Understanding cellulose pyrolysis via ab initio deep learning potential field.

Comprehensive and dynamic studies of cellulose pyrolysis reaction mechanisms are crucial in designing experiments and processes with enhanced safety, efficiency, and sustainability. The details of the pyrolysis mechanism are not readily available from experiments but can be better described via molecular dynamics (MD) simulations. However, the large size of cellulose molecules challenges accurate ab initio MD simulations, while existing reactive force field parameters lack precision. In this work, precise ab initio deep learning potentials field (DPLF) are developed and applied in MD simulations to facilitate the study of cellulose pyrolysis mechanisms. The formation mechanism and production rate of both valuable and greenhouse products from cellulose at temperatures larger than 1073 K are comprehensively described. This study underscores the critical role of advanced simulation techniques, particularly DLPF, in achieving efficient and accurate understanding of cellulose pyrolysis mechanisms, thus promoting wider industrial applications.

Paper-based ratiometric fluorescent sensing platform based on mixed quantum dots for the detection of glucose in urine.

A paper-based ratiometric fluorescent sensing platform has been developed for glucose detection based on a dual-emission fluorescent probe consisting of carbon quantum dots (C QDs) and CdTe QDs. When the two kinds of QDs are mixed, the fluorescence of C QDs is reversibly quenched by CdTe QDs. However, in the presence of glucose, the fluorescence of CdTe QDs is quenched by H2O2 catalyzed by glucose oxidase (GOx), which restores the fluorescence of C QDs. The proposed paper-based ratiometric fluorescent sensing platform exhibited good sensitivity and selectivity towards glucose. The working linear range was 0.1 mM to 50 mM with a limit of detection (LOD) of 0.026 mM. Additionally, the proposed paper-based sensor possesses viability for the determination of glucose in actual urine samples.

A novel injectable hydrogel prepared from phenylboronic acid modified gelatin and oxidized-dextran for bone tissue engineering.

Complicated fractures have always been challenging in orthopaedics. Designing a multifunctional biomaterial that can contribute to the treatment of fractures using a simple operation remains challenging. Here, we developed a trinity hydrogel system consisting of hydrogel prepared from phenylboronic acid modified gelatin and oxidized-dextran, lithium and cobalt co-doped mesoporous bioactive glass nanoparticles (MBGNs), and irisin. This hydrogel material exhibits considerable injectability, fat-to-shape, and self-healing characteristics. In addition, compared to hydrogel prepared from gelatin and oxidized-dextran, the hydrogel material presented a noticeable enhancement in compression stress and adhesion strength towards porcine bone fragments, which enables it more effectively splice bone fragments during surgery. Based on the various interactions between irisin and the hydrogel network, the system exhibited a clear sustained release of irisin. Based on the results of in vitro cell tests, the hydrogel material showed good cytocompatibility. And it also considerably enhanced the in vitro pro-osteogenic and pro-angiogenic capacities of bone marrow mesenchymal stromal cells (BMSCs) and human umbilical vein endothelial cells (HUVECs). In vivo experimental results indicated that this hydrogel considerably improved the repair of cranial defects in rats. The current study provides a feasible strategy for the treatment of bone fractures and stimulation of fracture healing.

Perioperative neurocognitive disorder changes in elderly diabetes patients within 30 days after surgery: a retrospective cohort study.

BACKGROUND: Perioperative neurocognitive disorders (PND) are a common central nervous system complication that predominantly affects the elderly. PND after surgery includes postoperative delirium (POD), delayed neurocognitive recovery up to 30 days (DNR), and postoperative neurocognitive disorder up to 12 months. Diabetes is an important independent risk factor for PND. Over the years, few studies have assessed the incidence of PND and the difference in serum biomarkers between diabetic and non-diabetic patients. We sought to examine the difference in the incidence of PND between elderly diabetic and non-diabetic patients in China and identify the risk factors of PND in elderly diabetics. METHODS: We conducted a secondary and exploratory data analysis from our prior studies, including patients aged 65 years or older who underwent non-cardiac elective surgery with general anesthesia. We used the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Montreal Cognitive Assessment (MoCA) to assess patient cognition. RESULTS: A total of 236 patients were analyzed; the incidence of PND was significantly higher in diabetic than in non-diabetic patients within 30 days (59.2% vs. 36.8%) (P = 0.022). Multivariate logistic regression analysis showed that the preoperative MoCA was an independent risk factor for PND (odds ratio, 0.88 [0.8 to 0.97]; P = 0.014), and Hosmer-Lemeshow tests showed that it could predict PND in diabetic patients (P = 0.360). According to the maximum Youden index, the optimal cutoff for preoperative MoCA was 21.5 points, yielding a specificity and sensitivity of 88.0% and 55.2% for PND. The levels of glial fibrillary acidic protein (GFAP) and Tau in diabetic patients before and after surgery were significantly higher than in non-diabetic patients among cases of PND (P = 0.002 and 0.011, respectively). CONCLUSION: The incidence of PND is higher in diabetic than in non-diabetic patients in China, and preoperative MoCA is an independent risk factor for PND in diabetics. Meanwhile, the changes in GFAP and p-Tau in diabetic patients who experienced PND were significantly higher than in non-diabetic ones.

