Broadband Near-Infrared Luminescence in Garnet Y3Ga3MgSiO12: Cr3+ Phosphors.

Broadband near-infrared (NIR) phosphors are the critical component of phosphor converted NIR light-emitting diode (LED) light sources. However, there are still a lack of NIR phosphors with excellent external quantum efficiency (EQE) and thermal stability. Here, we report a highly efficient broadband NIR phosphor Y3Ga3MgSiO12: Cr3+. The optimized phosphor yields an internal quantum efficiency (IQE) and an EQE of 79.9 and 33.7%, respectively. The integrated emission intensity still remains at 84.4% of that at room temperature when heated to 423 K. A broadband NIR LED lamp was made by combining as-prepared phosphor and a blue InGaN LED chip, which shows an output power of 89.8 mW with a photoelectric conversion efficiency of 17.1% driven at 525 mW input power. Our research provides a promising NIR phosphor with high efficiency broadband for the NIR light source.

Understanding the migration mechanism of hydrogen atom from the α-Fe matrix into nano-precipitates via DFT calculations.

The service of high-strength steel suffers from the threat of hydrogen embrittlement and introducing nano-precipitates is an effective avenue to mitigate it. How hydrogen atoms migrate into nano-precipitates is an important question that needs to be clarified. In this study, NEB-based DFT calculations have clearly constructed the energy evolution profiles of the whole process for hydrogen atoms diffusing from α-Fe through the α-Fe/MC (M = V, Ti, Nb) coherent interfaces and finally into the nano-precipitates. The calculation results indicate that a hydrogen atom migrates with difficulty through the α-Fe/MC coherent interfaces and the diffusions in nano-precipitates follow two-step pathways. The C atom vacancy is easier to form in MC nano-precipitates. When introducing a C atom or metallic atom vacancy into the α-Fe/MC interface, the C atom vacancy is the hydrogen trapping site, while the metallic atom vacancy reduces the migration barrier. In addition, once a C atom or metallic atom vacancy is formed in the nano-precipitate, the vacancy will behave as an irreversible trapping site. Finally, electronic structure analyses and distortion energy calculations clearly reveal the effects of the local atomic environment on hydrogen diffusion from α-Fe into nano-precipitates.

Unexpected High-Performance Photocatalytic Hydrogen Evolution in Co@NCNT@ZnIn2 S4 Triggered by Directional Charge Separation and Transfer.

The structural design of photocatalysts is highly related to the separation and transfer of photogenerated carriers, which is essential for the improvement of photocatalytic hydrogen evolution performance. Here, the hybrid photocatalyst M@NCNT@ZIS (M: Fe, Co, Ni; NCNT: nitrogen-doped carbon nanotube; ZIS: ZnIn2 S4 ) with a hierarchical structure is rationally designed and precisely synthesized. The unique hollow structure with a large specific surface area offers abundant reactive sites, thus increasing the adsorption of reactants. Importantly, the properly positioned metal nanoparticles realize the directional charge migration from ZIS to M@NCNT, which significantly improves the efficiency of charge separation. Furthermore, the intimate interface between M@NCNT and ZIS effectively facilitates charge migration by shortening the transfer distance and providing numerous transport channels. As a result, the optimized Co@NCNT@ZIS exhibits a remarkable photocatalytic hydrogen evolution efficiency (43.73 mmol g-1 h-1 ) without Pt as cocatalyst. Experimental characterizations and density functional theory calculations demonstrate that the synergistic effect between hydrogen adsorption and interfacial charge transport is of great significance for improving photocatalytic hydrogen production performance.

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations.

We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.

Effects of seasonal ambient heat stress on expression of microRNAs in the mammary gland of Holstein cows.

