Graphene and graphene oxide (GO), as wonder materials, have penetrated nearly every field of research. One of their most attractive features is the functionality and assembly of graphene or GO, in ...which they can be considered to be chemically functionalized building blocks for creating unconventional porous graphene materials (PGMs) that not only combine the merits of both porous materials and graphene, but also have major advantages over other porous carbons for specific applications. The chemistry and approaches for functionalizing graphene and GO are first introduced, and typical procedures for pore creation (e.g., in‐plane pores, 2D laminar pores, and 3D interconnected pore assemblies), self‐assembly, and tailoring mechanisms for PGMs to highlight the significance of precise control over the pore morphology and pore size are summarized. Because of their unique pore structures, with different morphologies and intriguing properties, PGMs serve as key components in a variety of applications such as energy storage, electrocatalysis, and molecular separation. Finally, the challenges relating to PGMs from the understanding of chemical self‐assembly to specific applications are discussed, and promising solutions on how to tackle them are presented. This provides an insightful outlook for the future development of the chemistry and applications of PGMs.
Recent advances in the chemistry of graphene and porous graphene materials, including surface chemistry, interface chemistry, assembly chemistry, and functionalization chemistry, and their potential applications are reviewed. Additionally, their porous structure‐performance relationships for energy storage and conversion, electrocatalysis, and molecular separation are summarized.
Abstract
Ambient sunlight-driven CO
2
methanation cannot be realized due to the temperature being less than 80 °C upon irradiation with dispersed solar energy. In this work, a selective light ...absorber was used to construct a photothermal system to generate a high temperature (up to 288 °C) under weak solar irradiation (1 kW m
−2
), and this temperature is three times higher than that in traditional photothermal catalysis systems. Moreover, ultrathin amorphous Y
2
O
3
nanosheets with confined single nickel atoms (SA Ni/Y
2
O
3
) were synthesized, and they exhibited superior CO
2
methanation activity. As a result, 80% CO
2
conversion efficiency and a CH
4
production rate of 7.5 L m
−2
h
−1
were achieved through SA Ni/Y
2
O
3
under solar irradiation (from 0.52 to 0.7 kW m
−2
) when assisted by a selective light absorber, demonstrating that this system can serve as a platform for directly harnessing dispersed solar energy to convert CO
2
to valuable chemicals.
Cu-based nanocatalysts are the cornerstone of various industrial catalytic processes. Synergistically strengthening the catalytic stability and activity of Cu-based nanocatalysts is an ongoing ...challenge. Herein, the high-entropy principle is applied to modify the structure of Cu-based nanocatalysts, and a PVP templated method is invented for generally synthesizing six-eleven dissimilar elements as high-entropy two-dimensional (2D) materials. Taking 2D Cu
Zn
Al
Ce
Zr
O
as an example, the high-entropy structure not only enhances the sintering resistance from 400 °C to 800 °C but also improves its CO
hydrogenation activity to a pure CO production rate of 417.2 mmol g
h
at 500 °C, 4 times higher than that of reported advanced catalysts. When 2D Cu
Zn
Al
Ce
Zr
O
are applied to the photothermal CO
hydrogenation, it exhibits a record photochemical energy conversion efficiency of 36.2%, with a CO generation rate of 248.5 mmol g
h
and 571 L of CO yield under ambient sunlight irradiation. The high-entropy 2D materials provide a new route to simultaneously achieve catalytic stability and activity, greatly expanding the application boundaries of photothermal catalysis.
Solar-heating catalysis has the potential to realize zero artificial energy consumption, which is restricted by the low ambient solar heating temperatures of photothermal materials. Here, we propose ...the concept of using heterostructures of black photothermal materials (such as Bi
Te
) and infrared insulating materials (Cu) to elevate solar heating temperatures. Consequently, the heterostructure of Bi
Te
and Cu (Bi
Te
/Cu) increases the 1 sun-heating temperature of Bi
Te
from 93 °C to 317 °C by achieving the synergy of 89% solar absorption and 5% infrared radiation. This strategy is applicable for various black photothermal materials to raise the 1 sun-heating temperatures of Ti
O
, Cu
Se, and Cu
S to 295 °C, 271 °C, and 248 °C, respectively. The Bi
Te
/Cu-based device is able to heat CuO
/ZnO/Al
O
nanosheets to 305 °C under 1 sun irradiation, and this system shows a 1 sun-driven hydrogen production rate of 310 mmol g
h
from methanol and water, at least 6 times greater than that of all solar-driven systems to date, with 30.1% solar-to-hydrogen efficiency and 20-day operating stability. Furthermore, this system is enlarged to 6 m
to generate 23.27 m
/day of hydrogen under outdoor sunlight irradiation in the spring, revealing its potential for industrial manufacture.
Utilizing and reducing carbon dioxide is a key target in the fight against global warming. The photocatalytic performance of bulk graphitic carbon nitride (g-C3N4) is usually limited by its low ...surface area and rapid charge carrier recombination. To develop g-C3N4 more suitable for photocatalysis, researchers have to enlarge its surface area and accelerate the charge carrier separation. In this work, novel hybrid graphitic carbon nitride and carbon (H-g-C3N4/C) composites with various carbon contents have been developed for the first time by a facile one-step pyrolysis method using melamine and natural soybean oil as precursors. The effect of carbon content on the structure of H-g-C3N4/C composites and the catalytic activity for the photoreduction of CO2 with H2O were investigated. The results indicated that the introduction of carbon component can effectively improve the textural properties and electronic conductivity of the composites, which exhibited imporved photocatalytic activity for the reduction of CO2 with H2O in comparison with bulk g-C3N4. The highest CO and CH4 yield of 22.60 μmol/g-cat. and 12.5 μmol/g-cat., respectively, were acquired on the H-g-C3N4/C-6 catalyst with the carbon content of 3.77 wt % under 9 h simulated solar irradiation, which were more than twice as high as that of bulk g-C3N4. The remarkably increased photocatalytic performance arises from the synergistic effect of hybrid carbon and g-C3N4.
