Ambient Degradation-Induced Spin Paramagnetism in Phosphorene.

The sizeable direct bandgap, high mobility, and long spin lifetimes at room temperature offer black phosphorus (BP) potential applications in spin-based semiconductor devices. Toward these applications, a critical step is creating a magnetic response in BP, which is arousing much interest. It is reported here that ambient degradation of BP, which is immediate and inevitable and greatly changes the semiconducting properties, creates magnetic moments, and any degree of degradation leads to notable paramagnetism. Its Landau factor g measured is ≈1.995, revealing that the magnetization mainly results from spin rather than orbital moments. Such magnetism most likely results from the unsaturated phosphorus in the vacancies which are stabilized by O adatoms. It can be tuned by changing any one of the ambient factors of ambient temperature, humidity, and light intensity, and can be stabilized by exposing BP in argon. The findings highlight the importance of evaluating the effect of ambient degradation-induced magnetism on BP's spin-based devices. The work seems an essential milestone toward the forthcoming research upsurge on BP's magnetism.

Laser paint removal monitoring based on time-resolved spectroscopy.

Laser paint removal is a new cleaning technology with high efficiency. Dynamic monitoring and closed-loop control of the laser paint removal process are key to reducing the risk of metal substrate damage and to achieving the best cleaning. In this paper, the time-resolved characteristics of the elemental peaks in the laser-induced breakdown spectrum of paints and substrate were studied by using the combination of a monochromator (or a bandpass filter) and a photomultiplier tube (PMT) detector. The results show that the intensity of the elemental spectrum peak of the paint has a sudden drop while the intensity of the elemental spectrum peak of the substrate has a sudden increase when the paint is removed. The time-resolved signals can be fitted by double exponential functions, which are combinations of exponential functions with a longer and a shorter lifetime, respectively. The relative ratios of the coefficients of the shorter and longer lifetimes (A s h o r t /A l o n g ) at the wavelength correspond to the elements in paint increasing suddenly while decreasing suddenly at the wavelength corresponding to the substrate. The intensity of the elemental spectrum peaks of paints and substrate and the ratio (A s h o r t /A l o n g ) can be used to monitor the laser paint removal process in real time to reduce the damage risk of the metal substrate and achieve the purpose of efficient cleaning with low cost.

Surface Vacancy-Induced Switchable Electric Polarization and Enhanced Ferromagnetism in Monolayer Metal Trihalides.

Monolayer chromium triiodide (CrI3), as the thinnest ferromagnetic material demonstrated in experiment [ Huang et al. Nature 2017 , 546 , 270 ], opens up new opportunities for the application of two-dimensional (2D) materials in spintronic nanodevices. Atom-thick 2D materials with switchable electric polarization are now urgently needed for their rarity and important roles in nanoelectronics. Herein, we unveil that surface I vacancies not only enhance the intrinsic ferromagnetism of monolayer CrI3 but also induce switchable electric polarization. I vacancies bring about an out-of-plane polarization without breaking the nonmetallic nature of CrI3. Meanwhile, the induced polarization can be reversed in a moderate energy barrier, arising from the unique porosity of CrI3 that contributes to the switch of I vacancies between top and bottom surfaces. Engineering 2D switchable polarization through surface vacancies is also applicable to many other metal trihalides, which opens up a new and general way toward pursuing low-dimensional multifunctional nanodevices.

Band-edge engineering via molecule intercalation: a new strategy to improve stability of few-layer black phosphorus.

The poor environmental stability of black phosphorous (BP) seriously limits its practical applications in (opto)electronics. Other than capping protective layers on its surface, herein we propose a new strategy to improve BP's ambient stability by engineering the interlayer interactions. Our first-principles calculations demonstrate that enlarging the interlayer spacing can effectively shift the conduction band minimum down to suppress the generation of superoxide and the enlargement can be achieved by intercalating small molecules like H2 and He into BP. Moreover, the molecule intercalated BP maintains high hole mobility, which makes it a better two-dimensional semiconductor for practical applications.

Water-Catalyzed Oxidation of Few-Layer Black Phosphorous in a Dark Environment.