This study was conducted to assess the link of miRNA expressions in cow's mammary gland undergoing heat stress. Twelve Holstein cows were allocated either to undergo heat stress (HS) or remain in a thermoneutral environment (non-heat stress, NS), respectively. The experiment with HS cows was carried out in August, and the experiment with NS cows was done in November. After a month, three cows from each group were slaughtered, and mammary gland samples were obtained, and then miRNA were extracted from the samples for later sequencing. From the miRNA-seq, we obtained a total of 124 differentially expressed miRNAs in HS and NS cows' mammary gland. The differentially expressed miRNA could be predicted to influence multiple target genes. The target interleukin-1 (IL-1), which play a role in regulating the function of mammary gland in dairy cows, could be affected by bta-let-7c, bta-let-7e, bta-miR-181d, bta-miR-452, and bta-miR-31. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that mitogen-activated protein kinase (MAPK) pathway plays an important role in the mammary glands of dairy cows and bta-miR-25 and bta-miR-382 may influence MAPK pathway through c-Jun N-terminal kinase (JNK) gene to affect the function of mammary gland in HS cows. In conclusion, this study characterized expression profile of miRNAs in the Holstein cows' mammary gland under summer heat stress or not. We observed miRNA expression during heat stress, which was significantly different from non-heat stress states. A comprehensive analysis of the miRNA's expression will be helpful to further study the link of miRNAs with mechanisms regulating heat stress in the cow mammary gland.

A theoretical study of the effect of a non-aqueous proton donor on electrochemical ammonia synthesis.

Ammonia synthesis is one of the most studied reactions in heterogeneous catalysis. To date, however, electrochemical N2 reduction in aqueous systems has proven to be extremely difficult, mainly due to the competing hydrogen evolution reaction (HER). Recently, it has been shown that transition metal complexes based on molybdenum can reduce N2 to ammonia at room temperature and ambient pressure in a non-aqueous system, with a relatively small amount of hydrogen output. We demonstrate that the non-aqueous proton donor they have chosen, 2,6-lutidinium (LutH+), is a viable substitute for hydronium in the electrochemical process at a solid surface, since this donor can suppress the HER rate. We also show that the presence of LutH+ can selectively stabilize the *NNH intermediate relative to *NH or *NH2via the formation of hydrogen bonds, indicating that the use of non-aqueous solvents can break the scaling relationship between limiting potential and binding energies.

Study of oxygen evolution reaction on amorphous Au13@Ni120P50 nanocluster.

The pursuit of catalysts to promote effective water oxidization to produce oxygen has become a research subject of high priority for water splitting. Here, first-principles calculations are employed to study the water-splitting oxygen evolution reaction (OER) on ∼1.5 nm diameter Au13@Ni120P50 core-shell nanoclusters. Water splitting to produce oxygen proceeds in four intermediate reaction steps (OH*, O*, OOH* and O2). Adsorption configurations and adsorption energies for the species involved in OER on both Au13@Ni120P50 cluster and Ni12P5(001) supported by Au are presented. In addition, thermodynamic free energy diagrams and kinetic potential energy changes are systematically discussed. We show that the third intermediate reaction (O* reacting with H2O to produce OOH*) of the four elementary steps is the reaction-determining step, which accords with previous results. Also, the catalytic performance of OER for Au13@Ni120P50 is better than that for Ni12P5(001) supported by Au in terms of reactive overpotential (0.74 vs. 1.58 V) and kinetic energy barrier (2.18 vs. 3.17 eV). The optimal kinetic pathway for OER is further explored carefully for the Au13@Ni120P50 cluster. The low thermodynamic overpotential and kinetic energy barrier make Au13@Ni120P50 promising for industrial applications as a good OER electrocatalyst candidate.

Size-dependent concentrations of thermal vacancies in solid films.

Solid films are considered as typical model systems to study size effects on thermal vacancy concentration in nanomaterials. By combining the generalized Young-Laplace equation with the chemical potential of vacancies, a strict size-dependent thermodynamic model of vacancies, which includes the surface intrinsic elastic parameters of the eigenstress, Young's modulus and the geometric size of the solid films, was established. The vacancy concentration changes in the film with respect to the bulk value, depending on the geometric size and surface stress sign of the solid films. Atomistic simulations of Au and Pt films verified the developed thermodynamic model. These results provide physical insights into the size-dependent thermal vacancy concentration in nanomaterials.

A materials terminology knowledge graph automatically constructed from text corpus.

A scalable, reusable, and broad-coverage unified material knowledge representation shows its importance and will bring great benefits to data sharing among materials communities. A knowledge graph (KG) for materials terminology, which is a formal collection of term entities and relationships, is conceptually important to achieve this goal. In this work, we propose a KG for materials terminology, named Materials Genome Engineering Database Knowledge Graph (MGED-KG), which is automatically constructed from text corpus via natural language processing. MGED-KG is the most comprehensive KG for materials terminology in both Chinese and English languages, consisting of 8,660 terms and their explanations. It encompasses 11 principal categories, such as Metals, Composites, Nanomaterials, each with two or three levels of subcategories, resulting in a total of 235 distinct category labels. For further application, a knowledge web system based on MGED-KG is developed and shows its great power in improving data sharing efficiency from the aspects of query expansion, term, and data recommendation.

