Local Concentration Research Articles

A Multiscale Computational Modeling Framework to Quantify Microstructural Effects on Nucleation of Li Metal on Carbon Scaffold Architectures

Carbon materials with scaffold architecture have been shown to mitigate the non-uniform Li plating/stripping issues during cycling, which is critical for achieving significantly enhanced energy densities and improved safety of Li metal batteries. However, optimal design of the architecture and microstructure of the carbon materials requires fundamental understanding of the Li metal nucleation behavior at different length scales. In this poster, we present a multiscale computational modeling framework to quantify the microstructural effects of carbon materials on the tendency of Li metal nucleation during plating by integrating atomic-scale simulation, mesoscale microstructure-based homogenization, continuum-scale electrochemistry modeling, and classical nucleation theory. We modeled the architecture of the carbon scaffold and the electrochemistry of Li transport across the electrode and electrolyte by finite element simulation to determine boundary conditions for our mesoscale models. We then generated different porous microstructures of various carbon materials by stochastic and physics-based simulations informed from experiments and performed multiphysics-based simulations at mesoscale to identify the electro-chemo-mechanical hotspots which are sensitive to the microstructure morphology. We calculated the energy barriers for Li to form clusters on graphene surfaces as a function of local Li concentrations and electric fields by ab initio molecular dynamics simulations. The synergistic deployment of different models across scales allows us to theoretically estimate the Li metal nucleation tendency based on a modified classical nucleation theory for different microstructures under various electroplating conditions. Comparison of the theoretical predictions and experimental results will be briefly discussed. The insights obtained from this multiscale framework offer new understanding and strategies for the design of carbon scaffold architectures to mitigate the non-uniformity of Li plating and issues in Li metal anode deployment in solid-state batteries.This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and 22-ERD-043.

Microstructure Modeling of Transport and Kinetics in Solid State Batteries with LLZO Solid Electrolyte Fabricated Using the Freeze-Tape-Casting Method

In traditional Li-ion batteries with liquid electrolyte, the transport of lithium ions in the electrolyte and lithium in the active material within a porous electrode are studied extensively. The continuum-scale modeling of these transport phenomena considers a homogenized simulation domain consisting of liquid electrolyte and solid active material with effective transport properties accounting for the heterogeneity [1]. There have been fewer studies that consider digitized versions of the experimentally imaged microstructure in continuum-scale modeling studies, particularly to study mechanics [2]. Despite of the computational challenges, there are inherent advantages in using fully resolved microstructure modeling to improve fundamental understanding of the relevant physical and chemical phenomena in porous electrodes, such as localized degradation and stress concentration. In the case of solid electrolytes, specifically scaffold-type LLZO solid electrolytes, microstructure modeling is of even more relevance, particularly to study anisotropic transport, localized degradation phenomena, stress and deformation leading to loss of contact, and chemo-mechanics. Thus far, microstructure modeling studies on experimentally obtained microstructure consisting of solid electrolyte and active material have been quite limited [3]. The studies that have explored this realm have employed voxel-based mesh to discretize the computation domain [3]. While these methods are sufficient proof of concept, the lack of precision in defining the interface separating active material and electrolyte when using voxel-based mesh provides a source of potentially significant numerical error. Without a highly resolved interface mesh, the total interfacial area increases artificially which leads to inaccuracies in calculations of local reaction rate and overpotential. A highly resolved, smooth interface is also necessary when simulating mechanical deformation and stress field in the microstructure. In the present investigation, we model mass transport and charge transport in the active material/electrolyte microstructure to simulate concentration and potential fields with varying mesh types in order to compare their effectiveness and characterize the error that can be attributed to the mesh type chosen, particularly in the case of voxel-based meshes. Additionally, we study the effect of microstructure domain length chosen in the two directions perpendicular to the shortest length (electrode thickness) as well as boundary condition formulation on the boundaries in these axes on the simulation results. The microstructures studied in this work are derived from the image stacks of the bi/trilayer LLZO solid electrolyte fabricated using freeze-tape-casting method [4]. Overall, the present work aims to develop a better understanding of the best practices in microstructure modeling, particularly when using microstructure image stacks obtained from fabricated samples.