Recent Progress in Porphyrin/g-C3N4 Composite Photocatalysts for Solar Energy Utilization and Conversion.

Transforming solar energy into chemical bonds is a promising and viable way to store solar energy. Porphyrins are natural light-capturing antennas, and graphitic carbon nitride (g-C3N4) is an effective, artificially synthesized organic semiconductor. Their excellent complementarity has led to a growing number of research papers on porphyrin/g-C3N4 hybrids for solar energy utilization. This review highlights the recent progress in porphyrin/g-C3N4 composites, including: (1) porphyrin molecules/g-C3N4 composite photocatalysts connected via noncovalent or covalent interactions, and (2) porphyrin-based nanomaterials/g-C3N4 composite photocatalysts, such as porphyrin-based MOF/g-C3N4, porphyrin-based COF/g-C3N4, and porphyrin-based assembly/g-C3N4 heterojunction nanostructures. Additionally, the review discusses the versatile applications of these composites, including artificial photosynthesis for hydrogen evolution, CO2 reduction, and pollutant degradation. Lastly, critical summaries and perspectives on the challenges and future directions in this field are also provided.

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.

Lithium and cobalt co-doped mesoporous bioactive glass nanoparticles promote osteogenesis and angiogenesis in bone regeneration.

Healing of severe fractures and bone defects involves many complex biological processes, including angiogenesis and osteogenesis, presenting significant clinical challenges. Biomaterials used for bone tissue engineering often possess multiple functions to meet these challenges, including proangiogenic, proosteogenic, and antibacterial properties. We fabricated lithium and cobalt co-doped mesoporous bioactive glass nanoparticles (Li-Co-MBGNs) using a modified sol-gel method. Physicochemical analysis revealed that the nanoparticles had high specific surface areas (>600 m2/g) and a mesoporous structure suitable for hydroxyapatite (HA) formation and sustained release of therapeutic ions. In vitro experiments with Li-Co-MBGNs showed that these promoted angiogenic properties in HUVECs and pro-osteogenesis abilities in BMSCs by releasing Co2+ and Li+ ions. We observed their antibacterial activity against Staphylococcus aureus and Escherichia coli, indicating their potential applications in bone tissue engineering. Overall, our findings indicate the feasibility of its application in bone tissue engineering.

Biaxial strain improving carrier mobility for inorganic perovskite:ab initioBoltzmann transport equation.

Inorganic halide perovskites have attracted interest due to their high efficiency and low cost. Considering the uncertainty of experimental measurements, it was important to predict the upper limit of carrier mobility. In this study, theab initioBoltzmann transport equation, including all electron-phonon interactions, was used to accurately predict the mobilities of CsPbI3, CsSnI3, CsPbBr3, and CsSnBr3. Using the iterative Boltzmann transport equation (IBTE), the calculated mobility for CsPbI3isµe= 512/µh= 379 cm2 V-1 s-1, and Sn-based perovskite exhibited high hole mobility. The longitudinal optical phonons associated with the stretching between halogen anions and divalent metal cations were revealed to be the dominant scattering source for the carriers. Furthermore, the effect of biaxial strain on mobility was investigated. We observed that biaxial compressive strain could improve the mobility of CsPbI3and CsPbBr3. Surprisingly, under a compressive strain of-2%, the mobilities of CsPbI3using IBTE approach were improved toµe= 1176/µh= 936 cm2 V-1 s-1. It was revealed that the compressive strain could decrease the effective mass of CsPbI3and CsPbBr3.

