Anomalously enhanced ion transport and uptake in functionalized angstrom-scale two-dimensional channels.

Emulating angstrom-scale dynamics of the highly selective biological ion channels is a challenging task. Recent work on angstrom-scale artificial channels has expanded our understanding of ion transport and uptake mechanisms under confinement. However, the role of chemical environment in such channels is still not well understood. Here, we report the anomalously enhanced transport and uptake of ions under confined MoS2-based channels that are ~five angstroms in size. The ion uptake preference in the MoS2-based channels can be changed by the selection of surface functional groups and ion uptake sequence due to the interplay between kinetic and thermodynamic factors that depend on whether the ions are mixed or not prior to uptake. Our work offers a holistic picture of ion transport in 2D confinement and highlights ion interplay in this regime.

Uncovering the predictive pathways of lithium and sodium interchange in layered oxides.

Ion exchange is a powerful method to access metastable materials with advanced functionalities for energy storage applications. However, high concentrations and unfavourably large excesses of lithium are always used for synthesizing lithium cathodes from parent sodium material, and the reaction pathways remain elusive. Here, using layered oxides as model materials, we demonstrate that vacancy level and its corresponding lithium preference are critical in determining the accessible and inaccessible ion exchange pathways. Taking advantage of the strong lithium preference at the right vacancy level, we establish predictive compositional and structural evolution at extremely dilute and low excess lithium based on the phase equilibrium between Li0.94CoO2 and Na0.48CoO2. Such phase separation behaviour is general in both surface reaction-limited and diffusion-limited exchange conditions and is accomplished with the charge redistribution on transition metals. Guided by this understanding, we demonstrate the synthesis of NayCoO2 from the parent LixCoO2 and the synthesis of Li0.94CoO2 from NayCoO2 at 1-1,000 Li/Na (molar ratio) with an electrochemical assisted ion exchange method by mitigating the kinetic barriers. Our study opens new opportunities for ion exchange in predictive synthesis and separation applications.

VLC channel model in underground mining scenarios with the extinction effect and shadowing effect.

In this work, a novel, to our knowledge, visible light communication (VLC) channel model is proposed for underground mining scenarios taking into account the impact of coal dust particles and obstacles. Specifically, the extinction effect of the coal dust particles is analyzed on the basis of the Mie theory, and the quantitative formula of the influence on channel direct current (DC) gain is derived. Meanwhile, the effect of a random shadowing phenomenon is investigated and quantified with the geometric and statistical model considering the position, size, and shape of the obstacles. The channel impulse response, path loss, root mean square delay spread, and bit error rate (BER) are further investigated in two different underground mining scenarios, namely, a mining roadway and coal mine working face. Simulation results show that the shadowing effect plays a major role in the influence of DC gain attenuation. Furthermore, the BER performance is noticeably degraded due to the presence of coal dust particles and obstacles, especially when the receiver is located far from the transmitter. This work will benefit the design of the VLC systems in underground mines.

Average signal-to-noise ratio maximization for an intelligent reflecting surface and angle diversity receiver jointly assisted indoor visible light communication system.

The intelligent reflecting surface (IRS) and angle diversity receiver (ADR) jointly assisted indoor visible light communication (VLC) system is proposed to improve average signal-to-noise ratio (ASNR) performance. Specifically, to maximize the ASNR at the receiving plane, the roll angle and yaw angle of IRS and the inclination angle of the side detector in the ADR structure are optimized simultaneously as one non-convex problem. With the bat algorithm, the optimal solution is numerically obtained. Results show that when the transmit power of the light emitting diode lamp array is 1 W, the ASNRs of this VLC system optimized by IRS and ADR are approximately 7.89 dB, 3.58 dB, and 2.09 dB higher than those of the original, IRS-assisted, and ADR-assisted VLC systems, respectively. Furthermore, the transmission rate and bit error rate performances of the original, IRS-assisted, ADR-assisted, and IRS and ADR jointly assisted indoor VLC systems are also simulated and compared; it is found that the performance improvement of the indoor VLC system jointly optimized by IRS and ADR is more evident than that of the other three VLC systems. This study will benefit the research and development of indoor VLC systems.

Texturing Silicon Nanowires for Highly Localized Optical Modulation of Cellular Dynamics.

Engineered silicon-based materials can display photoelectric and photothermal responses under light illumination, which may lead to further innovations at the silicon-biology interfaces. Silicon nanowires have small radial dimensions, promising as highly localized cellular modulators, however the single crystalline form typically has limited photothermal efficacy due to the poor light absorption and fast heat dissipation. In this work, we report strategies to improve the photothermal response from silicon nanowires by introducing nanoscale textures on the surface and in the bulk. We next demonstrate high-resolution extracellular modulation of calcium dynamics in a number of mammalian cells including glial cells, neurons, and cancer cells. The new materials may be broadly used in probing and modulating electrical and chemical signals at the subcellular length scale, which is currently a challenge in the field of electrophysiology or cellular engineering.