Black phosphorus (BP) shows great potential in electronic and optoelectronic devices owing to its semiconducting properties, such as thickness-dependent direct bandgap and ambipolar transport characteristics. However, the poor stability of BP in air seriously limits its practical applications. To develop effective schemes to protect BP, it is crucial to reveal the degradation mechanism under various environments. To date, it is generally accepted that BP degrades in air via light-induced oxidation. Herein, we report a new degradation channel via water-catalyzed oxidation of BP in the dark. When oxygen co-adsorbs with highly polarized water molecules on BP surface, the polarization effect of water can significantly lower the energy levels of oxygen (i.e. enhanced electron affinity), thereby facilitating the electron transfer from BP to oxygen to trigger the BP oxidation even in the dark environment. This new degradation mechanism lays important foundation for the development of proper protecting schemes in black phosphorus-based devices.

Light-Induced Ambient Degradation of Few-Layer Black Phosphorus: Mechanism and Protection.

The environmental instability of single- or few-layer black phosphorus (BP) has become a major hurdle for BP-based devices. The degradation mechanism remains unclear and finding ways to protect BP from degradation is still highly challenging. Based on ab initio electronic structure calculations and molecular dynamics simulations, a three-step picture on the ambient degradation of BP is provided: generation of superoxide under light, dissociation of the superoxide, and eventual breakdown under the action of water. The well-matched band gap and band-edge positions for the redox potential accelerates the degradation of thinner BP. Furthermore, it was found that the formation of P-O-P bonds can greatly stabilize the BP framework. A possible protection strategy using a fully oxidized BP layer as the native capping is thus proposed. Such a fully oxidization layer can resist corrosion from water and leave the BP underneath intact with simultaneous high hole mobility.

High-Temperature Ferroelectricity and Photoluminescence in a Hybrid Organic-Inorganic Compound: (3-Pyrrolinium)MnCl3.

Coupling of ferroelectricity and optical properties has become an interesting aspect of material research. The switchable spontaneous polarization in ferroelectrics provides an alternative way to manipulate the light-matter interaction. The recent observation of strong photoluminescence emission in ferroelectric hybrid organic-inorganic compounds, (pyrrolidinium)MnX3 (X = Cl or Br), is an attractive approach to high efficiency luminescence with the advantages of ferroelectricity. However, (pyrrolidinium)MnX3 only displays ferroelectricity near or below room temperature, which limits its future applications in optoelectronics and multifunctional devices. Here, we rationally designed and synthesized high-temperature luminescent ferroelectric materials. The new hybrid compound (3-pyrrolinium)MnCl3 has a very high Curie temperature, Tc = 376 K, large spontaneous electronic polarization of 6.2 µC/cm(2), and high fatigue resistance, as well as high emission efficiency of 28%. This finding is a further step to the practical use of ferroelectric luminescence based on organic-inorganic compounds.

From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning.

Data scarcity is one of the critical bottlenecks to utilizing machine learning in material discovery. Transfer learning can use existing big data to assist property prediction on small data sets, but the premise is that there must be a strong correlation between large and small data sets. To extend its applicability in scenarios with different properties and materials, here we develop a hybrid framework combining adversarial transfer learning and expert knowledge, which enables the direct prediction of carrier mobility of two-dimensional (2D) materials using the knowledge learned from bulk effective mass. Specifically, adversarial training ensures that only common knowledge between bulk and 2D materials is extracted while expert knowledge is incorporated to further improve the prediction accuracy and generalizability. Successfully, 2D carrier mobilities are predicted with the accuracy over 90% from only crystal structure, and 21 2D semiconductors with carrier mobilities far exceeding silicon and suitable bandgap are successfully screened out. This work enables transfer learning in simultaneous cross-property and cross-material scenarios, providing an effective tool to predict intricate material properties with limited data.

Universal machine learning aided synthesis approach of two-dimensional perovskites in a typical laboratory.

The past decade has witnessed the significant efforts in novel material discovery in the use of data-driven techniques, in particular, machine learning (ML). However, since it needs to consider the precursors, experimental conditions, and availability of reactants, material synthesis is generally much more complex than property and structure prediction, and very few computational predictions are experimentally realized. To solve these challenges, a universal framework that integrates high-throughput experiments, a priori knowledge of chemistry, and ML techniques such as subgroup discovery and support vector machine is proposed to guide the experimental synthesis of materials, which is capable of disclosing structure-property relationship hidden in high-throughput experiments and rapidly screening out materials with high synthesis feasibility from vast chemical space. Through application of our approach to challenging and consequential synthesis problem of 2D silver/bismuth organic-inorganic hybrid perovskites, we have increased the success rate of the synthesis feasibility by a factor of four relative to traditional approaches. This study provides a practical route for solving multidimensional chemical acceleration problems with small dataset from typical laboratory with limited experimental resources available.