Enhanced Electrochemical Performance of Disordered Rocksalt Cathode in a Localized High Concentration Electrolyte

Lithium (Li) transition metal oxides with layered structure, commonly employed as cathodes in Li-ion batteries, exhibit limited capacity, and employ less abundant and costly materials, raising sustainability concerns amid surging battery demand. Addressing this, lithium rich cation disordered rock salt cathode (DRX) materials have garnered substantial attention as they offer high capacity and cost benefits. Manganese (Mn) based DRXs, in particular, show promise due to the utilization of earth abundant materials and good thermal stability of Mn. However, these cathodes often face challenges when cycled in state-of-the-art carbonate-based electrolytes. These include severe side reactions between the cathode and the electrolyte, transition metal dissolution and structural instability of the cathode particles all of which result in fast capacity fading. In this work, an advanced localized high concentration electrolyte (LHCE) is developed to mitigate these problems and enable stable cycling of Li1.2Mn0.6Ti0.2O2 (LMTO). The developed LHCE exhibits high voltage stability, forming an ultrathin and stable electrode/electrolyte interphase. Consequently, Li||LMTO half cells with the developed LHCE demonstrate increased capacity, enhanced cycling stability and superior rate capabilities compared to the cells with the conventional electrolyte. For instance, the Li||LMTO cells cycled in LHCE show higher initial capacity of 205.2 mAh/g, and a capacity retention of 72.5 % in contrast to an initial capacity of 187.7 mAh/g and a capacity retention of 19.9 % observed in Li||LMTO cells with the conventional electrolyte after 200 cycles at a current density of 20 mA/g. This work paves the way for the development of practical DRX cathode- based high-energy Li batteries.

Fluorination Promotes Lithium Salt Dissolution in Borate Esters for Lithium Metal Batteries

Lithium metal batteries promise higher energy densities than current lithium-ion batteries but require novel electrolytes to extend their cycle life. To promote electrolyte stability against lithium metal and improve the reversibility of lithium deposition/stripping, several electrolyte design strategies have been pursued. For example, high concentration electrolytes (HCEs) and localized high concentration electrolytes (LHCEs) produce solvation structure rich in salt aggregates and ion pairs, which can increase lithium metal cycling Coulombic efficiency to as high as 99.5%. Recently, molecular design of fluorinated ether solvents also leads to high lithium metal Coulombic efficiency of up to 99.9% in single-solvent-single-salt ~ 1 M electrolytes. In addition, fluorinated acetals, fluorinated carbonates, and fluorinated sulfonamides are also reported to enable efficient lithium metal cycling. Among those novel electrolytes, fluorinated solvents or diluents are frequently used because fluorinated moieties are known to yield LiF as a preferable component in solid electrolyte interphase (SEI). However, fluorinated groups are believed to weaken ion solvation as most fluorinated solvents show poorer solvation ability or lower ionic conductivity compared to their nonfluorinated counterparts. The trade-off between SEI passivation and ion solvation limits further optimization of fluorinated electrolytes.In this work, we synthesize tris(2-fluoroethyl) borate (TFEB) as a new fluorinated borate ester solvent. Interestingly, moderately fluorinated TFEB shows unexpectedly high lithium salt solubility (~1 M LiFSA) while the nonfluorinated triethyl borate (TEB) and heavily fluorinated tris(2,2,2-trifluoroethyl) borate (TTFEB) can hardly dissolve lithium salt. Through density functional theory (DFT) calculations and ab-initio molecular dynamics (AIMD) simulations, we show that the partially fluorinated -CH2F group in TFEB acts as primary coordination site that promotes lithium salt dissolution. The electrochemical property of TFEB electrolyte is then compared to the methoxy polyethyleneglycol borate esters reported in literature. Owing to the fluorinated solvent structure, TFEB electrolyte passivates lithium metal with LiF-rich SEI and supports compact lithium deposition morphology, high lithium metal Coulombic efficiency, and stable cycling of lithium metal/LiFePO4 cells. This work ushers in a new electrolyte design paradigm where partially fluorinated moieties enable salt dissolution and can serve as primary ion coordination sites for next-generation electrolytes. Figure 1

A Reduced-Order Model of the Coupled Venting-Thermal-Electrochemical Behavior to Predict First Venting Under External Short Circuit Conditions