Au@MoS2 Core-Shell Heterostructures with Strong Light-Matter Interactions.

There are emerging opportunities to harness diverse and complex geometric architectures based on nominal two-dimensional atomically layered structures. Herein we report synthesis and properties of a new core-shell heterostructure, termed Au@MoS2, where the Au nanoparticle is snugly and contiguously encapsulated by few shells of MoS2 atomic layers. The heterostructures were synthesized by direct growth of multilayer fullerene-like MoS2 shell on Au nanoparticle cores. The Au@MoS2 heterostructures exhibit interesting light-matter interactions due to the structural curvature of MoS2 shell and the plasmonic effect from the underlying Au nanoparticle core. We observed significantly enhanced Raman scattering and photoluminescence emission on these heterostructures. We attribute these enhancements to the surface plasmon-induced electric field, which simulations show to mainly localize within the MoS2 shell. We also found potential evidence for the charge transfer-induced doping effect on the MoS2 shell. The DFT calculations further reveal that the structural curvature of MoS2 shell results in a modification of its electronic structure, which may facilitate the charge transfer from MoS2 to Au. Such Au@MoS2 core-shell heterostructures have the potential for future optoelectronic devices, optical imaging, and other energy-environmental applications.

Valence Band Modification and High Thermoelectric Performance in SnTe Heavily Alloyed with MnTe.

We demonstrate a high solubility limit of >9 mol% for MnTe alloying in SnTe. The electrical conductivity of SnTe decreases gradually while the Seebeck coefficient increases remarkably with increasing MnTe content, leading to enhanced power factors. The room-temperature Seebeck coefficients of Mn-doped SnTe are significantly higher than those predicted by theoretical Pisarenko plots for pure SnTe, indicating a modified band structure. The high-temperature Hall data of Sn1-xMnxTe show strong temperature dependence, suggestive of a two-valence-band conduction behavior. Moreover, the peak temperature of the Hall plot of Sn1-xMnxTe shifts toward lower temperature as MnTe content is increased, which is clear evidence of decreased energy separation (band convergence) between the two valence bands. The first-principles electronic structure calculations based on density functional theory also support this point. The higher doping fraction (>9%) of Mn in comparison with ∼3% for Cd and Hg in SnTe gives rise to a much better valence band convergence that is responsible for the observed highest Seebeck coefficient of ∼230 µV/K at 900 K. The high doping fraction of Mn in SnTe also creates stronger point defect scattering, which when combined with ubiquitous endotaxial MnTe nanostructures when the solubility of Mn is exceeded scatters a wide spectrum of phonons for a low lattice thermal conductivity of 0.9 W m(-1) K(-1) at 800 K. The synergistic role that Mn plays in regulating the electron and phonon transport of SnTe yields a high thermoelectric figure of merit of 1.3 at 900 K.

Two-dimensional mineral [Pb2BiS3][AuTe2]: high-mobility charge carriers in single-atom-thick layers.

Two-dimensional (2D) electronic systems are of wide interest due to their richness in chemical and physical phenomena and potential for technological applications. Here we report that [Pb2BiS3][AuTe2], known as the naturally occurring mineral buckhornite, hosts 2D carriers in single-atom-thick layers. The structure is composed of stacking layers of weakly coupled [Pb2BiS3] and [AuTe2] sheets. The insulating [Pb2BiS3] sheet inhibits interlayer charge hopping and confines the carriers in the basal plane of the single-atom-thick [AuTe2] layer. Magneto-transport measurements on synthesized samples and theoretical calculations show that [Pb2BiS3][AuTe2] is a multiband semimetal with a compensated density of electrons and holes, which exhibits a high hole carrier mobility of ∼1360 cm(2)/(V s). This material possesses an extremely large anisotropy, Γ = ρ(c)/ρ(ab) ≈ 10(4), comparable to those of the benchmark 2D materials graphite and Bi2Sr2CaCu2O(6+δ). The electronic structure features linear band dispersion at the Fermi level and ultrahigh Fermi velocities of 10(6) m/s, which are virtually identical to those of graphene. The weak interlayer coupling gives rise to the highly cleavable property of the single crystal specimens. Our results provide a novel candidate for a monolayer platform to investigate emerging electronic properties.

Codoping in SnTe: Enhancement of Thermoelectric Performance through Synergy of Resonance Levels and Band Convergence.