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.

Genome-Wide Identification of MAPKK and MAPKKK Gene Family Members and Transcriptional Profiling Analysis during Bud Dormancy in Pear (Pyrus x bretschneideri).

The mitogen-activated protein kinase (MAPK) cascade consisting of three types of reversibly major signal transduction module (MAPKKK, MAPKK, and MAPK) is distributed in eukaryotes. MAPK cascades participate in various aspects of plant development, including hormone responses, cell division and plant dormancy. Pear is one of the most economically important species worldwide, and its yield is directly affected by dormancy. In this study, genome-wide identification of MAPKK and MAPKKK gene family members in Pyrus x bretschneideri and transcriptional expression analysis of MAPK cascades during pear dormancy were performed. We identified 8 MAPKKs (PbrMKKs) and 100 MAPKKKs (PbrMAPKKKs) in Pyrus using recent genomic information. PbrMAPKKs were classified into four subgroups based on phylogenetic analysis, whereas PbrMAPKKKs were grouped into 3 subfamilies (MEKK, Raf, and ZIK). Most PbrMAPKKKs and PbrMAPKKs in the same subfamily had similar gene structures and conserved motifs. The genes were found on all 17 chromosomes. The comprehensive transcriptome analysis and quantitative real-time polymerase chain reaction (qRT-PCR) results showed that numerous MAPK cascade genes participated in pear bud dormancy. The interaction network and co-expression analyses indicated the crucial roles of the MAPK member-mediated network in pear bud dormancy. Overall, this study advances our understanding of the intricate transcriptional control of MAPKKK-MAPKK-MAPK genes and provides useful information on the functions of dormancy in perennial fruit trees.

Study on outlier detection method of the near infrared spectroscopy analysis by probability metric.

Due to the high dimensionality and non-linearity of the near infrared (NIR) spectra data result the difficulty of the outlier measure. This paper proposed a probability based outlier detection method, which adopted the distribution probability of the spectra data to identify outliers at each wavelength by using of copula function. The negative logarithmic function was also used to quantify the overall variation of the joint distribution for the outliers. This method not only enlarges the difference of the spectra between typical samples and outliers, but also can be adapted to multi-type of outliers. Moreover, the jump degree in statistics was introduced for the automated determination of threshold for the outliers, which avoids the threshold setting problem in empirical way and the misjudgment of the outliers. In order to investigate the effectiveness of the algorithm, the recognition of different cases and types of outliers were applied, and compared with the commonly used PCA-Mahalanobis distance, spectral residual (SR) and leverage methods. The experimental results showed that the probability based outlier detection method effectively improved the performance of outlier identification and calibration for NIR analysis.

Investigation of the Photoresponse and Time-Response Characteristics of HDA-BiI5-Based Photodetectors.

Photoelectric devices can be so widely used in various detection industries that people began to focus on its research. The research of photoelectric sensors with high performance has become an industry goal. In this paper, we prepared photodetectors using organic-inorganic hybrid semiconductor materials with narrow bandgap hexane-1,6-diammonium pentaiodobismuth (HDA-BiI5) and investigated the detector photoresponse and time-response characteristics under a single light source. The device exhibits high photoresponsivity and fast response time. The photoresponsivity can reach 1.45 × 10-3 A/W and 8.5 × 10-4 A/W under laser irradiation at 375 nm and 532 nm wavelengths, and the rise and decay times are 63 ms and 62 ms, 62 ms and 64 ms, respectively. The device has excellent performance and this work can extend the application of organic-inorganic hybrid semiconductor materials in photovoltaic and photodetectors.

Association of hyperchloremia with all-cause mortality in patients admitted to the surgical intensive care unit: a retrospective cohort study.