Single-atom catalysts (SACs) supported on two-dimensional (2D) materials are highly attractive for maximizing their catalytic activity. However, graphene based SACs are primarily bonded with nitrogen ...and carbon sites, resulting in poor performance for the oxygen evolution reaction (OER). Herein, we develop a general bimetal-ion adsorption strategy for the synthesis of individually dispersed Ni SACs anchored on the oxygenated sites of ultrathin reduced graphene oxide as efficient OER electrocatalysts. The resultant Ni SACs for OER in alkaline electrolyte exhibit a highly stable overpotential of 328 mV at the current density of 10 mA cm−2, and Tafel slope of 84 mV dec−1 together with long-term durability and negligible degradation for 50 h, which is greatly outperform its counterparts of nitrogen bonded Ni SACs (564 mV, 364 mV dec−1) and Ni(OH)2 nanoparticles anchored on graphene (450 mV, 142 mV dec−1), and most reported Ni based OER electrocatalysts. Furthermore, the extended X-ray absorption fine structure at the Ni K-edge and theoretical simulation reveal that the nickel-oxygen coordination significantly boost OER performance. Therefore, this work will open numerous opportunities for creating novel-type 2D SACs via oxygen–metal bonding as highly robust OER catalysts.
A general bimetal-ion adsorption strategy was successfully developed to synthesize the Ni single atoms anchored on the oxygenated sites of graphene as efficient OER electrocatalysts, which exhibited overpotential of 328 mV and Tafel slope of 84 mV dec−1. Display omitted
Abstract
This paper reports the estimated stellar parameters of 1153 Kepler red giant branch stars determined with asteroseismic modeling. We use radial-mode oscillation frequencies, gravity-mode ...period spacings, Gaia luminosities, and spectroscopic data to characterize these stars. Compared with previous studies, we find that the two additional observed constraints, i.e., the gravity-mode period spacing and luminosity, significantly improve the precision of fundamental stellar parameters. The typical uncertainties are 2.9% for the mass, 11% for the age, 1.0% for the radius, 0.0039 dex for the surface gravity, and 0.5% for the helium core mass, making this the best-characterized large sample of red giant stars available to date. With better characterizations for these red giants, we recalibrate the seismic scaling relations and study the surface term on the red giant branch. We confirm that the surface term depends on the surface gravity and effective temperature, but there is no significant correlation with metallicity.
Single‐atom catalysts (SACs) are efficient for maximizing electrocatalytic activity, but have unsatisfactory activity for the oxygen evolution reaction (OER). Herein, the NaCl template synthesis of ...individual nickel (Ni) SACs is reported, bonded to oxygen sites on graphene‐like carbon (denoted as Ni‐O‐G SACs) with superior activity and stability for OER. A variety of characterizations unveil that the Ni‐O‐G SACs present 3D porous framework constructed by ultrathin graphene sheets, single Ni atoms, coordinating nickel atoms to oxygen. Consequently, the catalysts are active and robust for OER with extremely low overpotential of 224 mV at current density of 10 mA cm−2, 42 mV dec−1 Tafel slope, oxygen production turn over frequency of 1.44 S−1 at 300 mV, and long‐term durability without significant degradation for 50 h at exceptionally high current of 115 mA cm−1, outperforming the state‐of‐the‐art OER SACs. A theoretical simulation further reveals that the bonding between single nickel and oxygen sites results in the extraordinary boosting of OER performance of Ni‐O‐G SACs. Therefore, this work opens numerous opportunities for creating unconventional SACs via metal–oxygen bonding.
Nickel single‐atom catalysts bonded to oxygen sites on graphene‐like carbon nanosheets are synthesized as extraordinarily active and durable electrocatalysts for the oxygen evolution reaction, showing the oxygen production turn over frequency of 1.44 S−1 at 300 mV, and low overpotential of 224 mV at current density of 10 mA cm−2.
We propose a multithreshold change plane regression model which naturally partitions the observed subjects into subgroups with different covariate effects. The underlying grouping variable is a ...linear function of observed covariates and thus multiple thresholds produce change planes in the covariate space. We contribute a novel two‐stage estimation approach to determine the number of subgroups, the location of thresholds, and all other regression parameters. In the first stage we adopt a group selection principle to consistently identify the number of subgroups, while in the second stage change point locations and model parameter estimates are refined by a penalized induced smoothing technique. Our procedure allows sparse solutions for relatively moderate‐ or high‐dimensional covariates. We further establish the asymptotic properties of our proposed estimators under appropriate technical conditions. We evaluate the performance of the proposed methods by simulation studies and provide illustrations using two medical data examples. Our proposal for subgroup identification may lead to an immediate application in personalized medicine.
Thresholding variable plays a crucial role in subgroup identification for personalized medicine. Most existing partitioning methods split the sample based on one predictor variable. In this paper, we ...consider setting the splitting rule from a combination of multivariate predictors, such as the latent factors, principle components, and weighted sum of predictors. Such a subgrouping method may lead to more meaningful partitioning of the population than using a single variable. In addition, our method is based on a change point regression model and thus yields straight forward model‐based prediction results. After choosing a particular thresholding variable form, we apply a two‐stage multiple change point detection method to determine the subgroups and estimate the regression parameters. We show that our approach can produce two or more subgroups from the multiple change points and identify the true grouping with high probability. In addition, our estimation results enjoy oracle properties. We design a simulation study to compare performances of our proposed and existing methods and apply them to analyze data sets from a Scleroderma trial and a breast cancer study.
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