Sketch2Human: Deep Human Generation with Disentangled Geometry and Appearance Constraints.

Geometry- and appearance-controlled full-body human image generation is an interesting but challenging task. Existing solutions are either unconditional or dependent on coarse conditions (e.g., pose, text), thus lacking explicit geometry and appearance control of body and garment. Sketching offers such editing ability and has been adopted in various sketch-based face generation and editing solutions. However, directly adapting sketch-based face generation to full-body generation often fails to produce high-fidelity and diverse results due to the high complexity and diversity in the pose, body shape, and garment shape and texture. Recent geometrically controllable diffusion-based methods mainly rely on prompts to generate appearance. It is hard to balance the realism and the faithfulness of their results to the sketch when the input is coarse. This work presents Sketch2Human, the first system for controllable full-body human image generation guided by a semantic sketch (for geometry control) and a reference image (for appearance control). Our solution is based on the latent space of StyleGAN-Human with inverted geometry and appearance latent codes as input. Specifically, we present a sketch encoder trained with a large synthetic dataset sampled from StyleGAN-Human's latent space and directly supervised by sketches rather than real images. Considering the entangled information of partial geometry and texture in StyleGAN-Human and the absence of disentangled datasets, we design a novel training scheme that creates geometry-preserved and appearance-transferred training data to tune a generator to achieve disentangled geometry and appearance control. Although our method is trained with synthetic data, it can also handle hand-drawn sketches. Qualitative and quantitative evaluations demonstrate the superior performance of our method to state-of-the-art methods.

Mg-MOF-74 Derived Defective Framework for Hydrogen Storage at Above-Ambient Temperature Assisted by Pt Catalyst.

Metal-organic frameworks (MOFs) are promising candidates for room-temperature hydrogen storage materials after modification, thanks to their ability to chemisorb hydrogen. However, the hydrogen adsorption strength of these modified MOFs remains insufficient to meet the capacity and safety requirements of hydrogen storage systems. To address this challenge, a highly defective framework material known as de-MgMOF is prepared by gently annealing Mg-MOF-74. This material retains some of the crystal properties of the original Mg-MOF-74 and exhibits exceptional hydrogen storage capacity at above-ambient temperatures. The MgO5 knots around linker vacancies in de-MgMOF can adsorb a significant amount of dissociated and nondissociated hydrogen, with adsorption enthalpies ranging from -22.7 to -43.6 kJ mol-1, indicating a strong chemisorption interaction. By leveraging a spillover catalyst of Pt, the material achieves a reversible hydrogen storage capacity of 2.55 wt.% at 160 °C and 81 bar. Additionally, this material offers rapid hydrogen uptake/release, stable cycling, and convenient storage capabilities. A comprehensive techno-economic analysis demonstrates that this material outperforms many other hydrogen storage materials at the system level for on-board applications.

Adsorption Performance and Mechanisms of Tetracycline on Clay Minerals in Estuaries and Nearby Coastal Areas.

Clay minerals in sediments have strong adsorption capacities for pollutants, but their role in the distribution of antibiotics in estuaries and nearby coastal areas is unclear. We evaluated the clay mineral montmorillonite (SWy-2) adsorption capacity for tetracycline (TC). We assessed the adsorption capacity of SWy-2 for TC by measuring the removal percentage of 30 mg/L TC over time. The effects of pH and ionic strength on the TC adsorption onto SWy-2 were investigated. We analyzed the kinetics of TC adsorption using a pseudo-second-order model and determined the adsorption isotherm using the Langmuir equation. SWy-2 particles were characterized using zeta potential, Fourier transform infrared (FTIR), and X-ray diffraction (XRD) analyses before and after TC adsorption. The removal percentage of 30 mg/L TC by SWy-2 reached 70.76% within 0.25 h and gradually increased to 78.64% at 6 h. TC adsorption was influenced by pH and ionic strength, where low pH enhanced and high ionic strength reduced the adsorption. The kinetics of TC adsorption followed a pseudo-second-order model, and the adsorption isotherm adhered to the Langmuir equation. The saturated adsorption capacity (qmax) of SWy-2 for TC was 227.27 mg/g. Zeta potential, FTIR, and XRD analyses confirmed that electrostatic interactions and chemical bonds played a significant role in the TC adsorption by SWy-2. SWy-2 clay mineral exhibits a substantial adsorption capacity for TC, indicating its potential as an effective sorbent to mitigate antibiotic contamination in estuaries and nearby coastal areas. The observed effects of pH and ionic strength on TC adsorption have implications for the environmental fate and transport of antibiotics. The pseudo-second-order kinetic model and Langmuir isotherm equation provide valuable insights into the adsorption behavior and capacity of TC on SWy-2. Characterization analyses support the involvement of electrostatic interactions and chemical bonds in the SWy-2-TC adsorption mechanism.