Effect of Mo Content on Hydrogen Evolution Reaction of 1400 MPa-Grade High-Strength Bolt Steel.

The effect of Mo content of 1400 MPa-grade high-strength bolt steel on hydrogen diffusion behavior and the hydrogen evolution reaction were studied using a hydrogen permeation experiment, potentiodynamic polarization tests, thermal desorption spectroscopy, and the first-principle calculation. Two 1400 MPa-grade high-strength bolt steels with different Mo content were used. Based on the potentiodynamic polarization tests, both steels' electrochemical behavior was similar in the test range. The hydrogen permeation experiment showed that the process of hydrogen adsorption and absorption was significantly promoted, and hydrogen desorption and recombination were slightly promoted, with the Mo content increasing from 0.70 to 1.09 wt%. The thermal desorption spectroscopy showed the overall reaction of hydrogen permeation and evolution. The increasing Mo content facilitated hydrogen entry behavior and increased the hydrogen content. According to the first-principle calculation and the density functional theory, this phenomenon is induced by the stronger bonding ability of Mo-H than Fe-H. This work could guide the design of 1400 MPa-grade high-strength bolt steel.

Spectrally tunable near-infrared photoluminescence in MP3O9:Cr3+ (M = Al, Ga, In) phosphate phosphors.

Modulation of the octahedral crystal field environment of Cr3+ is an effective approach to achieve tunable emission. Here, we prepared a series of broadband MP3O9:Cr3+ (M = Al, Ga, In) near-infrared (NIR) phosphors, and cubic AlP3O9:Cr3+ (APO-c:Cr3+) and monoclinic AlP3O9:Cr3+ (APO-m:Cr3+) phosphors were prepared by controlling the synthesis temperature. The emission wavelength was tuned from 787 nm for APO-c:Cr3+ to 894 nm for monoclinic InP3O9:Cr3+ (IPO:Cr3+) by regulating the M ion and reducing the crystal field intensity. Excitingly, the MP3O9:Cr3+ (M = Al, Ga, In) family shows excellent thermal stability; the emission intensity of APO-c:Cr3+, APO-m:Cr3+ and monoclinic GaP3O9:Cr3+ (GPO:Cr3+) can still maintain 95.6%, 86% and 86% of that at room temperature when heating to 423 K, respectively. An NIR LED device was prepared by incorporating GPO:Cr3+ and a blue light LED, demonstrating the potential application in night vision and non-destructive testing.

Effects of rumen-protective γ-aminobutyric acid additive on lactation performance and serum biochemistry in heat-stressed cows.

In the context of global warming, heat stress has become one of the major stress factors limiting dairy cattle production. Although many methods have been explored to help cows mitigate the negative effects of heat stress during the hot summer months, maintaining the performance of high-yielding cows under heat stress is still a great challenge. The aim of this trial was to investigate the effect of RP-GABA in the diet on milk yield, milk composition and serum biochemical parameters in heat-stressed cows. Twenty Chinese Holstein cows in early lactation (51.00 ± 4.92 kg milk/d, 71 ± 10.94 d in milk and 2.68 ± 0.73 parities) were included in this experiment and randomly divided into four groups (n = 5/group). The four experimental groups consisted of one control group (0 g RP-GABA/d) and three treatment groups, given 5, 7.5 and 10 g RP-GABA/d of dry matter (DM) per cow, respectively. The results showed that supplementing high-yielding cows with 10 g/d of RP-GABA improved milk protein production but had no effect on the improvement of other production performance, the alleviation of heat stress in cows, or the improvement of immune function and antioxidant capacity. Ultimately, we conclude that the supplementation of 10 g/d RP-GABA to heat-stressed, high-yielding dairy cows can provide a degree of performance enhancement. Furthermore, our study provides some reference for nutritional improvement measures for summer heat stress in dairy cows, especially high-yielding cows.

In situ fabrication of MIL-68(In)@ZnIn2S4 heterojunction for enhanced photocatalytic hydrogen production.