Modeling abusive battery operation before thermal runaway (TR) can reduce the testing requirements and facilitate the development of effective and reliable early failure detection and fast discharge strategies [1] which require multiple types of sensor signals, including current, voltage, temperature, and pressure. We present a multi-physics model that can predict the rapidly evolving discharge behavior of cells undergoing an external short circuit, including hazards like first venting. First venting models account for gas generation due to SEI decomposition and electrolyte vaporization at high temperatures to calculate the build-up of internal cell pressure under constant-displacement conditions [2]. Modeling gas generation requires accurate temperature prediction, which subsequently requires accurate Joule heating calculated from current and voltage predictions. From the cascading chain of model input dependencies, the first challenge is managing error propagation through the submodels with appropriate parameterization. Previous modeling work parameterized a venting model for a cell undergoing an external short circuit (ESC) but did not include a thermal or electrical model [2]. The second challenge is modeling the diffusion-limited discharge behavior with currents approaching 50-80 C with a fast and accurate model that is feasible for detection and control applications. Diffusion-limited behavior occurs when the local Li concentration saturates, suddenly causing large concentration overpotentials that are observable in the terminal voltage and current (see Fig. 1) as well as numerical instability when solving the Butler-Volmer (BV) equation. Previous ESC modeling works either used the Doyle-Fuller-Newman (DFN) model with a limiting current density in the BV equation [3] or an equivalent circuit model (Eq-CM) [1]. However, solving the DFN is computationally intensive for a control application, while Eq-CMs cannot predict the diffusion-limited electrical behavior beyond the data they were parameterized on, requiring apriori experiments to be accurate. To balance the trade-offs, we instead look towards reduced-order modeling.In this work, we present a control-oriented, reduced-order, multi-physics model that captures the electrochemical, thermal, and venting behavior of four 4.6 Ah NMC pouch cells undergoing an external short circuit with different initial state-of-charge (SOC). The multi-physics model couples a first venting model with a lumped thermal model driven by Joule heating calculated through the overpotentials from the Single-Particle Model with electrolyte (SPMe). The combined model was parameterized through four experiments by fitting five key parameters in the submodels related to the SEI decomposition rate, cell thermal behavior, and solid electrode diffusion to capture the first venting timing, peak temperature, and diffusion-limited current-voltage drops. Additionally, two resistances were tuned to match the initial current and voltage with all other parameters were taken from the literature. Applying the same parameter set consisting of the average of the fitted values on all four cells, the combined multi-physics model correctly predicted that the fully-charged cells would vent and conservatively predicted the cell venting timing up to about 40 s before it occurred in the experiment. For high initial SOC cells, the SPMe also accurately predicted the current and voltage drops associated with diffusion limitations and SOC up until the cell vented. This is the first work that systematically parameterizes and couples a reduced-order, physics-based model to capture the electrical, thermal, and venting behavior under battery abuse conditions. Future work will explore applications for the model in early detection and response to critical safety events.REFERENCES[1] Tran, Vivian, Jason Siegel, and Anna Stefanopoulou. "Emergency Li-ion Battery Discharge using Nonlinear Model Predictive Control with Temperature and Venting Pressure Constraints." 2023 American Control Conference (ACC). IEEE, 2023.[2] Cai, Ting, et al. "Modeling li-ion battery first venting events before thermal runaway." IFAC-PapersOnLine 54.20 (2021): 528-533.[3] Rheinfeld, Alexander, et al. "Quasi-isothermal external short circuit tests applied to lithium-ion cells: Part ii. modeling and simulation." Journal of The Electrochemical Society 166.2 (2019): A151. Fig. 1: 15-min simulation of an external short circuit for cells at different initial SOC. Model results and experimental measurements are shown for four cells that were externally shorted. The measured current, voltage, temperature, and expansion force were measured at 10 Hz and plotted versus log time to highlight the dynamic current-voltage behavior in the first few minutes. The diffusion-limited current and voltage behavior are captured by the model. The two cells at 100% SOC, experienced venting and higher peak temperatures, which are well captured by the model. The cell venting timing was predicted to be 43 s and 7 s early for Cell 100A and 100B, respectively. The cells that were shorted at lower SOC did not vent. Figure 1

Modeling Stochastic Kinetics of Cathodic Cu Surface Corrosion and Ionic Interaction in Nanoscopic Water Pools