Revealing Distance-Dependent Synergy between MnCo2O4 and Co-N-C in Boosting the Oxygen Reduction Reaction.

Synergistic effects have been applied to a variety of hybrid electrocatalysts to improve their activity and selectivity. Understanding the synergistic mechanism is crucial for the rational design of these types of catalysts. Here, we synthesize a MnCo2O4/Co-N-C hybrid electrocatalyst for the oxygen reduction reaction (ORR) and systematically investigate the synergy between MnCo2O4 nanoparticles and Co-N-C support. Theoretical simulations reveal that the synergy is closely related to the distance between active sites. For a pair of remote active sites, the ORR proceeds through the known 2e- + 2e- relay catalysis while the direct 4e- ORR occurs on a pair of adjacent active sites. Therefore, the formation of the undesired byproduct (H2O2) is inhibited at the interface region between MnCo2O4 and Co-N-C. This synergistic effect is further verified on an anion-exchange membrane fuel cell. The findings deepen the understanding of synergistic catalysis and will provide guidance for the rational design of hybrid electrocatalysts.

Single-crystal ZrCo nanoparticle for advanced hydrogen and H-isotope storage.

Hydrogen-isotope storage materials are essential for the controlled nuclear fusion. However, the currently used smelting-ZrCo alloy suffers from rapid degradation of performance due to severe disproportionation. Here, we reveal a defect-derived disproportionation mechanism and report a nano-single-crystal strategy to solve ZrCo's problems. Single-crystal nano-ZrCo is synthesized by a wet-chemistry method and exhibits excellent comprehensive hydrogen-isotope storage performances, including ultrafast uptake/release kinetics, high anti-disproportionation ability, and stable cycling, far superior to conventional smelting-ZrCo. Especially, a further incorporation of Ti into nano-ZrCo can almost suppress the disproportionation reaction. Moreover, a mathematical relationship between dehydrogenation temperature and ZrCo particle size is established. Additionally, a microwave method capable of nondestructively detecting the hydrogen storage state of ZrCo is developed. The proposed disproportionation mechanism and anti-disproportionation strategy will be instructive for other materials with similar problems.

ReenactArtFace: Artistic Face Image Reenactment.

Large-scale datasets and deep generative models have enabled impressive progress in human face reenactment. Existing solutions for face reenactment have focused on processing real face images through facial landmarks by generative models. Different from real human faces, artistic human faces (e.g., those in paintings, cartoons, etc.) often involve exaggerated shapes and various textures. Therefore, directly applying existing solutions to artistic faces often fails to preserve the characteristics of the original artistic faces (e.g., face identity and decorative lines along face contours) due to the domain gap between real and artistic faces. To address these issues, we present ReenactArtFace, the first effective solution for transferring the poses and expressions from human videos to various artistic face images. We achieve artistic face reenactment in a coarse-to-fine manner. First, we perform 3D artistic face reconstruction, which reconstructs a textured 3D artistic face through a 3D morphable model (3DMM) and a 2D parsing map from an input artistic image. The 3DMM can not only rig the expressions better than facial landmarks but also render images under different poses/expressions as coarse reenactment results robustly. However, these coarse results suffer from self-occlusions and lack contour lines. Second, we thus perform artistic face refinement by using a personalized conditional adversarial generative model (cGAN) fine-tuned on the input artistic image and the coarse reenactment results. For high-quality refinement, we propose a contour loss to supervise the cGAN to faithfully synthesize contour lines. Quantitative and qualitative experiments demonstrate that our method achieves better results than the existing solutions.

Ultrathin Nanotube Structure for Mass-Efficient and Durable Oxygen Reduction Reaction Catalysts in PEM Fuel Cells.

