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At least 1,117 records · Page 62

Atomistic thermodynamics and kinetics of dicalcium silicate dissolution

Low-temperature cement manufacturing has garnered academic and industrial attention for its low environmental footprints. However, the sluggish hydration kinetics of the resultant cement affects their early-age strength development. This motivates fundamental studies to unravel the mechanistic picture of the dissolution process and discover science-informed pathways to accelerate hydration. Standard atomistic simulations seldomly exceed a microsecond making them impractical to study slow dissolution processes. We are using rare event sampling techniques, we provide the mechanistic picture of Ca 2+ ion dissolution from a kink site on the dicalcium silicate surface. The Ca 2+ ion dissolution is comprised of two sequential stages: breaking restraints from the kink sites to form a ledge adatom and detaching from the ledge/terrace adatom sites into the solution. The first and second stages feature free energy barriers of ~63 kJ/mol and ~ 29 kJ/mol respectively, making the first stage the rate-limiting step of the entire Ca 2+ dissolution kinetics. Using the reactive flux method, the rate and equilibrium constants for each reaction step are calculated, which yield the Ca 2+ ion activity of ~1.03 × 10 -5 . The diffusion calculations indicate that the surface effects lower the self-diffusion coefficient of Ca 2+ ions at the solid-water interface.

36 MATERIALS SCIENCE↗

Elucidating key reducing species beyond ions in hydrogen plasma smelting reduction of iron ore

Hydrogen plasma smelting reduction (HPSR) of iron ore has attracted significant attention over the past decade due to its high-temperature operation, rapid plasma mediated reduction kinetics, and simpler density-based separation of molten iron product, compared to H2-based solid-state reduction. All of these attributes enable processing of low-grade ores for downstream use in electric-arc furnaces, as virgin iron with low gangue content is required for high quality steel and improved furnace operation. While positive ions exist within the plasma arc, this work demonstrates that near the anodic ore surface, hydrogen radicals and vibrationally excited hydrogen species dominate and their densities correlate well with observed reduction rates. Species concentrations in the transferred plasma arc and at the plasma-ore interface are evaluated using coupled thermal plasma and near-wall non-equilibrium plasma models. The thermal plasma model is validated against experimental voltage data and spectroscopic measurements of plasma temperature and density for varying current inputs. Modeling of the near surface thermochemical non-equilibrium and micrometer scale anode sheath layer reveals, in addition to the expected H + , significant concentrations of ArH + and H$^+_3$ ions, typically not observed in thermal plasmas under thermodynamic equilibrium. Our results show that the inverted sheath structure at the anodic ore surface strongly suppresses reactive positive ion fluxes, while non-equilibrium electron-impact processes generate abundant hydrogen radicals and vibrationally excited species. These findings highlight the critical role of non-equilibrium effects in hydrogen arc-driven iron ore reduction and advance understanding beyond prevailing hypotheses centered on hydrogen ion-driven mechanisms.

08 HYDROGEN↗

Electromechanical memcapacitor model offering biologically plausible spiking.

In this article, we introduce a new nanoscale electromechanical device - a leaky memcapacitor - and show that it may be useful for the hardware implementation of spiking neurons. The leaky memcapacitor is a movableplate capacitor that becomes quite conductive when the plates come close to each other. The equivalent circuit of the leaky memcapacitor involves a memcapacitive and memristive system connected in parallel. In the leaky memcapacitor, resistance and capacitance depend on the same internal state variable, which is the displacement of the movable plate. We have performed a comprehensive analysis showing that several types of spiking observed in biological neurons can be implemented with the leaky memcapacitor. Significant attention is paid to the dynamic properties of the model. As in leaky memcapacitors the capacitive, leaking resistive, and reset functionalities are implemented naturally within the same device structure, their use will simplify the creation of spiking neural networks.