We report a significant enhancement of the thermoelectric performance of p-type SnTe over a broad temperature plateau with a peak ZT value of ∼1.4 at 923 K through In/Cd codoping and a CdS nanostructuring approach. Indium and cadmium play different but complementary roles in modifying the valence band structure of SnTe. Specifically, In-doping introduces resonant levels inside the valence bands, leading to a considerably improved Seebeck coefficient at low temperature. Cd-doping, however, increases the Seebeck coefficient of SnTe remarkably in the mid- to high-temperature region via a convergence of the light and heavy hole bands and an enlargement of the band gap. Combining the two dopants in SnTe yields enhanced Seebeck coefficient and power factor over a wide temperature range due to the synergy of resonance levels and valence band convergence, as demonstrated by the Pisarenko plot and supported by first-principles band structure calculations. Moreover, these codoped samples can be hierarchically structured on all scales (atomic point defects by doping, nanoscale precipitations by CdS nanostructuring, and mesoscale grains by SPS treatment) to achieve highly effective phonon scattering leading to strongly reduced thermal conductivities. In addition to the high maximum ZT the resultant large average ZT of ∼0.8 between 300 and 923 K makes SnTe an attractive p-type material for high-temperature thermoelectric power generation.

High thermoelectric performance of p-type SnTe via a synergistic band engineering and nanostructuring approach.

SnTe is a potentially attractive thermoelectric because it is the lead-free rock-salt analogue of PbTe. However, SnTe is a poor thermoelectric material because of its high hole concentration arising from inherent Sn vacancies in the lattice and its very high electrical and thermal conductivity. In this study, we demonstrate that SnTe-based materials can be controlled to become excellent thermoelectrics for power generation via the successful application of several key concepts that obviate the well-known disadvantages of SnTe. First, we show that Sn self-compensation can effectively reduce the Sn vacancies and decrease the hole carrier density. For example, a 3 mol % self-compensation of Sn results in a 50% improvement in the figure of merit ZT. In addition, we reveal that Cd, nominally isoelectronic with Sn, favorably impacts the electronic band structure by (a) diminishing the energy separation between the light-hole and heavy-hole valence bands in the material, leading to an enhanced Seebeck coefficient, and (b) enlarging the energy band gap. Thus, alloying with Cd atoms enables a form of valence band engineering that improves the high-temperature thermoelectric performance, where p-type samples of SnCd(0.03)Te exhibit ZT values of ~0.96 at 823 K, a 60% improvement over the Cd-free sample. Finally, we introduce endotaxial CdS or ZnS nanoscale precipitates that reduce the lattice thermal conductivity of SnCd(0.03)Te with no effect on the power factor. We report that SnCd(0.03)Te that are endotaxially nanostructured with CdS and ZnS have a maximum ZTs of ~1.3 and ~1.1 at 873 K, respectively. Therefore, SnTe-based materials could be ideal alternatives for p-type lead chalcogenides for high temperature thermoelectric power generation.

Dynamic MDETR: A Dynamic Multimodal Transformer Decoder for Visual Grounding.

Multimodal transformer exhibits high capacity and flexibility to align image and text for visual grounding. However, the existing encoder-only grounding framework (e.g., TransVG) suffers from heavy computation due to the self-attention operation with quadratic time complexity. To address this issue, we present a new multimodal transformer architecture, coined as Dynamic Mutilmodal detection transformer (DETR) (Dynamic MDETR), by decoupling the whole grounding process into encoding and decoding phases. The key observation is that there exists high spatial redundancy in images. Thus, we devise a new dynamic multimodal transformer decoder by exploiting this sparsity prior to speed up the visual grounding process. Specifically, our dynamic decoder is composed of a 2D adaptive sampling module and a text guided decoding module. The sampling module aims to select these informative patches by predicting the offsets with respect to a reference point, while the decoding module works for extracting the grounded object information by performing cross attention between image features and text features. These two modules are stacked alternatively to gradually bridge the modality gap and iteratively refine the reference point of grounded object, eventually realizing the objective of visual grounding. Extensive experiments on five benchmarks demonstrate that our proposed Dynamic MDETR achieves competitive trade-offs between computation and accuracy. Notably, using only 9% feature points in the decoder, we can reduce  âˆ¼ 44% GFLOPs of the multimodal transformer, but still get higher accuracy than the encoder-only counterpart. With the same number of encoder layers as TransVG, our Dynamic MDETR (ResNet-50) outperforms TransVG (ResNet-101) but only brings marginal extra computational cost relative to TransVG. In addition, to verify its generalization ability and scale up our Dynamic MDETR, we build the first one-stage CLIP empowered visual grounding framework, and achieve the state-of-the-art performance on these benchmarks.