It remains a challenge for platinum-based oxygen reduction reaction catalysts to simultaneously possess high mass activity and high durability in proton-exchange-membrane fuel cells. Herein, we report ultrathin holey nanotube (UHT)-structured Pt-M (M = Ni, Co) alloy catalysts that achieve unprecedented comprehensive performance. The nanotubes have ultrathin walls of 2-3 nm and construct self-supporting network-like catalyst layers with thicknesses of less than 1 µm, which have efficient mass transfer and 100% surface exposure, thus enabling high utilization of Pt atoms. Combined with the high intrinsic activity produced by the alloying effect, the catalysts achieve high mass activity. Moreover, the nanotube structure not only avoids the agglomeration problem of nanoparticles, but the low curvature of the tube wall also gives UHT a low surface energy (less than 1/3 of that of the same size nanoparticle), so UHT is more resistant to the Ostwald ripening and is stable. For the first time, the U.S. DOE mass activity target and dual durability targets for load and start-stop cycles are achieved on one catalyst. This study provides an effective structural strategy for the preparation of electrocatalysts with high atomic efficiency and excellent durability.

Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation of Indoor Scenes.

In recent years, sparse voxel-based methods have become the state-of-the-arts for 3D semantic segmentation of indoor scenes, thanks to the powerful 3D CNNs. Nevertheless, being oblivious to the underlying geometry, voxel-based methods suffer from ambiguous features on spatially close objects and struggle with handling complex and irregular geometries due to the lack of geodesic information. In view of this, we present Voxel-Mesh Network (VMNet), a novel 3D deep architecture that operates on the voxel and mesh representations leveraging both the Euclidean and geodesic information. Intuitively, the Euclidean information extracted from voxels can offer contextual cues representing interactions between nearby objects, while the geodesic information extracted from meshes can help separate objects that are spatially close but have disconnected surfaces. To incorporate such information from the two domains, we design an intra-domain attentive module for effective feature aggregation and an inter-domain attentive module for adaptive feature fusion. Experimental results validate the effectiveness of VMNet: specifically, on the challenging ScanNet dataset for large-scale segmentation of indoor scenes, it outperforms the state-of-the-art SparseConvNet and MinkowskiNet (74.6% vs 72.5% and 73.6% in mIoU) with a simpler network structure (17M vs 30M and 38M parameters).

Iron atom-cluster interactions increase activity and improve durability in Fe-N-C fuel cells.

Simultaneously increasing the activity and stability of the single-atom active sites of M-N-C catalysts is critical but remains a great challenge. Here, we report an Fe-N-C catalyst with nitrogen-coordinated iron clusters and closely surrounding Fe-N4 active sites for oxygen reduction reaction in acidic fuel cells. A strong electronic interaction is built between iron clusters and satellite Fe-N4 due to unblocked electron transfer pathways and very short interacting distances. The iron clusters optimize the adsorption strength of oxygen reduction intermediates on Fe-N4 and also shorten the bond amplitude of Fe-N4 with incoherent vibrations. As a result, both the activity and stability of Fe-N4 sites are increased by about 60% in terms of turnover frequency and demetalation resistance. This work shows the great potential of strong electronic interactions between multiphase metal species for improvements of single-atom catalysts.

Electronic Mechanism of Martensitic Transformation in Nb-doped NiTi Alloys: A First-Principles Investigation.

The effect of Nb on the crystal structures and electronic mechanism of martensitic transformation in Ni50Ti50-x Nb x alloys is investigated by first principles. The lattice parameters, the formation energy, the middle eigenvalue of the transformation stretch tensor (λ2), and the energy difference between the parent and martensite (ΔE) as a function of Nb content x (x = 0, 2.08, 6.25, 8.33, 10.42, 12.5, 18.75) are calculated. Lattice parameters increase with the increase of Nb content. The formation energies of the parent B2 phase, martensite orthorhombic B19, and monoclinic B19' increase with the increase of Nb content. It is also found that at ≤10.42 at. % Nb, the martensite stable phase is monoclinic structure B19'; at >10.42 at. % Nb, the orthorhombic crystal structure B19 is formed. The energy difference between the parent and martensite means that the transformation temperature decreases with increasing Nb concentration at Nb ≤ 10.42 at. % and increases at >10.42 at. % Nb. The λ2 of the NiTiNb alloys have the same value of about 0.95 with low Nb content. Furthermore, the electronic structure mechanisms behind the martensitic transformations are discussed in detail based on the density of states.