Prevalence of human metapneumovirus in children with acute lower respiratory infection in Changsha, China.

Human metapneumovirus (hMPV) causes acute respiratory infections in children. The prevalence and clinical characteristics of hMPV were determined in nasopharyngeal aspirates of children in Changsha, China. Reverse transcription-polymerase chain reaction (RT-PCR) or PCR was employed to screen for both hMPV and other common respiratory viruses in 1,165 nasopharyngeal aspirate specimens collected from children with lower respiratory tract infections from September 2007 to August 2008. All PCR products were sequenced, and demographic and clinical data were collected from all patients. Seventy-six of 1,165 (6.5%) specimens were positive for hMPV, of which 85.5% (65/76) occurred in the winter and spring seasons. The hMPV coinfection rate was 57.9% (44/76), and human bocavirus was the most common virus detected in conjunction with hMPV. Phylogenetic analysis revealed that 94.7% of the hMPV detected were of subgroup A2, 5.3% were subgroup B2, and none belonged to either the A1 or B1 subgroups. No significant differences were found in terms of the frequency of diagnosis and clinical signs between either the co- and mono-infection groups, or between patients with and without underlying diseases. It was concluded that hMPV is an important viral pathogen in pediatric patients with lower respiratory tract infections in Changsha. Only hMPV genotypes A2 and B2 were co-circulating in this locality; human bocavirus was the most common coinfecting virus, and coinfection did not affect disease severity.

Synthesis of carboxylate-functionalized graphene nanosheets for high dispersion of platinum nanoparticles based on the reduction of graphene oxide via 1-pyrenecarboxaldehyde.

A one-step reduction/functionalization strategy for the synthesis of carboxylate-functionalized graphene nanosheets is reported in this paper. 1-pyrenecarboxaldehyde (PCA) is introduced as a new reductant for the chemical reduction of graphene oxide (GO), serving three roles: reducing GO to graphene nanosheets (GNs), stabilizing the as-prepared GNs due to the electrostatic repulsion of the oxidation products of PCA (1-pyrenecarboxylate, PC⁻) on the surface of the GNs and anchoring Pt nanoparticles (Pt NPs) with high dispersion and small particle size. Transmission electron microscopy shows that Pt NPs with an average diameter of 1.3 ± 0.2 nm are uniformly dispersed on the surface of the PC⁻-functionalized GNs (PC⁻-GNs). The obtained Pt NPs/PC⁻-GNs nanohybrids have higher electrocatalytic activity and stability towards methanol oxidation in comparison with Pt NPs supported on GNs obtained by the chemical reduction of GO with the typical reductant, hydrazine.

Adaptive Design of Alloys for CO2 Activation and Methanation via Reinforcement Learning Monte Carlo Tree Search Algorithm.

Data-driven machine learning (ML) has earned remarkable achievements in accelerating materials design, while it heavily relies on high-quality data acquisition. In this work, we develop an adaptive design framework for searching for optimal materials starting from zero data and with as few DFT calculations as possible. This framework integrates automatic density functional theory (DFT) calculations with an improved Monte Carlo tree search via reinforcement learning algorithm (MCTS-PG). As a successful example, we apply it to rapidly identify the desired alloy catalysts for CO2 activation and methanation within 200 MCTS-PG steps. To this end, seven alloy surfaces with high theoretical activity and selectivity for CO2 methanation are screened out and further validated by comprehensive free energy calculations. Our adaptive design framework enables the fast computational exploration of materials with desired properties via minimal DFT calculations.

Distilling universal activity descriptors for perovskite catalysts from multiple data sources via multi-task symbolic regression.

