STEM in situ thermal wave observations for investigating thermal diffusivity in nanoscale materials and devices.

Practical techniques to identify heat routes at the nanoscale are required for the thermal control of microelectronic, thermoelectric, and photonic devices. Nanoscale thermometry using various approaches has been extensively investigated, yet a reliable method has not been finalized. We developed an original technique using thermal waves induced by a pulsed convergent electron beam in a scanning transmission electron microscopy (STEM) mode at room temperature. By quantifying the relative phase delay at each irradiated position, we demonstrate the heat transport within various samples with a spatial resolution of ~10 nm and a temperature resolution of 0.01 K. Phonon-surface scatterings were quantitatively confirmed due to the suppression of thermal diffusivity. The phonon-grain boundary scatterings and ballistic phonon transport near the pulsed convergent electron beam were also visualized.

Magnetic and Ferroelectric Manipulation of Valley Physics in Janus Piezoelectric Materials.

The realization of multiferroic materials offers the possibility of multifunctional electronic device design. However, the coupling between the multiferroicity and piezoelectricity in Janus materials is rarely reported. In this study, we propose a mechanism for manipulating valley physics by magnetization reversing and ferroelectric switching in multiferroic and piezoelectric material. The ferromagnetic VSiGeP4 monolayer exhibits a large valley polarization up to 100 meV, which can be effectively operated by reversing magnetization. Interestingly, the antiferromagnetic VSiGeP4 bilayers with AB and BA stacking configurations allow the coexistence of valley polarization and ferroelectricity, supporting the proposed strategy for manipulating valley physics via ferroelectric switching and interlayer sliding. In addition, the VSiGeP4 monolayer contains remarkable tunable piezoelectricity regulated by electron correlation U. This study proposes a feasible idea for regulating valley polarization and a general design idea for multifunctional devices with multiferroic and piezoelectric properties, facilitating the miniaturization and integration of nanodevices.

Efficient Exploration of Adsorption Space for Separations in Metal-Organic Frameworks Combining the Use of Molecular Simulations, Machine Learning, and Ideal Adsorbed Solution Theory.

Adsorption-based separations using metal-organic frameworks (MOFs) are promising candidates for replacing common energy-intensive separation processes. The so-called adsorption space formed by the combination of billions of possible molecules and thousands of reported MOFs is vast. It is very challenging to comprehensively evaluate the performance of MOFs for chemical separation through experiments. Molecular simulations and machine learning (ML) have been widely applied to make predictions for adsorption-based separations. Previous ML approaches to these issues were typically limited to smaller molecules and often had poor accuracy in the dilute limit. To enable exploration of a wider adsorption space, we carefully selected a diverse set of 45 molecules and 335 MOFs and generated single-component isotherms of 15,075 MOF-molecule pairs by grand canonical Monte Carlo. Using this database, we successfully developed accurate (r2 > 0.9) machine learning models predicting adsorption isotherms of diverse molecules in large libraries of MOFs. With this approach, we can efficiently make predictions of large collections of MOFs for arbitrary mixture separations. By combining molecular simulation data and ML predictions with Ideal Adsorbed Solution Theory, we tested the ability of these approaches to make predictions of adsorption selectivity and loading for challenging near-azeotropic mixtures.

Light-Induced Dynamic Restructuring of Cu Active Sites on TiO2 for Low-Temperature H2 Production from Methanol and Water.

The structure and configuration of reaction centers, which dominantly govern the catalytic behaviors, often undergo dynamic transformations under reaction conditions, yet little is known about how to exploit these features to favor the catalytic functions. Here, we demonstrate a facile light activation strategy over a TiO2-supported Cu catalyst to regulate the dynamic restructuring of Cu active sites during low-temperature methanol steam reforming. Under illumination, the thermally deactivated Cu/TiO2 undergoes structural restoration from inoperative Cu2O to the originally active metallic Cu caused by photoexcited charge carriers from TiO2, thereby leading to substantially enhanced activity and stability. Given the low-intensity solar irradiation, the optimized Cu/TiO2 displays a H2 production rate of 1724.1 µmol g-1 min-1, outperforming most of the conventional photocatalytic and thermocatalytic processes. Taking advantages of the strong light-matter-reactant interaction, we achieve in situ manipulation of the Cu active sites, suggesting the feasibility for real-time functionalization of catalysts.

Switch effect on controlled water splitting by biaxial strain regulating the promising two-dimensional Janus X2PAs (X = Si, Ge and Sn) photocatalyst.