High-Entropy Atomic Layers of Transition-Metal Carbides (MXenes).

High-entropy materials (HEMs) have great potential for energy storage and conversion due to their diverse compositions, and unexpected physical and chemical features. However, high-entropy atomic layers with fully exposed active sites are difficult to synthesize since their phases are easily segregated. Here, it is demonstrated that high-entropy atomic layers of transition-metal carbide (HE-MXene) can be produced via the selective etching of novel high-entropy MAX (also termed Mn +1 AXn (n = 1, 2, 3), where M represents an early transition-metal element, A is an element mainly from groups 13-16, and X stands for C and/or N) phase (HE-MAX) (Ti1/5 V1/5 Zr1/5 Nb1/5 Ta1/5 )2 AlC, in which the five transition-metal species are homogeneously dispersed into one MX slab due to their solid-solution feature, giving rise to a stable transition-metal carbide in the atomic layers owing to the high molar configurational entropy and correspondingly low Gibbs free energy. Additionally, the resultant high-entropy MXene with distinct lattice distortions leads to high mechanical strain into the atomic layers. Moreover, the mechanical strain can efficiently guide the nucleation and uniform growth of dendrite-free lithium on HE-MXene, achieving a long cycling stability of up to 1200 h and good deep stripping-plating levels of up to 20 mAh cm-2 .

Selective Etching Quaternary MAX Phase toward Single Atom Copper Immobilized MXene (Ti3C2Clx) for Efficient CO2 Electroreduction to Methanol.

Single atom catalysts possess attractive electrocatalytic activities for various chemical reactions owing to their favorable geometric and electronic structures compared to the bulk counterparts. Herein, we demonstrate an efficient approach to producing single atom copper immobilized MXene for electrocatalytic CO2 reduction to methanol via selective etching of hybrid A layers (Al and Cu) in quaternary MAX phases (Ti3(Al1-xCux)C2) due to the different saturated vapor pressures of Al- and Cu-containing products. After selective etching of Al in the hybrid A layers, Cu atoms are well-preserved and simultaneously immobilized onto the resultant MXene with dominant surface functional group (Clx) on the outmost Ti layers (denoted as Ti3C2Clx) via Cu-O bonds. Consequently, the as-prepared single atom Cu catalyst exhibits a high Faradaic efficiency value of 59.1% to produce CH3OH and shows good electrocatalytic stability. On the basis of synchrotron-based X-ray absorption spectroscopy analysis and density functional theory calculations, the single atom Cu with unsaturated electronic structure (Cuδ+, 0 < δ < 2) delivers a low energy barrier for the rate-determining step (conversion of HCOOH* to absorbed CHO* intermediate), which is responsible for the efficient electrocatalytic CO2 reduction to CH3OH.

Hydrogen storage in incompletely etched multilayer Ti2CTx at room temperature.

Hydrogen storage materials are the key to hydrogen energy utilization. However, current materials can hardly meet the storage capacity and/or operability requirements of practical applications. Here we report an advancement in hydrogen storage performance and related mechanism based on a hydrofluoric acid incompletely etched MXene, namely, a multilayered Ti2CTx (T is a functional group) stack that shows an unprecedented hydrogen uptake of 8.8 wt% at room temperature and 60 bar H2. Even under completely ambient conditions (25 °C, 1 bar air), Ti2CTx is still able to retain ~4 wt% hydrogen. The hydrogen storage is stable and reversible in the material, and the hydrogen release is controllable by pressure and temperature below 95 °C. The storage mechanism is deduced to be a nanopump-effect-assisted weak chemisorption in the sub-nanoscale interlayer space of the material. Such a storage approach provides a promising strategy for designing practical hydrogen storage materials.

Rational prediction of multifunctional bilayer single atom catalysts for the hydrogen evolution, oxygen evolution and oxygen reduction reactions.