Stabilization of copper catalysts for liquid-phase reactions by atomic layer deposition.

Atomic layer deposition (ALD) of an alumina overcoat can stabilize a base metal catalyst (e.g., copper) for liquid-phase catalytic reactions (e.g., hydrogenation of biomass-derived furfural in alcoholic solvents or water), thereby eliminating the deactivation of conventional catalysts by sintering and leaching. This method of catalyst stabilization alleviates the need to employ precious metals (e.g., platinum) in liquid-phase catalytic processing. The alumina overcoat initially covers the catalyst surface completely. By using solid state NMR spectroscopy, X-ray diffraction, and electron microscopy, it was shown that high temperature treatment opens porosity in the overcoat by forming crystallites of γ-Al2 O3 . Infrared spectroscopic measurements and scanning tunneling microscopy studies of trimethylaluminum ALD on copper show that the remarkable stability imparted to the nanoparticles arises from selective armoring of under-coordinated copper atoms on the nanoparticle surface.

Improvement of Reinforcement Learning With Supermodularity.

Reinforcement learning (RL) is a promising approach to tackling learning and decision-making problems in a dynamic environment. Most studies on RL focus on the improvement of state evaluation or action evaluation. In this article, we investigate how to reduce action space by using supermodularity. We consider the decision tasks in the multistage decision process as a collection of parameterized optimization problems, where state parameters dynamically vary along with the time or stage. The optimal solutions of these parameterized optimization problems correspond to the optimal actions in RL. For a given Markov decision process (MDP) with supermodularity, the monotonicity of the optimal action set and the optimal selection with respect to state parameters can be obtained by using the monotone comparative statics. Accordingly, we propose a monotonicity cut to remove unpromising actions from the action space. Taking bin packing problem (BPP) as an example, we show how the supermodularity and monotonicity cut work in RL. Finally, we evaluate the monotonicity cut on the benchmark datasets reported in the literature and compare the proposed RL with some popular baseline algorithms. The results show that the monotonicity cut can effectively improve the performance of RL.

Periplasmic biomineralization for semi-artificial photosynthesis.

Semiconductor-based biointerfaces are typically established either on the surface of the plasma membrane or within the cytoplasm. In Gram-negative bacteria, the periplasmic space, characterized by its confinement and the presence of numerous enzymes and peptidoglycans, offers additional opportunities for biomineralization, allowing for nongenetic modulation interfaces. We demonstrate semiconductor nanocluster precipitation containing single- and multiple-metal elements within the periplasm, as observed through various electron- and x-ray-based imaging techniques. The periplasmic semiconductors are metastable and display defect-dominant fluorescent properties. Unexpectedly, the defect-rich (i.e., the low-grade) semiconductor nanoclusters produced in situ can still increase adenosine triphosphate levels and malate production when coupled with photosensitization. We expand the sustainability levels of the biohybrid system to include reducing heavy metals at the primary level, building living bioreactors at the secondary level, and creating semi-artificial photosynthesis at the tertiary level. The biomineralization-enabled periplasmic biohybrids have the potential to serve as defect-tolerant platforms for diverse sustainable applications.

A soil-inspired dynamically responsive chemical system for microbial modulation.

Interactions between the microbiota and their colonized environments mediate critical pathways from biogeochemical cycles to homeostasis in human health. Here we report a soil-inspired chemical system that consists of nanostructured minerals, starch granules and liquid metals. Fabricated via a bottom-up synthesis, the soil-inspired chemical system can enable chemical redistribution and modulation of microbial communities. We characterize the composite, confirming its structural similarity to the soil, with three-dimensional X-ray fluorescence and ptychographic tomography and electron microscopy imaging. We also demonstrate that post-synthetic modifications formed by laser irradiation led to chemical heterogeneities from the atomic to the macroscopic level. The soil-inspired material possesses chemical, optical and mechanical responsiveness to yield write-erase functions in electrical performance. The composite can also enhance microbial culture/biofilm growth and biofuel production in vitro. Finally, we show that the soil-inspired system enriches gut bacteria diversity, rectifies tetracycline-induced gut microbiome dysbiosis and ameliorates dextran sulfate sodium-induced rodent colitis symptoms within in vivo rodent models.

The role of solid solutions in iron phosphate-based electrodes for selective electrochemical lithium extraction.