Cathodic Cu corrosion has been reported to occur in both the presence and absence of carbon dioxide in aqueous electrolytes and while the mechanism is not understood well it implies carbide-, hydride- and hydroxide-formation mediated pathways. Corrosion leads to roughening, which creates local pockets of electrolyte that are somewhat disconnected from the bulk. In this talk, we describe a combination of theoretical studies to identify reaction pathways, and kinetics modeling of them to obtain a working description of corrosion in water. Corrosion at metal surfaces is both influenced by and influences the formation of nanoscopic aqueous pools by trapping electrolyte solution in microscopic pockets. Such electrolyte nano-pools exhibit non-bulk behavior, and the lifetime of locally trapped ions can be significantly different than in the bulk. This can potentially have an effect on the chemistry in the local microenvironment. Stochastic reaction-diffusion models can be used to model kinetics of electrochemical processes at length and time scales relevant to laboratory experiments, allowing a direct comparison of transient observable quantities to time-resolved experimental data. Atomistic simulations employ methods of electronic structure theory (such as density functional theory (DFT)) and molecular dynamics (both classical and ab initio) to describe a detailed picture of the (electro-)chemistry at microscopic time and length scales. Scaling up these methods to macroscopic levels is not trivial but required for direct comparison to experiment. By using Gibbs free energies obtained from atomistic simulations it is possible to calculate rate constants for individual elementary steps in reaction schemes describing kinetics of relevant processes. We use Kinetiscope to implement stochastic kinetics models of two reaction schemes describing: 1. cathodic Cu surface corrosion through formation of copper hydroxides, through which we aim to describe essential steps in the cathodic corrosion mechanism of metal surfaces; 2. interactions between bicarbonate and hydronium ions, both present in the bicarbonate salt buffers used routinely in electrochemical reduction at copper surfaces, in a nanoscopic water droplet to understand time-dependent changes in the local concentrations of electrolytes trapped at or near metal surfaces. Figure 1

Sensitivity Analysis of Atmospheric Ozone and Source Apportionment of Volatile Organic Compounds in Yinchuan City

Based on the observation data of O3 concentration in Yinchuan in 2022, the monthly variation characteristics of O3 concentrations were analyzed. Further, based on the observation data of meteorological elements, conventional pollutants, and volatile organic compounds （VOCs） concentrations at an urban site in Yinchuan from May to July, the difference in meteorological elements and precursor concentrations between the polluted days and the non-polluted days were compared. Then, the O3 sensitivity and the VOCs sources were discussed using the Framework for 0-D Atmospheric Modeling （F0AM） and positive matrix factorization （PMF） model, respectively. The results showed that： ① The O3 pollution occurred from May to July in 2022, and the concentrations of O3-8h-90per were 156 μg·m-3, 170 μg·m-3, and 174 μg·m-3, respectively, with exceeding standard rates of 9.7%, 26.7%, and 29.0%, respectively. ② Compared with those on the non-polluted days, the hourly mean values of temperature, total solar radiation, and concentrations of various precursors on the O3-polluted days increased, including the volume concentrations of propane, isobutane, ethane, n-butane, and dichloromethane, which increased significantly by 33.1%, 29.1%, 25.0%, 22.7%, and 21.3%, respectively. The results showed that the combined increase in pollutant emissions and adverse meteorological conditions contributed to the formation of O3. ③ From May to July 2022, the top five VOCs species in terms of ozone formation potential （OFP） value on whole, non-polluted, and polluted days were the same. They were acetaldehyde, m/p-xylene, ethylene, isoprene, and toluene, mainly from solvent use sources, natural sources, and chemical industry emissions. ④ The local O3 production was mostly controlled by VOCs, and the relative incremental reactivity （RIR） results revealed that O3 production showed strong positive sensitivity to alkene and aromatic hydrocarbon but showed negative sensitivity to NOx on both polluted and non-polluted days. The relative contributions of active species such as acetone, ethylene, and isobutane to O3 production were high, and the implementation of an emission reduction scheme with the ratio of VOCs to NOx emission reduction much greater than 1 could effectively reduce the local O3 concentration. ⑤ The main sources of atmospheric VOCs in Yinchuan were motor vehicle emission sources （32.3%）, process sources （20.7%）, combustion sources （19.2%）, solvent use sources （12.7%）, gasoline volatile sources （9.1%）, and natural sources （6%）, and the contribution rate of motor vehicle emission sources on polluted days increased by 4.6% compared with that on non-polluted days, indicating that the motor vehicle emission source was an important object of summer VOCs control in Yinchuan.