BACKGROUND: Serum chloride (Cl-) is one of the most essential extracellular anions. Based on emerging evidence obtained from patients with kidney or heart disease, hypochloremia has been recognized as an independent predictor of mortality. Nevertheless, excessive Cl- can also cause death in severely ill patients. This study aimed to investigate the relationship between hyperchloremia and high mortality rate in patients admitted to the surgical intensive care unit (SICU). METHODS: We enrolled 2131 patients from the Multiparameter Intelligent Monitoring in Intensive Care III database version 1.4 (MIMIC-III v1.4) from 2001 to 2012. Selected SICU patients were more than 18 years old and survived more than 72 h. A serum Cl- level ≥ 108 mEq/L was defined as hyperchloremia. Clinical and laboratory variables were compared between hyperchloremia (n = 664) at 72 h post-ICU admission and no hyperchloremia (n = 1467). The Locally Weighted Scatterplot Smoothing (Lowess) approach was utilized to investigate the correlation between serum Cl- and the thirty-day mortality rate. The Cox proportional-hazards model was employed to investigate whether serum chlorine at 72 h post-ICU admission was independently related to in-hospital, thirty-day and ninety-day mortality from all causes. Kaplan-Meier curve of thirty-day and ninety-day mortality and serum Cl- at 72 h post-ICU admission was further constructed. Furthermore, we performed subgroup analyses to investigate the relationship between serum Cl- at 72 h post-ICU admission and the thirty-day mortality from all causes. RESULTS: A J-shaped correlation was observed, indicating that hyperchloremia was linked to an elevated risk of thirty-day mortality from all causes. In the multivariate analyses, it was established that hyperchloremia remained a valuable predictor of in-hospital, thirty-day and ninety-day mortality from all causes; with adjusted hazard ratios (95% CIs) for hyperchloremia of 1.35 (1.02 ~ 1.77), 1.67 (1.28 ~ 2.19), and 1.39 (1.12 ~ 1.73), respectively. In subgroup analysis, we observed hyperchloremia had a significant interaction with AKI (P for interaction: 0.017), but there were no interactions with coronary heart disease, hypertension, and diabetes mellitus (P for interaction: 0.418, 0.157, 0.103, respectively). CONCLUSION: Hyperchloremia at 72 h post-ICU admission and increasing serum Cl- were associated with elevated mortality risk from all causes in severely ill SICU patients.

High-efficiency (>20%) planar carbon-based perovskite solar cells through device configuration engineering.

Carbon-based perovskite solar cells (C-PSCs) have attracted widespread research interest because of their excellent stability. However, the power conversion efficiency (PCE) of C-PSCs, especially planar C-PSCs, lags far behind the certified efficiency (25.5%) of metal-based PSCs. The simple architecture of planar C-PSCs imparts stringent requirements for device configuration. In this study, we fabricated high-performance planar C-PSCs through device configuration engineering in terms of the perovskite active layer and carbon electrode. Through the combination of component and additive engineering, the crystallization and absorption profiles of perovskite active layer have been improved, which afforded sufficient photogenerated carriers and decreased nonradiative recombination. Furthermore, the mechanical and physical properties of carbon electrode were evaluated comprehensively to regulate the back-interface contact. Based on the compromise of the flexibility and conductivity of carbon film, an excellent back-interface contact has been formed, which promoted fast interface charge transfer, thereby decreasing interface recombination and improving carrier collection efficiency. Finally, the as-prepared devices achieved a remarkable PCE of up to 20.04%, which is a record-high value for planar C-PSCs. Furthermore, the as-prepared devices exhibited excellent long-term stability. After storage for 1000 h at room temperature and 25% relative humidity without encapsulation, the as-prepared device retained 94% of its initial performance.

Origin of phonon-limited mobility in two-dimensional metal dichalcogenides.

Metal dichalcogenides are novel two-dimensional (2D) semiconductors after the discovery of graphene. In this article, phonon-limited mobility for six kinds of 2D semiconductors with the composition of MX2is reviewed, in which M (Cr, Mo and W) is the transition metal, and X (S and Se) is the chalcogen element. The review is divided into three parts. In the first part, we briefly introduce the calculation method of mobility, including the empirical model and Boltzmann transport theory (BTE). The application scope, merits and limitations of these methods are summarized. In the second part, we explore empirical models to calculate the mobility of MX2, including longitudinal acoustic phonon, optical phonon (OP) and polar optical phonon (POP) models. The contribution of multi-valley to mobility is reviewed in the calculation. The differences between static and high-frequency dielectric constants (Δϵ) are only 0.13 and 0.03 for MoS2and WS2. Such a low value indicates that the polarization hardly changes in the external field. So, their mobility is not determined by POP, but by deformation potential models. Different from GaAs, POP scattering plays a decisive role in its mobility. Our investigations also reveal that the scattering from POP cannot be ignored in CrSe2, MoSe2and WSe2. In the third parts, we investigate the mobility of MX2using electron-phonon coupling matrix element, which is based on BTE from the framework of a many-body quantum-field theory. Valence band splitting of MoS2and WS2is induced by spin-orbit coupling effect, which leads to the increase of hole mobility. In particular, we review in detail the theoretical and experimental results of MoS2mobility in recent ten years, and its mobility is also compared with other materials to deepen the understanding.