Electrochemical intercalation can enable lithium extraction from dilute water sources. However, during extraction, co-intercalation of lithium and sodium ions occurs, and the response of host materials to this process is not fully understood. This aspect limits the rational materials designs for improving lithium extraction. Here, to address this knowledge gap, we report one-dimensional (1D) olivine iron phosphate (FePO4) as a model host to investigate the co-intercalation behavior and demonstrate the control of lithium selectivity through intercalation kinetic manipulations. Via computational and experimental investigations, we show that lithium and sodium tend to phase separate in the host. Exploiting this mechanism, we increase the sodium-ion intercalation energy barrier by using partially filled 1D lithium channels via non-equilibrium solid-solution lithium seeding or remnant lithium in the solid-solution phases. The lithium selectivity enhancement after seeding shows a strong correlation with the fractions of solid-solution phases with high lithium content (i.e., LixFePO4 with 0.5 ≤ x < 1). Finally, we also demonstrate that the solid-solution formation pathway depends on the host material's particle morphology, size and defect content.

Tuning transport in graphene oxide membrane with single-site copper (II) cations.

Controlling the ion transport through graphene oxide (GO) membrane is challenging, particularly in the aqueous environment due to its strong swelling tendency. Fine-tuning the interlayer spacing and chemistry is critical to create highly selective membranes. We investigate the effect of single-site divalent cations in tuning GO membrane properties. Competitive ionic permeation test indicates that Cu2+ cations dominate the transport through the 2D channels of GO membrane over other cations (Mg2+/Ca2+/Co2+). Without/With the single-site M2+ modifications, pristine GO, Mg-GO, Ca-GO, and Cu-GO membranes show interlayer spacings of ∼13.6, 15.6, 14.5, and 12.3 Å in wet state, respectively. The Cu-GO membrane shows a two-fold decrease of NaCl (1 M) permeation rate comparing to pristine GO, Mg-GO, and Ca-GO membranes. In reverse osmosis tests using 1000 ppm NaCl and Na2SO4 as feeds, Cu-GO membrane shows rejection of ∼78% and ∼94%, respectively, which are 5%-10% higher than its counterpart membranes.

Laser writing of nitrogen-doped silicon carbide for biological modulation.

Conducting or semiconducting materials embedded in insulating polymeric substrates can be useful in biointerface applications; however, attainment of this composite configuration by direct chemical processes is challenging. Laser-assisted synthesis has evolved as a fast and inexpensive technique to prepare various materials, but its utility in the construction of biophysical tools or biomedical devices is less explored. Here, we use laser writing to convert portions of polydimethylsiloxane (PDMS) into nitrogen-doped cubic silicon carbide (3C-SiC). The dense 3C-SiC surface layer is connected to the PDMS matrix via a spongy graphite layer, facilitating electrochemical and photoelectrochemical activity. We demonstrate the fabrication of arbitrary two-dimensional (2D) SiC-based patterns in PDMS and freestanding 3D constructs. To establish the functionality of the laser-produced composite, we apply it as flexible electrodes for pacing isolated hearts and as photoelectrodes for local peroxide delivery to smooth muscle sheets.

Structured silicon for revealing transient and integrated signal transductions in microbial systems.

Bacterial response to transient physical stress is critical to their homeostasis and survival in the dynamic natural environment. Because of the lack of biophysical tools capable of delivering precise and localized physical perturbations to a bacterial community, the underlying mechanism of microbial signal transduction has remained unexplored. Here, we developed multiscale and structured silicon (Si) materials as nongenetic optical transducers capable of modulating the activities of both single bacterial cells and biofilms at high spatiotemporal resolution. Upon optical stimulation, we capture a previously unidentified form of rapid, photothermal gradient-dependent, intercellular calcium signaling within the biofilm. We also found an unexpected coupling between calcium dynamics and biofilm mechanics, which could be of importance for biofilm resistance. Our results suggest that functional integration of Si materials and bacteria, and associated control of signal transduction, may lead to hybrid living matter toward future synthetic biology and adaptable materials.

Rational design of silicon structures for optically controlled multiscale biointerfaces.

Silicon-based materials have been widely used. However, remotely controlled and interconnect-free silicon configurations have been rarely explored, because of limited fundamental understanding of the complex physicochemical processes that occur at interfaces between silicon and biological materials. Here, we describe rational design principles, guided by biology, for establishing intracellular, intercellular and extracellular silicon-based interfaces, where the silicon and the biological targets have matched properties. We focused on light-induced processes at these interfaces, and developed a set of matrices to quantify and differentiate the capacitive, Faradaic and thermal outputs from about 30 different silicon materials in saline. We show that these interfaces are useful for the light-controlled non-genetic modulation of intracellular calcium dynamics, of cytoskeletal structures and transport, of cellular excitability, of neurotransmitter release from brain slices, and of brain activity in vivo.