Compartmentalization in cardiomyocytes modulates creatine kinase and adenylate kinase activities.

Intracellular molecules are transported by motor proteins or move by diffusion resulting from random molecular motion. Cardiomyocytes are packed with structures that are crucial for function, but also confine the diffusional spaces, providing cells with a means to control diffusion. They form compartments in which local concentrations are different from the overall, average concentrations. For example, calcium and cyclic AMP are highly compartmentalized, allowing these versatile second messengers to send different signals depending on their location. In energetic compartmentalization, the ratios of AMP and ADP to ATP are different from the average ratios. This is important for the performance of ATPases fuelling cardiac excitation-contraction coupling and mechanical work. A recent study suggested that compartmentalization modulates the activity of creatine kinase and adenylate kinase in situ. This could have implications for energetic signaling through, for example, AMP-activated kinase. It highlights the importance of taking compartmentalization into account in our interpretation of cellular physiology and developing methods to assess local concentrations of AMP and ADP to enhance our understanding of compartmentalization in different cell types.

Numerical simulation of the Co-combustion of coke and biochar coupled with methane injection in iron ore sintering processes

It is of great significance for cleaner production to partially replace traditional coke with biomass fuel in iron ore sintering processes. However, the higher reactivity of biomass leads to an unacceptable deterioration in sintering performance, which limits its high proportion application. This paper presents the numerical simulation of the technology of combining gaseous fuels and biomass for iron ore sintering. The improvement effect and mechanism of the methane injection method on the heat pattern and performance of the coke/biochar co-sintering bed were discussed. To more accurately quantify the coupling phenomena involved, the proposed model especially considers sub-processes of biomass combustion and gaseous reactions including volatile release/char formation, burning of the volatiles, and the oxidation and gasification of char particles. The results indicated that the equivalent methane heat injection method reached its limit of improvement at a concentration of about 0.6%, and failed to obtain qualified products. The thermal indicators and yield kept increasing within the concentration simulation range of 0∼0.8% under the extra methane method. At a concentration of 0.8%, peak temperature (PT), duration time (DTMZ), and enclosed area (MQI) in the high-temperature zone are 1442.094 K, 165.6 s, and 15923.72 K s, respectively, reaching the level of all coke method. The use of local concentration segregation can significantly optimize heat distribution and increase the yield of the coke/biochar co-sintering process.

Molecular dynamics modelling of interacting magnetic nanoparticles for investigating equilibrium and dynamic ensemble properties

Magnetic nanoparticles have the potential to be used in various biomedical applications, including magnetic drug targeting and hyperthermia for cancer treatment. In both cases, precise prediction of the local particle concentration is required to plan a successful therapy, which is a challenging task due to several complex flow phenomena. Computational macroscopic and microscopic models have been developed to support this process, but they have limitations in terms of interactions implementation, micromagnetic dynamics or computational costs. This study aims to develop a model that can represent micromagnetic dynamics and being employed to study equilibrium properties of particle ensembles in viscous media. Therefore, a kinetic Monte Carlo method in combination with Langevin equations is used. So, magnetization dynamics and mechanical motion can be simulated in combination very efficiently. The new model is validated with another model based on the stochastic Landau-Lifshitz-Gilbert equation. Various interaction potentials like Van der Waals, steric and electrostatic interactions are included to study their specific influence on structural properties. Also, methods to control the errors while integrating the equations of motion and using the Ewald method for calculating interaction quantities are implemented. As a validation we studied equilibrium and time dependent properties of non-interacting particle ensembles as well as errors made by the Ewald-method used for interaction quantities calculation. In all studies we found very good agreement of the simulation results with the theoretical predictions. The developed models can now be used for investigating equilibrium and dynamic properties of ferrofluids, or more general for biomedical research for magnetic drug targeting, hyperthermia, or imaging techniques. Furthermore, the new hybrid model can be also used for simulations in the range of milliseconds with reasonable computational effort.

Enhanced Fire Safety of Energy-Saving Foam by Self-Cleavage CO2 Pre-Combustion and Phosphorus Release Post-Combustion.

