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.

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.

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.

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.

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

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

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.

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.

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.

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.

Upper limit of the transition temperature of superconducting materials.

Why are the transition temperatures (T c) of superconducting materials so different? The answer to this question is not only of great significance in revealing the mechanism of high-T c superconductivity but also can be used as a guide for the design of new superconductors. However, so far, it is still challenging to identify the governing factors affecting the T c. In this work, with the aid of machine learning and first-principles calculations, we found a close relevance between the upper limit of the T c and the energy-level distribution of valence electrons. It implies that some additional inter-orbital electron-electron interaction should be considered in the interpretation of high-T c superconductivity.

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.

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.

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.

Ferroptosis: A Novel Type of Cell Death in Male Reproduction.

Ferroptosis, an iron-dependent type of regulated cell death, is triggered by the accumulation of lethal lipid peroxides. Due to its potential in exploring disease progression and highly targeted therapies, it is still a widely discussed topic nowadays. In recent studies, it was found that ferroptosis was induced when testicular tissue was exposed to some high-risk factors, such as cadmium (Cd), busulfan, and smoking accompanied by a variety of reproductive damage characteristics, including changes in the specific morphology and ferroptosis-related features. In this literature-based review, we summarize the related mechanisms of ferroptosis and elaborate upon its relationship network in the male reproductive system in terms of three significant events: the abnormal iron metabolism, dysregulation of the Cyst(e)ine/GSH/GPX4 axis, and lipid peroxidation. It is meaningful to deeply explore the relationship between ferroptosis and the male reproductive system, which may provide suggestions regarding pristine therapeutic targets and novel drugs.

Influence of Phase Transitions on Electrostrictive and Piezoelectric Characteristics in PMN-30PT Single Crystals.

The ultrahigh electrostrain and piezoelectric constant (d33) in relaxor piezoelectric PMN-30PT single crystals are closely related to the coexistence and transition of multiple phases at the morphotropic phase boundary (MPB). However, the key mechanisms underlying the stability of the phases and their transitions are yet to be fully understood. In this work, we undertake a systematic study of the influences of phase transitions on the electrostrictive and piezoelectric behaviors in ⟨001⟩-, ⟨011⟩-, and ⟨111⟩-oriented PMN-30PT single crystals. We first classify the various phase transitions within the quasi-MPB in electric field-temperature phase diagrams as either dominated by the electric field or by temperature. We find that the electrostrain reaches a maximum at each phase transition, especially in the electric-field-dominated transitions, whereas d33 only peaks at specific phase transitions. In particular, the electrostrain in the ⟨001⟩ crystal reaches a maximum of S = 0.52% at 55 °C under an external electric field with E = 15 kV/cm, primarily due to a joint contribution of the electric field-dominated rhombohedral-monoclinic and monoclinic-tetragonal phase transitions at the quasi-MPB. An ultrahigh d33 (∼2460 pC/N) only occurs at the rhombohedral-monoclinic phase transition in the ⟨001⟩ crystal and at the rhombohedral-orthorhombic transition in the ⟨011⟩ crystal (d33 ∼ 1500 pC/N) due to the lower energy barriers. The temperature-dominated phase transitions also contribute toward minor peaks in electrostrain and/or d33. This work provides a deeper and quantitative understanding of the microscopic mechanisms underlying electrostrictive and piezoelectric behaviors relevant for the design of high-performance materials.

Effect of Alloying Elements on the Stacking Fault Energy and Ductility in Mg2Si Intermetallic Compounds.

Alloying elements can pronouncedly change the mechanical properties of intermetallic compounds. However, the effect mechanism of this in Mg2Si alloys is not clear yet. In this paper, systematic first-principles calculations were performed to investigate the effect of alloying elements on the ductility of Mg-Si alloys. It was found that some alloying elements such as In, Cu, Pd, etc. could improve the ductility of Mg2Si alloys. Moreover, the interatomic bonding mechanisms were analyzed through the electron localization functional. Simultaneously, the machine-learning method was employed to help identify the most important features associated with the toughening mechanisms. It shows that the ground state atomic volume (V GS) is strongly related to the stacking fault energy (γus) of Mg2Si alloys. Interestingly, the alloying elements with appropriate V GS and higher Allred-Rochow electronegativity (En) would reduce the γus in the Mg-Si-X system and yield a better ductility. This work demonstrates how a fundamental theoretical understanding at the atomic and electronic levels can rationalize the mechanical properties of Mg2Si alloys at a macroscopic scale.

Engineering of g-C3N4-based photocatalysts to enhance hydrogen evolution.

The technology of photocatalytic hydrogen production that converts abundant yet intermittent solar energy into an environmentally friendly alternative energy source is an attractive strategy to mitigate the energy crisis and environmental pollution. Graphitic carbon nitride (g-C3N4), as a promising photocatalyst, has gradually received focus in the field of artificial photosynthesis due to its appealing optical property, high chemical stability and easy synthesis. However, the limited light absorption and massive recombination of photoinduced carriers have hindered the photocatalytic activity of bare g-C3N4. Therefore, from the perspective of theoretical calculations and experiments, many valid approaches have been applied to rationally design the photocatalyst and ameliorate the hydrogen production performance, such as element doping, defect engineering, morphology tuning, and semiconductor coupling. This review summarized the latest progress of g-C3N4-based photocatalysts from two perspectives, modification of pristine g-C3N4 and interfacial engineering design. It is expected to offer feasible suggestions for the fabrication of low-cost and high-efficiency photocatalysts and the photocatalytic mechanism analyses assisted by calculation in the near future. Finally, the prospects and challenges of this exciting research field are discussed.