Metal-organic frameworks (MOFs), as a class of semiconductor-like materials, are widely used in photocatalysis. However, the limited visible light absorption and poor charge separation efficiency are the main challenges restricting their photocatalytic performance. Herein, the type II heterojunction MIL-68(In)@ZIS was successfully fabricated by in situ growth of ZnIn2S4 (ZIS) on the surface of a representative MOF, i.e. MIL-68(In). After composition optimization, MIL-68(In)-20@ZIS shows an extraordinary photocatalytic hydrogen production efficiency of 9.09 mmol g-1 h-1 and good photochemical stability, which far exceeds those of most photocatalysts. The hierarchical loose structure of MIL-68(In)-20@ZIS is conducive to the adsorption of reactants and mass transfer. Meanwhile, a large number of tight 2D contact interfaces significantly reduce the obstruction of charge transfer, paving the way for high-perform photocatalytic hydrogen evolution. The experimental results demonstrate that the MIL-68(In)@ZIS heterojunction achieves intensive photoresponse and effective charge separation and transfer benefiting from unique charge transport paths of a type II heterojunction. This study opens an avenue toward MOF-based heterojunctions for solar energy conversion.

Erratum: Upper limit of the transition temperature of superconducting materials.

[This corrects the article DOI: 10.1016/j.patter.2022.100609.].

Mutation of cellulose synthase gene improves the nutritive value of rice straw.

Rice straw is an important roughage resource for ruminants in many rice-producing countries. In this study, a rice brittle mutant (BM, mutation in OsCesA4, encoding cellulose synthase) and its wild type (WT) were employed to investigate the effects of a cellulose synthase gene mutation on rice straw morphological fractions, chemical composition, stem histological structure and in situ digestibility. The morphological fractions investigation showed that BM had a higher leaf sheath proportion (43.70% vs 38.21%, p<0.01) and a lower leaf blade proportion (25.21% vs 32.14%, p<0.01) than WT. Chemical composition analysis showed that BM rice straw was significantly (p<0.01) higher in CP (crude protein), hemicellulose and acid insoluble ash (AIA) contents, but lower in dry matter (DM), acid detergent fiber (ADFom) and cellulose contents when compared to WT. No significant difference (p>0.05) was detected in neutral detergent fiber (NDFom) and ADL contents for both strains. Histological structure observation indicated that BM stems had fewer sclerenchyma cells and a thinner sclerenchyma cell wall than WT. The results of in situ digestion showed that BM had higher DM, NDFom, cellulose and hemicellulose disappearance at 24 or 48 h of incubation (p<0.05). The effective digestibility of BM rice straw DM and NDFom was greater than that of WT (31.4% vs 26.7% for DM, 29.1% vs 24.3% for NDFom, p<0.05), but the rate of digestion of the slowly digested fraction of BM rice straw DM and NDF was decreased. These results indicated that the mutation in the cellulose synthase gene could improve the nutritive value of rice straw for ruminants.

Materials information extraction via automatically generated corpus.

Information Extraction (IE) in Natural Language Processing (NLP) aims to extract structured information from unstructured text to assist a computer in understanding natural language. Machine learning-based IE methods bring more intelligence and possibilities but require an extensive and accurate labeled corpus. In the materials science domain, giving reliable labels is a laborious task that requires the efforts of many professionals. To reduce manual intervention and automatically generate materials corpus during IE, in this work, we propose a semi-supervised IE framework for materials via automatically generated corpus. Taking the superalloy data extraction in our previous work as an example, the proposed framework using Snorkel automatically labels the corpus containing property values. Then Ordered Neurons-Long Short-Term Memory (ON-LSTM) network is adopted to train an information extraction model on the generated corpus. The experimental results show that the F1-score of γ' solvus temperature, density and solidus temperature of superalloys are 83.90%, 94.02%, 89.27%, respectively. Furthermore, we conduct similar experiments on other materials, the experimental results show that the proposed framework is universal in the field of materials.

Ultrasensitive Frequency Shifting of Dielectric Mie Resonance near Metallic Substrate.