Rigid polyurethane foam (RPUF) is widely utilized in construction and rail transportation due to its lightweight properties and low thermal conductivity, contributing to energy conservation and emission reduction. However, the inherent flammability of RPUF presents significant challenges. Delaying the time to ignition and preventing flame spread post-combustion is crucial for ensuring sufficient evacuation time in the event of a fire. Based on this principle, this study explores the efficacy of using potassium salts as a catalyst to promote the self-cleavage of RPUF, generating substantial amounts of CO2, thereby reducing the local oxygen concentration and delaying ignition. Additionally, the inclusion of a reactive flame retardant (DFD) facilitates the release of phosphorus-oxygen free radicals during combustion, disrupting the combustion chain reaction and thus mitigating flame propagation. Moreover, potassium salt-induced catalytic carbonization and phosphorus derivative cross-linking enhance the condensed phase flame retardancy. Consequently, the combined application of potassium salts and DFD increases the limiting oxygen index (LOI) and reduces both peak heat release rate (PHRR) and total heat release (THR). Importantly, the incorporation of these additives does not compromise the compressive strength or thermal insulation performance of RPUF. This integrated approach offers a new and effective strategy for the development of flame retardant RPUF.

Therapeutic application of mesenchymal stem cell-derived exosomes in skin wound healing.

Wound healing is a complicated obstacle, especially for chronic wounds. Mesenchymal stem cell-derived exosomes may be a promising cell-free approach for treating skin wound healing. Exosomes can accelerate wound healing by attenuating inflammation, promoting angiogenesis, cell proliferation, extracellular matrix production and remodeling. However, many issues, such as off-target effects and high degradation of exosomes in wound sites need to be addressed before applying into clinical therapy. Therefore, the bioengineering technology has been introduced to modify exosomes with greater stability and specific therapeutic property. To prolong the function time and the local concentration of exosomes in the wound bed, the use of biomaterials to load exosomes emerges as a promising strategy. In this review, we summarize the biogenesis and characteristics of exosomes, the role of exosomes in wound healing, and the therapeutic applications of modified-exosomes in wound healing. The challenges and prospects of exosomes in wound healing are also discussed.

A mitochondria-targeted fluorescent probe for revealing H2O2 elevation modulated by basal HClO in HeLa and A549 cells

Hydrogen peroxide, which is mainly produced in mitochondria, plays deleterious and beneficial roles in cells depending on its localized concentration. Tumor cells have been observed to have increased H2O2 levels due to enhanced metabolic activity. Moderately high levels of H2O2 are crucial for the growth and survival of tumor cells. Monitoring mitochondrial H2O2 is essential for revealing the factors that affect cellular redox balance. In the present work, we have developed a fast responsive fluorescent probe for the detection of H2O2 in mitochondria. Hcy-S shows high selectivity, sensitivity and a fast response to H2O2, enabling imaging of basal levels of mitochondrial H2O2 in tumor cells in 1 min. Hcy-S has been applied to the study of the impact of HClO on H2O2 level. The results revealed that endogenous HClO raises the levels of H2O2 by inactivating catalase and glutathione peroxidase in HeLa and A549 cells. This study offers a novel insight into the redox balance in tumor cells.

Enhancing strength-ductility combination of Fe–Ni–Cr–Al–Ti high-entropy alloys via co-precipitation of sigma and L21 phases

The sigma phase is a well-known harmful phase in transition metal alloys, leading to severe embrittlement due to its inherent brittleness. However, in this work, we develop a new strategy to obtain enhanced strength-ductility combination via the synergistic effects of interlocking co-precipitation of the sigma and L21 phases in Fe40Ni30Cr20Al5Ti5 (at. %) high-entropy alloy (HEA). This HEA exhibits a good strength-ductility combination after aging treatment (800 °C for 4h), with a yield strength (YS) of about 920 MPa and an ultimate tensile strength (UTS) of about 1300 MPa while maintaining a total elongation (TE) of 24 %. It is attributed to the interlocking co-precipitation of the sigma and L21 phases with equal volume fractions into the face-centered cubic (FCC) matrix through thermomechanical treatment. During the tensile deformation, the softer L21 phase coordinates the deformation around the sigma phase, suppresses the local stress concentration, and achieves a stable high work hardening capability, as well as stacking faults (SFs) networks and density Lomer-Cottrell (L-C) locks, contributes to the excellent strain hardening capacity and thus obtains the enhanced strength-ductility combination in the HEA. This study will provide a new strategy to obtain enhanced strength-ductility combination for alloys containing brittle and hard topologically close-packed (TCP) phases, such as the sigma phases.