Zhang, Zixi↗

Isochronous and period-doubling diagrams for symplectic maps of the plane

Symplectic mappings of the plane serve as key models for exploring the fundamental nature of complex behavior in nonlinear systems. Central to this exploration is the effective visualization of stability regimes, which enables the interpretation of how systems evolve under varying conditions. While the area-preserving quadratic Hénon map has received significant theoretical attention, a comprehensive description of its mixed parameter-space dynamics remain lacking. This limitation arises from early attempts to reduce the full two-dimensional phase space to a one-dimensional projection, a simplification that resulted in the loss of important dynamical features. Consequently, there is a clear need for a more thorough understanding of the underlying qualitative aspects. This paper aims to address this gap by revisiting the foundational concepts of reversibility and associated symmetries, first explored in the early works of G.D. Birkhoff. We extend the original framework proposed by Hénon by adding a period-doubling diagram to his isochronous diagram, which allows to represents the system’s bifurcations and the groups of symmetric periodic orbits that emerge in typical bifurcations of the fixed point. A qualitative and quantitative explanation of the main features of the region of parameters with bounded motion is provided, along with the application of this technique to other symplectic mappings, including cases of multiple reversibility. Modern chaos indicators, such as the Reversibility Error Method (REM) and the Generalized Alignment Index (GALI), are employed to distinguish between various dynamical regimes in the mixed space of variables and parameters. These tools prove effective in differentiating regular and chaotic dynamics, as well as in identifying twistless orbits and their associated bifurcations. Additionally, we discuss the application of these methods to real-world problems, such as visualizing dynamic aperture in accelerator physics, where our findings have direct relevance.

43 PARTICLE ACCELERATORS↗

Engineering intricacies of implementing single-atom alloy catalysts for low-temperature electrocatalytic CO 2 reduction

Catalysts research for electrocatalytic CO 2 reduction reactions (CO 2 R) has undergone rapid growth in the last decade. Single-atom alloy catalysts (SAAs) featuring atomically dispersed metal dopants on host metal surfaces have shown promises in boosting CO 2 R yield by optimizing the structure and synergy of the catalytic metals at the atomic scale. Despite the exciting development of SAAs for CO 2 R in fundamental science, dedicated studies for its engineering implementation have been absent. We use this perspective to discuss our non-exhaustive engineering considerations for implementing SAAs for CO 2 R. Here, the perspective starts with a brief overview of the current research status for SAAs in CO 2 R, followed by focal points on structure uncertainties associated with catalyst manufacturing, catalyst layer degradation during reaction, and possibilities for SAAs to mitigate the salt precipitation issue at the device level. We hope our opinions will engage increasing attention toward the engineering catalysis research for applying SAAs to CO 2 R at scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Upcycling mixed cathode materials to high-energy-density LiFe 0.75 Mn 0.25 PO 4

To address the demand for next-generation cathode materials with high energy density, upcycling LiFePO 4 into LiFe 0.75 Mn 0.25 PO 4 has attracted considerable attention. Nevertheless, existing strategies have yet to achieve both morphology and full elemental recovery under mild ambient conditions. Here, we report an upcycling route that can address this issue by combining leaching and a high-temperature treatment process. The upcycled LiFe 0.75 Mn 0.25 PO 4 exhibits enlarged lattice spacing and a high discharge plateau, and it delivers an energy density of 563.7 Wh/kg, 40.3 Wh/kg higher than recycled LiFePO 4 , which indicates the high value of the proposed upcycling strategy. At 1 C, LiFe 0.75 Mn 0.25 PO 4 also exhibits excellent cycling stability of 91% over 700 cycles. Techno-economic analysis also indicates impressive economic and environmental benefits, including 10.4% less raw materials usage and 12.2% less energy consumption and wastewater generation. This work demonstrates a scalable and economic upcycling strategy and provides a promising pathway for sustainable battery upcycling compatible with industrial conditions.