Two-dimensional photocatalytic materials with unique properties have been well-reported in recent decades. However, strategies for controlling the photocatalytic process are still ongoing. Herein, Janus X2PAs (X = Si, Ge and Sn) monolayers have been explored by first-principles calculations to meet this challenge. All strain-free X2PAs monolayers exhibit excellent photocatalytic properties with high carrier mobility (2.39 × 102-1.34 × 104 cm2 V-1 s-1), suitable band edge positions straddling the standard redox potential of water and large visible light absorption coefficients (up to 105 cm-1). Most importantly, a reaction switch effect is proposed for the first time towards controlling the microscopic photocatalytic process of water splitting on X2PAs monolayers through macroscopic mechanical strain. This effect renders the Janus X2PAs photocatalytic switches among the states of only oxygen evolution reaction, only hydrogen evolution reaction and the full redox reaction for controlled water splitting. This work not only provides a new avenue for designing highly tunable photocatalysts but also offers new physical insights into controlling the photocatalytic water-splitting reaction.

Thermal and Chemical Phase Engineering of Two-Dimensional Ruthenate.

Monolayer ruthenate nanosheets obtained by exfoliating layered ruthenium oxide exhibit excellent electrical conductivity, redox activity, and catalytic activity, which render them suitable for advanced electronic and energy devices. However, to fully exploit the benefits, we require further structural insights into a complex polymorphic nature and diversity in relevant electronic states of two-dimensional (2D) ruthenate systems. In this study, the 2D structures, stability, and electronic states of 2D ruthenate are investigated on the basis of thermal and chemical phase engineering approaches. We reveal that contrary to a previous report, exfoliation of an oblique 1T phase precursor leads to nanosheets having an identical phase without exfoliation-induced phase transition to a 1H phase. The oblique 1T phase in the nanosheets is found to be metastable and, thus, transforms successively to a rectangular 1T phase upon heating. A phase-controllable synthesis via Co doping affords nanosheets with metastable rectangular and thermally stable hexagonal 1T phases at a Co content of 5-10 and 20 at%, respectively. The 1T phases show metallic electronic states, where the d-d optical transitions between the Ru 4d (t2g) orbital depend on the symmetry of the Ru framework. The Co doping in ruthenate nanosheets unexpectedly suppresses the redox and catalytic activities under acidic conditions. In contrast, the Co2+/3+ redox pair is activated and produces conductive nanosheets with high electrochemical capacitance in an alkaline condition.

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials.

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ∼ 0.94-0.99) for predicting single-component adsorption capacity in metal-organic frameworks (MOFs). We consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

Growth mechanism of carbon nanotubes from Co-W-C alloy catalyst revealed by atmospheric environmental transmission electron microscopy.

High-melting point alloy catalysts have been reported to be effective for the structure-controlled growth of single-wall carbon nanotubes (SWCNTs). However, some fundamental issues remain unclear because of the complex catalytic growth environment. Here, we directly investigated the active catalytic phase of Co-W-C alloy catalyst, the growth kinetics of CNTs, and their interfacial dynamics using closed-cell environmental transmission electron microscopy at atmospheric pressure. The alloy catalyst was precisely identified as a cubic η-carbide phase that remained unchanged during the whole CNT growth process. Rotations of the catalyst nanoparticles during CNT growth were observed, implying a weak interfacial interaction and undefined orientation dependence for the solid catalyst. Theoretical calculations suggested that the growth kinetics are determined by the diffusion of carbon atoms on the surface of the η-carbide catalyst and through the interface of the catalyst-CNT wall.

A novel sulfur-driven autotrophic denitrification coupled with bio-cathode system for bioelectricity generation and groundwater remediation.

This study explored the feasibility of treating wastewater using sulfur-driven autotrophic denitrification (SAD) coupled with the bio-cathode of microbial fuel cell (MFC), focusing on simultaneous bioelectricity generation, denitrification, and desulphurization. A maximum output voltage of 360 mV was obtained with a power generation cycle of 25 h when simulated wastewater with 100.0 mg/L of each NO3--N and S2--S was employed as the influent in the SAD-BMFC. Compared with solo SAD or MFC, SAD-BMFC obtained a higher NO3--N removal rate (E12 h = 87.7%, E24 h = 100%), and less NO2--N accumulation. S2--S of the influent was almost completely removed, oxidized to S0-S (88.6-90.2 mg/L) and SO42--S (9.8-11.4 mg/L). The reaction system achieved self-balance of acidity-alkalinity (pH 7.05-7.35). The SAD process was the main pathway for NO3--N removal (80.2%) and a smaller proportion of electrons came from the bio-cathode. This study effectively combined SAD with a bio-cathode system for simultaneous energy harvest and bio-enhanced remediation of groundwater contaminated by both NO3--N and S2--S.