Bimetallic atom catalysts (BACs), which can exhibit remarkable catalytic performance compared with single atom catalysts (SACs) due to their higher metal loading and the synergy between two metal atoms, have attracted great attention in research. Herein, by means of density functional theory calculations, novel BACs with a bilayer structure composed of monolayers FeN4 (Fe and nitrogen co-doped graphene) and MN4 (Fe/M, M represents transition metal atoms) as electrocatalysts for the hydrogen evolution reaction (HER), oxygen reduction reaction (ORR), and oxygen evolution reaction (OER) are investigated. Among these bilayer SACs, a series of highly efficient monofunctional, bifunctional, and even trifunctional electrocatalysts have been screened. For example, the overpotentials for the HER, ORR, and OER can reach -0.02 (Fe/Cu), 0.31 (Fe/Hg), and 0.27 V (Fe/Hf), respectively; Fe/Hf and Ir/Fe can serve as promising bifunctional catalysts for the ORR/OER and HER/OER, respectively and Fe/Rh is considered as an excellent trifunctional catalyst for the HER, OER, and ORR. This work not only provides a new idea for understanding and optimizing the active sites of BACs, but also proposes a new strategy for designing high-performance multifunctional electrocatalysts for fuel cells and metal-air batteries.

Bimetallic Pairs Supported on Graphene as Efficient Electrocatalysts for Nitrogen Fixation: Search for the Optimal Coordination Atoms.

The electrocatalytic nitrogen reduction reaction (NRR) is a most attractive approach to ammonia synthesis, and the development of catalysts with excellent activity, high NRR selectivity, and long-term durability is crucial but remains a great challenge. Herein, by means of density functional theory calculations, the stability and catalytic performance of anchored bimetals was systematically investigated by pairing different transition-metal atoms (Mo, Cr, Ti, V, Ru, and W) on graphene with different coordination atoms (C, N, O, P, and S) for N2 fixation. By screening the stability, limiting potential, and selectivity of 105 candidates, carbon was found to be the optimal coordination atom for bimetallic pairs, whereas the other four coordination atoms were unsatisfactory owing to either thermodynamically unstable anchor sites for bimetallic pairs (O, P, and S atoms) or relatively low catalytic activity (N atom). Notably, the bimetallic compound of Mo and Ti supported on C-coordinated graphene (MoTi-CG) and TiV-CG were predicted as effective NRR catalysts with the attractive limiting potentials of -0.34 and -0.30 V. Furthermore, the volcano curve between the limiting potential and the adsorption free energy of NH2 * [ΔG(NH2 *)] was revealed, in which a moderate ΔG(NH2 *) was required for high-activity NRR catalysts. This study not only provides a theoretical basis for the rational design of bimetallic compounds anchored on graphene as effective NRR catalysts under ambient conditions but also opens up a new way to accelerate the screening of NRR catalysts.

Martensitic transformation of Ti50(Ni50-xCux) and Ni50(Ti50-xZrx) shape-memory alloys.

Martensitic transformation and phase stability of Ti50(Ni50-xCux) and Ni50(Ti50-xZrx) shape memory alloys are investigated based on density functional theory (DFT). According to the results of formation energy we calculated, upon substitution of Ni by Cu at levels of about 10.4 at.%, Ti50(Ni50-xCux) alloys lose the monoclinic martensite in favor of the orthorhombic martensite structure. The martensite monoclinic B19´ structure of Ni50(Ti50-xZrx) becomes more stable with increasing of the Zr content. The energy difference between austenite and martensite decreases when Cu < 10.4 at.%, and then increases slightly, which suggesting that Cu addition reduces the composition sensitivity of martensitic transformation temperature comparing with binary NiTi alloys. The energy difference decreases slightly firstly when Zr < 10.4 at.% and then increases sharply, which indicates that Zr addition increases martensitic transformation temperature dramatically. Furthermore, a geometric model is used to evaluate the thermal hysteresis. More interestingly, it is found that the lowest thermal hysteresis is achieved at 10.4 at.% for Cu-doped NiTi; whereas the thermal hysteresis increases with increasing of Zr. The electronic structures of austenite phase are also discussed in detail.

Zigzag carbon as efficient and stable oxygen reduction electrocatalyst for proton exchange membrane fuel cells.

