial-temporal-frequency characterization of resting-state signals in WM.

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping.

A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change substantially. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.

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.

Direct observation of 2-dimensional ices on different surfaces near room temperature without confinement.

Water-solid interfaces play important roles in a wide range of fields, including atmospheric science, geochemistry, electrochemistry, and food science. Herein, we report simulation evidence of 2-dimensional (2D) ice formation on various surfaces and the dependence of the 2D crystalline structure on the hydrophobicity and morphology of the underlying surface. Contrary to the prevailing view that nanoscale confinement is necessary for the 2D liquid-to-bilayer ice transition, we find that the liquid-to-bilayer hexagonal ice (BHI) transition can occur either on a model smooth surface or on model fcc-crystal surfaces with indices of (100), (110), and (111) near room temperature. We identify a critical parameter that characterizes the water-surface interaction, above which the BHI can form on the surface. This critical parameter increases as the temperature increases. Even at temperatures above the freezing temperature of bulk ice (Ih ), we find that BHI can also form on a superhydrophilic surface due to the strong water-surface interaction. The tendency toward the formation of BHI without confinement reflects a proper water-surface interaction that can compensate for the entropy loss during the freezing transition. Furthermore, phase diagrams of 2D ice formation are described on the plane of the adsorption energy versus the fcc lattice constant (Eads-afcc), where 4 monolayer square-like ices are also identified on the fcc model surfaces with distinct water-surface interactions.

First-Principles Molecular Dynamics Simulations of the Spontaneous Freezing Transition of 2D Water in a Nanoslit.

As with bulk ices, two-dimensional (2D) ices exhibit diverse crystalline structures, and the majority of these 2D structures have been predicted based on classical molecular dynamics (MD) simulations. Here, the spontaneous freezing transition of 2D liquid water within hydrophobic nanoslits is demonstrated for the first time using first-principles MD simulations. Various 2D ices are observed under different lateral pressure and temperature conditions. Notably, the liquid water confined to a 6.0 Å-wide nanoslit can spontaneously freeze into a monolayer ice consisting of an array of zigzag water chains at 2.5 GPa and 250 K. Moreover, within an 8.0 Å-wide nanoslit and at 4.0 GPa and 300 K, a previously unreported bilayer ice forms spontaneously that has a structure resembling that of the double surface layers of bulk ice-VII. Both 2D crystalline ices do not obey the ice rule, suggesting first-principles simulation can access a certain phase space that is not easily approached using classical simulations.

Detection of synchronous brain activity in white matter tracts at rest and under functional loading.

Functional MRI based on blood oxygenation level-dependent (BOLD) contrast is well established as a neuroimaging technique for detecting neural activity in the cortex of the human brain. While detection and characterization of BOLD signals, as well as their electrophysiological and hemodynamic/metabolic origins, have been extensively studied in gray matter (GM), the detection and interpretation of BOLD signals in white matter (WM) remain controversial. We have previously observed that BOLD signals in a resting state reveal structure-specific anisotropic temporal correlations in WM and that external stimuli alter these correlations and permit visualization of task-specific fiber pathways, suggesting variations in WM BOLD signals are related to neural activity. In this study, we provide further strong evidence that BOLD signals in WM reflect neural activities both in a resting state and under functional loading. We demonstrate that BOLD signal waveforms in stimulus-relevant WM pathways are synchronous with the applied stimuli but with various degrees of time delay and that signals in WM pathways exhibit clear task specificity. Furthermore, resting-state signal fluctuations in WM tracts show significant correlations with specific parcellated GM volumes. These observations support the notion that neural activities are encoded in WM circuits similarly to cortical responses.

Functional engagement of white matter in resting-state brain networks.

The topological characteristics of functional networks, derived from measurements of resting-state connectivity in gray matter (GM), are associated with individual cognitive abilities or specific dysfunctions. However, blood oxygen level-dependent (BOLD) signals in white matter (WM) are usually ignored or even regressed out as nuisance factors in the data analyses that underlie network models. Recent studies have demonstrated reliable detection of WM BOLD signals and imply these reflect associated neural activities. Here we evaluate quantitatively the contributions of individual WM voxels to the identification of functional networks, which we term their engagement (or conceptually, their importance). We quantify the engagement by measuring the reductions of connectivity, produced by ignoring the signal fluctuations within each WM voxel, with respect to both the entire network (global) or a single GM node (local). We observed highly reproducible spatial distributions of global engagement maps, as well as a trend toward increased relevance of deep WM voxels at delayed times. Local engagement maps exhibit homogeneous spatial distributions with respect to internal nodes that constitute a well-recognized sub-functional network, but inhomogeneous distributions with respect to other nodes. WM voxels show distinct distributions of engagement depending on their anatomical locations. These findings demonstrate the important role of WM in network modeling, thus supporting the need for changes of conventional views that WM signal variations represent only physiological noise.

Turning a Superhydrophilic Surface Weakly Hydrophilic: Topological Wetting States.

For water droplets placed on a rough or structured surface, two distinct wetting states commonly observed are either the Wenzel state (droplets wet the surface without showing air pockets beneath the droplets) or the Cassie state (droplets reside on top of the structure with air pockets trapped beneath the droplets). Herein, we show molecular dynamics (MD) simulation evidence of a previously unreported wetting behavior, i.e., the rise of multiple Wenzel states on the structured surfaces whose flat-surface counterparts are superhydrophilic (i.e., complete wetting surfaces with the hallmark of zero contact angle for water droplets). Specifically, our MD simulations show that on the structured surfaces with topology of closed-loop nanowalls/nanochannels, the water droplet can exhibit multiple Wenzel wetting states with the apparent contact angles >0°. We name these distinct multiple Wenzel states as "topological wetting states" because their existence can be attributed to the topology of the closed-loop nanowalls/nanochannels. Regardless of the shape of the closed loops, such topological wetting states can always arise due to the topological invariant (i.e., all closed loops entail the same topological genus value). This unusual wetting behavior is contrary to the conventional view (and to the prediction of the Wenzel equation), namely, a rough hydrophilic surface should have stronger hydrophilicity than its flat-surface counterpart.

Unraveling Molecular Mechanism on Dilute Surfactant Solution Controlled Ice Recrystallization.

Ice recrystallization (IR) is ubiquitous, playing an important role in many areas of science, such as cryobiology, food science, and atmospheric physics. However, controllable ice recrystallization remains a challenging task largely due to an incomplete understanding of the physical mechanism associated with ice recrystallization. Herein, we explore the molecular mechanism underlying the controlling of ice recrystallization by using different small amphiphilic molecules (surfactants) through joint experimental measurements and molecular dynamics simulation. Our experiment shows that in nonionic/zwitterionic surfactant solutions, the mean size of the recrystallized ice grains increases monotonically with the concentration of surfactants, whereas in the ionic surfactant solutions, the mean size of the recrystallized ice grains tends to increase first and then decrease with increasing the concentration, yielding a peak typically at ∼5 µM. Further sequential ice affinity purification experiments and molecular dynamics simulations show that the surfactants actually do not bind to ice directly. Rather, the different spatial distributions of counter ions and molecular surfactants in the interfacial regions (ice-water interface and water-air interface) and bulk region can markedly affect the mean size of the recrystallized ice grain.