Nucleation of Single-Wall Carbon Nanotubes from Faceted Pt Catalyst Particles Revealed by in Situ Transmission Electron Microscopy.

Revealing the nucleation and growth mechanism of single-wall carbon nanotubes (SWCNTs) from faceted solid catalysts is crucial to the control of their structure and properties. However, due to the small size and complex growth environment, the early stages and dynamic process of SWCNT nucleation have rarely been directly revealed, especially under atmospheric conditions. Here, we report the atomic-resolved nucleation of SWCNTs from the faces of truncated octahedral Pt catalysts under atmospheric pressure using a transmission electron microscope equipped with a gas-cell. It was found that the graphene layers were initially formed preferentially on (111) surfaces, which then joined together to form an annular belt and a hemispherical cap, followed by the elongation of the SWCNT. Based on the observations, an annular belt assembly nucleation model and a possible chirality control mechanism are proposed for SWCNTs grown from well-faceted Pt catalysts, which provides useful guidance for the controlled synthesis of SWCNTs by catalyst design.

Active Asymmetric Electron-Transfer Effect on the Enhanced Piezoelectricity in MoTO (T = S, Se, or Te) Monolayers and Bilayers.

Development of piezoelectric materials is limited partly due to the incompleteness of internal mechanism and the lack of vertical piezoelectricity. Herein, we theoretically identify the stable MoTO (T = S, Se, or Te) monolayers and bilayers. When two elements are given but another element can be changed, the larger the electronegativity difference ratio Rratio is, the stronger the piezoelectricity will be. Vertical piezoelectric coefficient d33 of the MoTeO bilayer reaches 38.907 pm/V, which is 12 times larger than that of the bulk GaN. The "active asymmetric electron-transfer" strategy mainly contributes to the spontaneous remarkable piezoelectricity of MoTO. Importantly, we proposed the new method for calculating the piezoelectric coefficients of two-dimensional (2D) materials, which corresponds to the fact that 2D materials have a certain thickness. This study not only provides novel extraordinary candidates for energy conversion and touch-sensor nanodevices but also promotes a deeper understanding of piezoelectricity of 2D materials.

Metal-Organic Framework Integrating Ionic Framework and Bimetallic Coupling Effect for Highly Efficient Oxygen Evolution Reaction.

Metal-organic frameworks (MOFs) are recognized as promising electrocatalysts for the oxygen evolution reaction (OER) because of their permanent porosity and rich architectural diversity; however, ionic MOFs enabling fast ions exchange during OER are rarely explored. Here, an ionic MOF (Ni-btz) constructed with an azolate ligand is selected, and continuous 3D bimetallic MOF (NiFe-btz) films deriving from high-degree intergrowth of microsized MOFs particles are fabricated. The as-prepared NiFe-btz/NF-OH electrode exhibits excellent OER performance with a low overpotential of 239 mV at 10 mA cm-2 under alkaline condition. The OER charge transfer process and bimetallic coupling effect in ionic NiFe-btz are probed by density functional theory calculations and confirmed via X-ray photoelectron spectroscopy and in situ Raman measurements. The partial density of states of NiFe-btz indicates that the main contribution for electron density around the Fermi level is from Cl ions clarifying the profitable impact of ionic MOF framework. This work systematically demonstrates the relationship of electronic structure and OER activity in ionic, bimetallic MOFs and expands the scope of 3D MOF films for efficient OER.

Efficient direct conversion of methane into methanol on CuZn hetero-diatomic catalysts with certain coordination spheres: a DFT study.

The oxidation of methane to a high-value-added chemical, methanol, is a major challenge in catalysis, requiring high energy input to overcome the CH3-H bond activation energy barrier. Based on density functional theory (DFT) calculations, methane oxidation to methanol is catalyzed by hetero-diatomic catalysts (CuZn-NG) with different coordination spheres (CSs). Valence band maximum (VBM), atomic charge and d-band center are selected as analysis methods for the pathway selection and activity of catalysis. The VBM plays a vital role in the catalytic pathway selection, CuZn-NG catalyzes the direct conversion of methane into methanol without side reactions. Alarmingly, the most important reaction step, CH3-H bond activation, is a spontaneously exothermic reaction (releasing 0.06 eV) with CuZn-NPAG as the catalyst, in contrast to most other endothermic reactions in the same activation. By analyzing the atomic charge of the Cu center and O atom, the special electronic phenomenon for this important step is summarized as the "bow-release effect". The CS affects the electronic properties of the active center and further affects the methane oxidation activity. This work provides a useful guide to understand the catalytic selectivity and activity of hetero-diatomic catalysts.