The effect of farm size and farmland use on agricultural diversification: a spatial analysis of Brazilian municipalities

Brazilian agriculture is characterized by the prevalence of small farms and regions with a high degree of rurality and dominance of the agricultural sector in the economy. These two characteristics affect the diversity of agricultural production in the country. Specifically, the article aims to analyze the effects of size farm and farmland use on agricultural diversification and the effects of demand and technology adopted by farmers. The database encompasses 4298 Brazilian municipalities from 1996 to 2017 (the last three agricultural censuses). Empirically, we consider spillover effects by estimating spatial models at the municipal level using panel data, highlighting the importance of location and neighborhood. The study’s findings indicate a tendency toward local concentration of agricultural production in the country, despite the balance between municipalities with diversified and concentrated production. The results showed a significant effect of small farms and the municipalities’ rurality degree on the agricultural output diversification. The study provides insights into the discussion on measures to strengthen support for small properties and regions that diversify crops to ensure economic efficiency and food security.

Impact of air pollution on human morality: A multinational perspective

This study aimed to investigate whether global air pollution harms human morals beyond physiological and psychological health. To accomplish this, we conducted an original survey involving over 80,000 individuals across 30 countries, inquiring about their recent perceived unethical behaviors. Through regression analyses, we identified global evidence of a positive correlation between local monthly average concentrations of nitrogen dioxide (NO2) and perceptions of unethical behavior. This finding suggests that air pollution may potentially elicit unethical behavior through a complex response mechanism. It is noteworthy that the impact of air pollution on the inclination to perceive unethical behavior is heterogeneous across categories of unethical behavior and countries. For example, the effects of increasing air pollution concentrations vary even within the same European country: an increase in NO2 concentration in Greece and the Netherlands augments the inclination to perceive fatal unethical behaviors such as murder, terrorism, and suicide, while in Germany, NO2 concentration diminishes the inclination to perceive the same types of unethical behaviors. Overall, the societal costs of air pollution may be even more far-reaching than previously acknowledged, and further research is necessary to unveil the intricate response mechanisms underlying this issue.

Tourniquet Use and Local Tissue Concentrations of Cefazolin During Total Knee Arthroplasty

Prophylactic administration of antibiotics before skin incision is an important component in the prevention of periprosthetic joint infection in arthroplasty surgery. For antibiotics to be effective, the local tissue concentration (LTC) must exceed the minimum inhibitory concentration of typical infecting organisms; however, the LTC of cefazolin during arthroplasty is poorly understood. To compare the systemic concentration of cefazolin in serum with the LTC in fat, synovium, and bone during primary total knee arthroplasty (TKA) while assessing the effect of tourniquet inflation. This prospective randomized clinical trial was conducted from March 1, 2022, to June 30, 2023, in patients undergoing TKA at a single academic center. Total knee arthroplasty with or without a limb tourniquet. Systemic blood and local tissues from the surgical site (fat, synovium, and bone) were harvested at regular intervals during the surgery. The primary outcome was the LTC of cefazolin, quantified using the liquid chromatography-tandem mass spectrometry technique. A total of 59 patients were included in the study, with 29 in the tourniquet group (mean [SD] age, 69.3 [9.6] years; 23 [79.3%] female) and 30 in the no tourniquet group (mean [SD] age, 69.9 [9.7] years; 21 [70.0%] female). In patients undergoing TKA without a tourniquet, the mean concentration of cefazolin in serum was 71.9 μg/mL (95% CI, 66.4-77.5 μg/mL), whereas the mean LTCs were 13.9 μg/g (95% CI, 12.1-15.7 μg/g) in fat, 27.7 μg/g (95% CI, 24.3-31.0 μg/g) in synovium, and 17.7 μg/g (95% CI, 14.8-20.5 μg/g) in bone. For patients undergoing TKA with a tourniquet, the mean concentration of cefazolin in serum was 72.0 μg/mL (95% CI, 66.3-77.7 μg/mL), and the mean LTCs were 9.9 μg/g (95% CI, 8.7-11.1 μg/g) in fat, 21.8 μg/g (95% CI, 18.7-25.0 μg/g) in synovium, and 13.0 μg/g (95% CI, 10.8-15.2 μg/g) in bone. The use of a tourniquet resulted in significantly lower mean LTCs by 60 minutes after cefazolin infusion (10.8 μg/g [95% CI, 9.1-12.4 μg/g] vs 16.9 μg/g [95% CI, 14.1-19.6 μg/g], P = .001 in fat; 18.9 μg/g [95% CI, 14.1-23.6 μg/g] vs 25.8 μg/g [95% CI, 21.4-30.3 μg/g], P = .03 in synovium; and 11.8 μg/g [95% CI, 9.3-14.2 μg/g] vs 19.4 μg/g [95% CI, 14.5-24.4 μg/g], P = .007 in bone). In this randomized clinical trial, the concentration of cefazolin was lower in local tissues (fat, synovium, and bone) than in systemic blood, and the use of a limb tourniquet further significantly reduced these concentrations. Although the current prophylactic dosing regimen for cefazolin provides sufficient serum concentrations, the levels in the periarticular tissue during TKA may be insufficient to prevent periprosthetic joint infection. ClinicalTrials.gov Identifier: NCT05604157.