Developing activity descriptors via data-driven machine learning (ML) methods can speed up the design of highly active and low-cost electrocatalysts. Despite the fact that a large amount of activity data for electrocatalysts is stored in the literature, data from different publications are not comparable due to different experimental or computational conditions. In this work, an interpretable ML method, multi-task symbolic regression, was adopted to learn from data in multiple experiments. A universal activity descriptor to evaluate the oxygen evolution reaction (OER) performance of oxide perovskites free of calculations or experiments was constructed and reached high accuracy and generalization ability. Utilizing this descriptor with Bayesian-optimized parameters, a series of compelling double perovskites with excellent OER activity were predicted and further evaluated using first-principles calculations. Finally, the two ML-predicted nickel-based perovskites with the best OER activity were successfully synthesized and characterized experimentally. This work opens a new way to extend machine-learning material design by utilizing multiple data sources.

[Viral etiology and risk factors for severe community-acquired pneumonia in children].

OBJECTIVE: To study the virus spectrum of severe community-acquired pneumonia (CAP) and risk factors for the disease in children. METHODS: Respiratory secretion specimens were collected from 1096 children hospitalized with CAP from June 2007 to November 2008, including 100 cases of severe CAP. Respiratory viruses were detected by PCR, nest-PCR or RT-PCR. Clinical data on the children were analyzed by univariate and multivariate logistic regression analysis for examining risk factors for severe CAP. RESULTS: Viral pathogens were isolated from 82 (82%) of the 100 cases with severe CAP. RSV was the most common (37%), followed by HBoV (25%) and HRV (18%). Mixed infection was noted in 32 cases (32%). The presence of underlying diseases (OR=6.623, P<0.01) and RSV infection (OR=1.672, P<0.05) were risk factors for severe CAP in children, while age was a protective factor (OR=0.475, P<0.01). CONCLUSIONS: RSV is the most frequent viral pathogen in children with severe CAP. The presence of underlying diseases and RSV infection may be risk factors for severe CAP, while age is a protective factor.

[Viral etiology of 1165 hospitalized children with acute lower respiratory tract infection].

OBJECTIVE: To explore the viral etiology of acute low respiratory tract infection (ALRTI) among hospitalized children in Changsha of Hunan Province of China. METHODS: Nasopharyngeal aspirates were collected from 1165 hospitalized children with ALRTI in Changsha from September 2007 to August 2008. Respiratory syncytin virus (RSV), human rhinovirus (HRV), influenza virus A (IFVA), influenza virus B (IFVB), parainfluenza 1-3 (PIV 1-3), human metapneumovirus (hMPV), human coronaviruses NL63 (HCoV-NL63), and human coronaviruses HKU1 (HCoV-HKU1) were detected by reverse transcription polymerase chain reaction (RT-PCR). Adenovirus (ADV) and human bocavirus (HBoV) were detected by standard polymerase chain reaction (PCR). WU polyomaviruses (WUPyV) and KI polyomaviruses(KIPyV) were detected by nested PCR. The positive samples further underwent genetic sequencing. RESULTS: Among the 1165 nasopharyngeal aspirates, viruses were detected in 871 samples (74.76%), among which RSV (27.03%) was the most common virus, followed by HRV (17.33%), PIV3 (13.73%), HBoV (8.67%) and hMPV (6.52%). The overall positive rate of viral detection showed no significant differences between males and females (X2=2.241, P=0.134), whereas the positive rates of PIV3, hMPV, and HBoV in males were higher than in females. The positive rate of viral detection showed significant differences among different age groups (X2=10.934, P=0.027), and the highest positive rate was noted in the age group of 6 months to 1 year. Furthermore, the overall positive rate of viral detection showed a significant difference in term of seasonal distribution, with a peak prevalence in winter. CONCLUSIONS: Virues predominate in the etiology of pediatric ALRTI in Changsha, and RSV, HRV and PIV3 are the main viruses for ALRTI. HBoV and hMPV have become increasingly important. Viral infection-associated ALRTI shows a prevail in the age group of 6 months to 1 year as well as in winter.

Formation of Graphene Nanoscrolls and Their Electronic Structures Based on Ab Initio Calculations.