Non-precious-metal or metal-free catalysts with stability are desirable but challenging for proton exchange membrane fuel cells. Here we partially unzip a multiwall carbon nanotube to synthesize zigzag-edged graphene nanoribbons with a carbon nanotube backbone for electrocatalysis of oxygen reduction in proton exchange membrane fuel cells. Zigzag carbon exhibits a peak areal power density of 0.161 W cm-2 and a peak mass power density of 520 W g-1, superior to most non-precious-metal electrocatalysts. Notably, the stability of zigzag carbon is improved in comparison with a representative iron-nitrogen-carbon catalyst in a fuel cell with hydrogen/oxygen gases at 0.5 V. Density functional theory calculation coupled with experimentation reveal that a zigzag carbon atom is the most active site for oxygen reduction among several types of carbon defects on graphene nanoribbons in acid electrolyte. This work demonstrates that zigzag carbon is a promising electrocatalyst for low-cost and durable proton exchange membrane fuel cells.

Twin and dislocation mechanisms in tensile W single crystal with temperature change: a molecular dynamics study.

Molecular dynamics simulations are performed to investigate the orientation and temperature dependence of tensile response in single crystal W. It is found that W single crystal exhibits distinct temperature-dependent deformation behaviors along different orientations. With increasing temperature, the yield strain in the [001] orientation increases, while those in [110] and [111] orientations first increase and then decrease. The tensile deformations along orientations close to [001] are found to be dominated by twinning; the nucleation and growth of twins are accomplished through the nucleation and glide of ⅙111 partial dislocations on {112} planes. In contrast, the deformations along orientations close to [110] and [111] are found to be dominated by the slip of ½111 full dislocations, which move in a stay-and-go fashion. Moreover, intermediate deformation behaviors, which may become unstable at high temperatures, are observed for some intervening orientations. The distinct deformation behaviors of W along different orientations are rationalized based on the twinning-antitwinning asymmetry of ⅙111 partial dislocations on {112} planes.

Oxygen vacancy and doping atom effect on electronic structure and optical properties of Cd2SnO4.

The electronic structure and optical properties of oxygen vacancy and La-doped Cd2SnO4 were calculated using the plane-wave-based pseudopotential method based on the density functional theory (DFT) within the generalized gradient approximation (GGA). The formation energy of different oxygen vacancies showed that the VO2 oxygen vacancy was easy to obtain in experiments. The Bader charge analysis is implemented to directly observe the electron transfer and distribution for each atom. The calculated band structures show that when the oxygen vacancy was introduced, the impurity energy level appeared in the band gap. The impurity levels induced by oxygen vacancies were mainly composed of O 2p orbits and a very small amount of Cd 4s orbits. After La doping based on the VO2 oxygen vacancy of Cd2SnO4, the Fermi energy level entered the conduction band and overlapped with the conduction band which increased the conductivity, and the band gap value increased to above 3.0 eV. The optical calculation results showed that the transmittance of the VO2 oxygen vacancy of Cd2SnO4 increased in short wavelength (<600 nm), the reflectivity increased in the infrared region compared with Cd2SnO4, and the transmittance increased to 90% in visible light region after La doping.

Formation of Multiple-Phase Catalysts for the Hydrogen Storage of Mg Nanoparticles by Adding Flowerlike NiS.

In order to enhance the hydrogen storage properties of Mg, flowerlike NiS particles have been successfully prepared by solvothermal reaction method, and are subsequently ball milled with Mg nanoparticles (NPs) to fabricate Mg-5 wt % NiS nanocomposite. The nanocomposite displays Mg/NiS core/shell structure. The NiS shell decomposes into Ni, MgS and Mg2Ni multiple-phases, decorating on the surface of the Mg NPs after the first hydrogen absorption and desorption cycle at 673 K. The Mg-MgS-Mg2Ni-Ni nanocomposite shows enhanced hydrogenation and dehydrogenation rates: it can quickly uptake 3.5 wt % H2 within 10 min at 423 K and release 3.1 wt % H2 within 10 min at 573 K. The apparent hydrogen absorption and desorption activation energies are decreased to 45.45 and 64.71 kJ mol-1. The enhanced sorption kinetics of the nanocomposite is attributed to the synergistic catalytic effects of the in situ formed MgS, Ni and Mg2Ni multiple-phase catalysts during the hydrogenation/dehydrogenation process, the porthole effects for the volume expansion and microstrain of the phase transformation of Mg2Ni and Mg2NiH4 and the reduced hydrogen diffusion distance caused by nanosized Mg. This novel method of in situ producing multiple-phase catalysts gives a new horizon for designing high performance hydrogen storage material.