Protein-Induced DNA Dumbbell Amplification (PINDA) and its applications to food hazards detection

Quantification of trace amounts of proteins is technically challenging because proteins cannot be directly amplified like nucleic acids. To improve the analytical sensitivity and to complement conventional protein analysis methods, we developed a highly sensitive and homogeneous detection strategy called Protein-Induced DNA Dumbbell Amplification (PINDA). PINDA combines protein recognition with exponential nucleic acid amplification by using protein binding probes made of DNA strands conjugated to protein affinity ligands. When a pair of probes bind to the same target protein, complementary nucleic acid sequences that are conjugated to each probe are brought into close proximity. The increased local concentration of the probes results in the formation of a stable dumbbell structure of the nucleic acids. The DNA dumbbell is readily amplifiable exponentially using techniques such as loop-mediated isothermal amplification. The PINDA assay eliminates the need for washing or separation steps, and is suitable for on-site applications. Detection of the model protein, thrombin, has a linear range of 10 fM-100 pM and detection limit of 10 fM. The PINDA technique is successfully applied to the analysis of dairy samples for the detection of β-lactoglobulin, a common food allergen, and Salmonella enteritidis, a foodborne pathogenic bacterium. The PINDA assay can be easily modified to detect other targets by changing the affinity ligands used to bind to the specific targets.

Cerebrovascular Endothelial Dysfunction: Role of BACE1.

Dysfunctional endothelium is increasingly recognized as a mechanistic link between cardiovascular risk factors and dementia, including Alzheimer disease. BACE1 (β-site amyloid-β precursor protein-cleaving enzyme 1) is responsible for β-processing of APP (amyloid-β precursor protein), the first step in the production of Aβ (amyloid-β) peptides, major culprits in the pathogenesis of Alzheimer disease. Under pathological conditions, excessive activation of BACE1 exerts detrimental effects on endothelial function by Aβ-dependent and Aβ-independent mechanisms. High local concentration of Aβ in the brain blood vessels is responsible for the loss of key vascular protective functions of endothelial cells. More recent studies recognized significant contribution of Aβ-independent proteolytic activity of endothelial BACE1 to the pathogenesis of endothelial dysfunction. This review critically evaluates existing evidence supporting the concept that excessive activation of BACE1 expressed in the cerebrovascular endothelium impairs key homeostatic functions of the brain blood vessels. This concept has important therapeutic implications. Indeed, improved understanding of the mechanisms of endothelial dysfunction may help in efforts to develop new approaches to the protection and preservation of healthy cerebrovascular function.

A model for predicting grain-boundary energy of refractory high-entropy alloys based on local element concentration

Refractory high-entropy alloys (RHEAs) exhibit exceptional high-temperature mechanical properties, and their structural stability is primarily influenced by grain boundaries (GBs). However, it remains challenging to accurately quantify the grain boundary energy (GBE) in RHEAs. Herein, we introduce a quantitative descriptor for point-to-point prediction of GBEs in RHEAs based on local element concentration and valence-electron numbers. Our results demonstrate that the role of the constituent elements on GBEs is primarily determined by their valence-electron numbers in RHEAs. These findings are derived from the cohesive energy and atomic structure of the elements within the framework of the broken-bond model, as well as the differential contributions of s-electrons and d-electrons. The model establishes a structure-property relationship between local element concentration and GBEs, with the prediction consistent with experimental and theoretical results, which is crucial for evaluating the GB stability of RHEAs and facilitating the development of high-performance alloys.