Application of a New Mesh Fixation Method in Laparoscopic Incisional Hernia Repair.

Laparoscopic incisional hernia repair using intraperitoneal onlay mesh (IPOM) is one of the most widely used minimally invasive methods for repairing incisional hernias. The laparoscopic IPOM involves implanting the mesh into the abdominal cavity through laparoscopy to repair an abdominal wall hernia. In the IPOM surgery, after the closure of the hernia ring, an anti-adhesion mesh is placed laparoscopically. The correct placement of this mesh is critical to the success of the method, and surgical skills are required to achieve perfect placement. If the mesh placement is not mastered properly, the operation and anesthesia time will be prolonged. In addition, improper placement of the mesh can lead to serious consequences, such as intestinal obstruction and mesh infection. A "contraposition and alignment" mesh fixation method is described in this study, which involves pre-marking the fixation position of the mesh to reduce the difficulty of mesh placement. A properly placed mesh is completely flat on the peritoneum, the edges are not curled or wrapped, and the mesh is adhered firmly such that there is no displacement after removing the pneumoperitoneum pressure. The "contraposition and alignment" mesh fixation technique offers the advantages of reliable placement of the mesh and fewer complications than other techniques, and it is easy to learn and master. It also allows for positioning the nail gun in advance based on the anatomy of the incisional hernia. This enables the use of the minimum number of nails possible while still ensuring good fixation, which can reduce the occurrence of complications and reduce the cost of surgery. Thus, the mesh fixation method described here is highly suitable for clinical applications based on the aforementioned advantages.

Semiconductor nanochannels in metallic carbon nanotubes by thermomechanical chirality alteration.

Carbon nanotubes have a helical structure wherein the chirality determines whether they are metallic or semiconducting. Using in situ transmission electron microscopy, we applied heating and mechanical strain to alter the local chirality and thereby control the electronic properties of individual single-wall carbon nanotubes. A transition trend toward a larger chiral angle region was observed and explained in terms of orientation-dependent dislocation formation energy. A controlled metal-to-semiconductor transition was realized to create nanotube transistors with a semiconducting nanotube channel covalently bonded between a metallic nanotube source and drain. Additionally, quantum transport at room temperature was demonstrated for the fabricated nanotube transistors with a channel length as short as 2.8 nanometers.

1000 Wh L-1 lithium-ion batteries enabled by crosslink-shrunk tough carbon encapsulated silicon microparticle anodes.

Microparticulate silicon (Si), normally shelled with carbons, features higher tap density and less interfacial side reactions compared to its nanosized counterpart, showing great potential to be applied as high-energy lithium-ion battery anodes. However, localized high stress generated during fabrication and particularly, under operating, could induce cracking of carbon shells and release pulverized nanoparticles, significantly deteriorating its electrochemical performance. Here we design a strong yet ductile carbon cage from an easily processing capillary shrinkage of graphene hydrogel followed by precise tailoring of inner voids. Such a structure, analog to the stable structure of plant cells, presents 'imperfection-tolerance' to volume variation of irregular Si microparticles, maintaining the electrode integrity over 1000 cycles with Coulombic efficiency over 99.5%. This design enables the use of a dense and thick (3 mAh cm-2) microparticulate Si anode with an ultra-high volumetric energy density of 1048 Wh L-1 achieved at pouch full-cell level coupled with a LiNi0.8Co0.1Mn0.1O2 cathode.

One-dimensional van der Waals heterostructures: Growth mechanism and handedness correlation revealed by nondestructive TEM.

We recently synthesized one-dimensional (1D) van der Waals heterostructures in which different atomic layers (e.g., boron nitride or molybdenum disulfide) seamlessly wrap around a single-walled carbon nanotube (SWCNT) and form a coaxial, crystalized heteronanotube. The growth process of 1D heterostructure is unconventional-different crystals need to nucleate on a highly curved surface and extend nanotubes shell by shell-so understanding the formation mechanism is of fundamental research interest. In this work, we perform a follow-up and comprehensive study on the structural details and formation mechanism of chemical vapor deposition (CVD)-synthesized 1D heterostructures. Edge structures, nucleation sites, and crystal epitaxial relationships are clearly revealed using transmission electron microscopy (TEM). This is achieved by the direct synthesis of heteronanotubes on a CVD-compatible Si/SiO2 TEM grid, which enabled a transfer-free and nondestructive access to many intrinsic structural details. In particular, we have distinguished different-shaped boron nitride nanotube (BNNT) edges, which are confirmed by electron diffraction at the same location to be strictly associated with its own chiral angle and polarity. We also demonstrate the importance of surface cleanness and isolation for the formation of perfect 1D heterostructures. Furthermore, we elucidate the handedness correlation between the SWCNT template and BNNT crystals. This work not only provides an in-depth understanding of this 1D heterostructure material group but also, in a more general perspective, serves as an interesting investigation on crystal growth on highly curved (radius of a couple of nanometers) atomic substrates.