Rolling up two-dimensional (2D) materials can form quasi-one-dimensional nanoscrolls, which are expected to have novel properties due to their larger space of structural parameters. In this Letter, the structural dependence of formation energy was investigated based on more than 90 different graphene nanoscrolls (GNSs) through ab initio calculations. A quantified relationship between formation energy and structural parameters is discovered, which could provide universal description of rolling up 2D materials beyond graphene. Further calculations on electronic structures show the opening of bandgap in GNSs with ultrahigh carrier mobilities up to 107 cm2 V-1 s-1. The structural stability under room temperature was also testified by using molecular dynamic simulations. This work provides general insights into the rolling-up strategy and demonstrates the tunable properties of GNSs, thus extending the scope of the research field for 2D materials.

Inverse design with deep generative models: next step in materials discovery.

Data-driven inverse design for inorganic functional materials is a rapidly emerging field, which aims to automatically design innovative materials with target properties and to enable property-to-structure material discovery.

Coexistence of Semiconducting Ferromagnetics and Piezoelectrics down 2D Limit from Non van der Waals Antiferromagnetic LiNbO3-Type FeTiO3.

Stable two-dimensional (2D) ferromagnetic semiconductors (FMSs) with multifunctional properties have attracted extensive attention in device applications. Non van der Waals (vdW) transition-metal oxides with excellent environmental stability, if ferromagnetic (FM), may open up an unconventional and promising avenue for this subject, but they are usually antiferromagnetic or ferrimagnetic. Herein, we predict an FMS, monolayer Fe2Ti2O9, which can be obtained from LiNbO3-type FeTiO3 antiferromagnetic bulk, has a moderate band gap of 0.87 eV, large perpendicular magnetization (6 µB/fu) and a Curie temperature up to 110 K. The intriguing magnetic properties are derived from the double exchange and negative charge transfer between O_p orbitals and Fe_d orbitals. In addition, a large in-plane piezoelectric (PE) coefficient d11 of 5.0 pm/V is observed. This work offers a competitive candidate for multifunctional spintronics and may stimulate further experimental exploration of 2D non-vdW magnets.

[Value of fluorescence quantitative PCR assay of bronchoalveolar lavage fluid samples in the diagnosis of Mycoplasma pneumoniae pneumonia in children].

OBJECTIVE: To study the value of fluorescence quantitative polymerase chain reaction (FQ-PCR) for detecting Mycoplasma pneumoniae (MP)-DNA in bronchoalveolar lavage fluid (BALF) in the early diagnosis of Mycoplasma pneumoniae pneumonia (MPP). METHODS: FQ-PCR was used to detect MP-DNA in BALF obtained by fiberoptic bronchoscopy from 61 children with MPP, and the sensitivity and the specificity of FQ-PCR were compared with the traditional serological test. RESULTS: The sensitivity and the specificity of BALF FQ-PCR for detecting MP-DNA were 94% and 100% respectively. The accuracy of BALF FQ-PCR assay for detecting MP-DNA was higher than that of the serological test at the early stage of the disease (1-7 days) (P<0.01). In the children with refractory MPP, BALF FQ-PCR assay also showed higher accuracy for detecting MP-DNA than the serological test (P<0.01). The copies of MP-DNA in children with refractory MPP were significant higher than those in children with common MPP (P<0.05). The copies of MP-DNA were positively correlated with CRP values (r=0.845, P<0.01). CONCLUSIONS: FQ-PCR assay of BALF for detecting MP-DNA in BALF is superior to the serological test. It is a reliable method for the early diagnosis of MPP, especially refractory MPP. The copies of MP-DNA can be used as an index for evaluation of the treatment outcome of refractory MPP.

Accelerated design of promising mixed lead-free double halide organic-inorganic perovskites for photovoltaics using machine learning.

Mixed double halide organic-inorganic perovskites (MDHOIPs) exhibit both good stability and high power conversion efficiency and have been regarded as attractive photovoltaic materials. Nevertheless, due to the complexity of structures, large-scale screening of thousands of possible candidates remains a great challenge. In this work, advanced machine learning (ML) techniques and first-principles calculations were combined to achieve a rapid screening of MDHOIPs for solar cells. Successfully, 204 stable lead-free MDHOIPs with optimal bandgaps were selected out of 11 370 candidates. The accuracy of ML models for perovskite structure formability and bandgap is over 94% and 97%, respectively. Moreover, representative MDHOIP candidates, MA2GeSnI4Br2 and MA2InBiI2Br4, stand out with suitable direct bandgaps, light carrier effective masses, small exciton binding energies, strong visible light absorption, and good stability against decomposition.