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.

Device Modeling and Design of Inverted Solar Cell Based on Comparative Experimental Analysis between Effect of Organic and Inorganic Hole Transport Layer on Morphology and Photo-Physical Property of Perovskite Thin Film.

It is crucial to find a good material as a hole transport layer (HTL) to improve the performance of perovskite solar cells (PSCs), devices with an inverted structure. Polyethylene dioxythiophene-poly (styrene sulfonate) (PEDOT:PSS) and inorganic nickel oxide (NiOx) have become hotspots in the study of hole transport materials in PSCs on account of their excellent properties. In our research, NiOx and PEDOT: PSS, two kinds of hole transport materials, were prepared and compared to study the impact of the bottom layer on the light absorption and morphology of perovskite layer. By the way, some experimental parameters are simulated by wx Analysis of Microelectronic and Photonic Structures (wxAMPS). In addition, thin interfacial layers with deep capture levels and high capture cross sections were inserted to simulate the degradation of the interface between light absorption layer and PEDOT:PSS. This work realizes the combination of experiment and simulation. Exploring the mechanism of the influence of functional layer parameters plays a vital part in the performance of devices by establishing the system design. It can be found that the perovskite film growing on NiOx has a stronger light absorption capacity, which makes the best open-circuit voltage of 0.98 V, short-circuit current density of 24.55 mA/cm2, and power conversion efficiency of 20.01%.

Catalytic activity, thermal stability and structural evolution of PdCu single-atom alloy catalysts: the effects of size and morphology.

Single-atom alloys (SAAs) have been emerging as an important field of research in electrocatalysis owing to extremely high atom utilization, unique structure and high catalytic activity. In this work, the catalytic properties and thermal stability of PdCu SAAs with a crown-jewel (CJ) structure are studied by density functional theory (DFT) calculations and the molecular dynamics (MD) simulation method. The DFT results reveal that CJ-structured PdCu SAAs show excellent HER and ORR catalytic performance, and can be regarded as a promising alternative to Pt catalysts towards the ORR or HER. Additionally, we attempt to explain the high catalytic activity of PdCu SAAs by electronic structure analysis. In addition, MD simulation results confirm the thermal stability of CJ-structured PdCu. More importantly, we found that CJ-structured PdCu clusters undergo a structural transformation from cuboctahedral (Cubo) to icosahedral (Ico) structure by heating or after the adsorption of reaction intermediate, which indicates that Cubo is less stable than the Ico structure. Besides, Cubo-Ico transformation is size-dependent and only found in small clusters. Furthermore, the effects of size and morphology on melting properties are discussed. The melting point increases as cluster size increases, which agrees well with Pawlow's law.

Poly[2-(methacryloyloxy)ethyl choline phosphate] functionalized polylactic acid film with improved degradation resistance both in vitro and in vivo.

In this study, the surface-initiated atom transfer radical polymerization (SI-ATRP) of 2-(methacryloyloxy) ethyl choline phosphate (MCP) was successfully carried out via the ATRP initiator immobilized on the surfaces of polylactic acid (PLA) films. Different amounts of PMCP polymer brushes were constructed on the PLA surface to investigate the effects of the biological and degradation properties before and after modification. The results showed that the hydrophilicity of the surface of PLA were improved by MCP modification. In addition, there are no significant influence on the structure and crystallinity of the film before and after modification, except for the increased slightly thermal stability. Since the PMCP polymer brush forms a "protection" effect on the surface, the films showed an excellent property of resistant to hydrolysis even with obviously improved hydrophilicity. Furthermore, with the increase of the amount of introduced MCP monomer, the hydrophilicity and degradation resistance have been further improved. The in vivo animal experiment also verified this degradation resistance. Thereby, this strategy can be used to modulate the degradation rate of degradable polymers via surface modification.