Exfoliated Ferrierite-Related Unilamellar Nanosheets in Solution and Their Use for Preparation of Mixed Zeolite Hierarchical Structures.

Direct exfoliation of layered zeolites into solutions of monolayers has remained unresolved since the 1990s. Recently, zeolite MCM-56 with the MWW topology (layers denoted mww) has been exfoliated directly in high yield by soft-chemical treatment with tetrabutylammonium hydroxide (TBAOH). This has enabled preparation of zeolite-based hierarchical materials and intimate composites with other active species that are unimaginable via the conventional solid-state routes. The extension to other frameworks, which provides broader benefits, diversified activity, and functionality, is not routine and requires finding suitable synthesis formulations, viz. compositions and conditions, of the layered zeolites themselves. This article reports exfoliation and characterization of layers with ferrierite-related structure, denoted bifer, having rectangular lattice constants like those of the FER and CDO zeolites, and thickness of approximately 2 nm, which is twice that of the so-called fer layer. Several techniques were combined to prove the exfoliation, supported by simulations: AFM; in-plane, in situ, and powder X-ray diffraction; TEM; and SAED. The results confirmed (i) the structure and crystallinity of the layers without unequivocal differentiation between the FER and CDO topologies and (ii) uniform thickness in solution (monodispersity), ruling out significant multilayered particles and other impurities. The bifer layers are zeolitic with Brønsted acid sites, demonstrated catalytic activity in the alkylation of mesitylene with benzyl alcohol, and intralayer pores visible in TEM. The practical benefits are demonstrated by the preparation of unprecedented intimately mixed zeolite composites with the mww, with activity greater than the sum of the components despite high content of inert silica as pillars.

Fingerprinting diverse nanoporous materials for optimal hydrogen storage conditions using meta-learning.

Adsorptive hydrogen storage is a desirable technology for fuel cell vehicles, and efficiently identifying the optimal storage temperature requires modeling hydrogen loading as a continuous function of pressure and temperature. Using data obtained from high-throughput Monte Carlo simulations for zeolites, metal-organic frameworks, and hyper-cross-linked polymers, we develop a meta-learning model that jointly predicts the adsorption loading for multiple materials over wide ranges of pressure and temperature. Meta-learning gives higher accuracy and improved generalization compared to fitting a model separately to each material and allows us to identify the optimal hydrogen storage temperature with the highest working capacity for a given pressure difference. Materials with high optimal temperatures are found in close proximity in the fingerprint space and exhibit high isosteric heats of adsorption. Our method and results provide new guidelines toward the design of hydrogen storage materials and a new route to incorporate machine learning into high-throughput materials discovery.

Adsorption-Based Separation of Near-Azeotropic Mixtures-A Challenging Example for High-Throughput Development of Adsorbents.

Adsorption of gas mixtures is central to adsorption-based gas separations, and the number of adsorbate mixture/adsorbent systems that exist is staggering. Because examples of machine learning (ML) models predicting single-component adsorption of arbitrary molecules in large libraries of crystalline adsorbents have been developed, it is interesting to determine whether these models can accurately predict mixture adsorption. Here, we use molecular simulations to generate mixture adsorption data with a set of 12 near-azeotropic molecules in a diverse set of MOFs. These data provide a challenging example for any method to rapidly predict mixture adsorption in MOFs. We combine a previous ML single-component isotherm model with ideal adsorbed solution theory (IAST) to make predictions that can be compared directly with molecular simulation data for these adsorbed mixtures. This combination of ML and IAST illustrates the scope that is available with these methods, but the accuracy of the resulting predictions is disappointing. By examining the same examples with IAST based on minimal molecular simulation data for single-component isotherms, we show that having an accurate description of adsorption in the dilute loading limit is critical to being able to accurately predict mixture adsorption. This observation points to a useful direction for future work developing robust ML models of adsorption isotherms for diverse collections of molecules and adsorbents.