Dielectric resonators on metallic surface can enhance far-field scattering and boost near-field response having promising applications in nonlinear optics and reflection-type devices. However, the dependence of gap size between dielectric resonator and metallic surface on Mie resonant frequency is complex and desires a comprehensive physical interpretation. Here, we systematically study the effect of metallic substrate on the magnetic dipole (MD) resonant frequency at X-band by placing a high permittivity CaTiO3 ceramic block on metallic substrate and regulating their gap size. The simulated and experimental results show that there are two physical mechanisms to codetermine the metallic substrate-induced MD frequency. The greatly enhanced electric field pair in the gap and the coupling of MD resonance with its mirror image are decisive for small and large gaps, respectively, making the MD resonant frequency present an exponential blue shift first and then a slight red shift with increasing gap size. Further, we use the two mechanisms to explain different frequency shifting properties of ceramic sphere near metallic substrate. Finally, taking advantage of the sharp frequency shifting to small gaps, the ceramic block is demonstrated to accurately estimate the thickness or permittivity of thin film on metallic substrate through a governing equation derived from the method of symbolic regression. We believe that our study will help to understand the resonant frequency shifting for dielectric particle near metallic substrate and give some prototypes of ultrasensitive detectors.

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan-Green Garnet: Ce Phosphors with Excellent Thermal Stability.

Ce-doped garnet phosphors play an important role in the white light-emitting diode (LED) family. In the past years, a lot of trial-and-error experiments guided by experience to discover phosphors suitable for white LEDs have been presented. The working temperature of phosphors may reach 200 °C in white LEDs, and so, the exploration of phosphors with excellent thermal stability at the desired wavelength continues to be a challenge. In the present study, to discover novel cyan-green garnet:Ce phosphors, wavelength and thermal stability machine learning models were built by constructing reasonable features. Among the 171,636 compounds with garnet structures predicted by our models, 25 samples were selected for preparation and characterization by multiobjective optimization based on active learning. Lu1.5Sr1.5Al3.5Si1.5O12:Ce performed the best with excellent thermal stability (≥60% emission intensity was retained at 640 K) and exhibited emission peaks of about 505 nm, and it is a very promising phosphor for future applications, especially in high-temperature operating environments.

Rapid Discovery of Efficient Long-Wavelength Emission Garnet:Cr NIR Phosphors via Multi-Objective Optimization.

High-efficiency long-wavelength emission near-infrared (NIR) phosphors are the key to next-generation LED light sources. However, high-efficiency phosphors usually exhibit narrow-band emission at shorter wavelengths due to the crystal field intensity. In this paper, we utilize multi-objective optimization to discover the NIR phosphor Gd3Mg0.5Al1.5Ga2.5Ge0.5O12:0.04Cr3+. It exhibits a broadband NIR emission from 650 to 1100 nm peaking at 763 nm, with a full width at half maximum (FWHM) of 150 nm, an internal quantum efficiency (IQE)/external quantum efficiency (EQE) of 90%/53.1%, and good thermal stability (85.3% @ 150 °C). The packaging results show that ∼53.2 mW of output power is achieved at 915 mW input power, which suggests promising applications for NIR pc-LED. Our approach is based on the data of emission wavelength (WL) and IQE for garnet:Cr NIR phosphors to construct machine learning models. An active learning strategy is used to make tradeoffs between WL and IQE, and we are able to find the targeted phosphor after only four iterations of synthesis and characterization.

Mass Diffusion Metamaterials with "Plug and Switch" Modules for Ion Cloaking, Concentrating, and Selection: Design and Experiments.

The outstanding abilities of metamaterials to manipulate physical fields are extensively studied in both wave-based and diffusion-based fields. However, mass diffusion metamaterials, with the ability to manipulate diffusion with practical applications associated with chemical and biochemical engineering, have not yet been experimentally demonstrated. In this work, ion cloaking, concentrating, and selection in liquid solvents are verified by both simulations and experiments, and the concept of a "plug and switch" metamaterial is proposed based on scattering cancellation (SC) to achieve switchable functions by plugging modularized functional units into a functional motherboard. Plugging in any module barely affects the environmental diffusion field, but the module choice impacts different diffusion behaviors in the central region. Cloaking strictly hinds ion diffusion, and concentrating increase diffusion flux, while cytomembrane-like ion selection permits the entrance of some ions but blocks others. In addition, these functions are demonstrated in special applications like the catalytic enhancement by the concentrator and the protein protection by the ion selector. This work not only experimentally demonstrates the effective manipulation of mass diffusion by metamaterials, but also shows that the "plug and switch" design is extensible and reconfigurable. It facilitates novel applications including sustained drug release, catalytic enhancement, bioinspired cytomembranes, etc.