LMFP↗

The effect of autoionization on the HBr + X 2 Π 3/2,1/2 state photoelectron angular distributions

A double-imaging photoelectron-photoion spectrometer and synchrotron radiation have been used to measure the HBr + X 2 Π 3/2 v + = 0, 1, 2 and the 2 Π 1/2 v + = 0 state photoelectron angular distributions, as characterized by the anisotropy parameter β , the total ion yield, and the threshold photoelectron spectrum. Particular attention has been focussed on the photon energy range between the 2 Π 3/2 and the 2 Π 1/2 spin–orbit components of the ground ionic state. This region encompasses Rydberg states, belonging to series converging onto the upper 2 Π 1/2 ionization limit, which may decay by autoionization into the 2 Π 3/2 ionization continuum. A detailed study has been performed on the effects of autoionization on the 2 Π 3/2 v + = 0 state photoelectron angular distributions. Furthermore, the observed energy dependent variations in the β -values exhibit a regular pattern that correlates with excitation into members of a very broad d-type Rydberg series. Additional rapid variations in the β -parameters, which occur over a narrow energy range, appear to coincide with sharp autoionizing Rydberg states belonging to s, p and d series. The present experimental results for the HBr + X 2 Π 3/2 v + = 0 state photoelectron anisotropy parameter are compared to previously reported theoretical predictions and to earlier studies of the Kr + 4p 5 2 P 3/2 state β -parameter. The threshold photoelectron spectrum of the X 2 Π 3/2 v + = 0 band exhibits partially resolved rotational structure. A simulation of this structure yields an ionization threshold of 11.6673 ± 0.0010 eV, which is consistent with previous measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Propane Dehydrogenation on Single-Site [PtZn4] Intermetallic Catalysts

Propane dehydrogenation (PDH) is a commercial propylene production technology that has received much attention, but high reaction temperature results in decrease of propylene selectivity and catalyst stability. This paper describes a single-site [PtZn 4 ] catalyst by assembling atomically ordered intermetallic alloy (IMA) as a selective and ultrastable PDH catalyst. The catalyst enables more than 95% propylene selectivity from 520 to 620 oC. No obvious deactivation is observed within 160-hours test, superior to PtSn/Al 2 O 3 and state-of-the-art Pt-based catalysts. Additionally, based on in situ X-ray absorption fine-structure, X-ray photoelectron spectroscopy measurements and density functional theory calculations, we reveal that the surface [PtZn 4 ] ensembles in PtZn IMAs serve as the key active site structures, wherein the geometry-isolated and electron-rich Pt1 site in [PtZn 4 ] ensembles readily promotes the first and second C–H cleavage of propane, but inhibits further dehydrogenation of surface-bounded propylene. This significantly improves the selectivity and stability by prohibiting coke side reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗

A thermodynamically consistent finite strain phase field approach to ductile fracture considering multi-axial stress states

Phase field models for ductile fracture have gained significant attention in the last two decades due to their ability in implicitly tracking the nucleation and propagation of cracks. However, most crack phase field formulations for elastoplastic solids focus only on the effects of plastic deformation, and do not consider the different multi-axial stress states that may arise in practical designs. In this work, a thermodynamically consistent phase field approach coupled with finite strain plasticity, considering multi-axial stress states is presented. In order to account for the coupling between plasticity and stress states, the Stress-Weighted Ductile Fracture Model (SWDFM) is utilized. The SWDFM represents a criterion for predicting ductile crack initiation under both monotonic and cyclic loadings based on histories of an internal plastic variable, stress triaxiality, and the Lode angle parameter. The excellent performance of the SWDFM for predicting ductile crack initiation motivates for its incorporation into a phase field approach for predicting both crack initiation and propagation through degradation of the fracture toughness. Moreover, based on the second law of thermodynamics, exact requirements are imposed on the rate at which the fracture toughness can evolve. Here, a novel function for degrading the plastic yield surface during the evolution of damage is introduced. This function, in line with experimental observations, leads to an accumulation of plastic deformation in damaged regions of a solid, and avoids numerical instabilities arising from concentrations of large plastic deformations in severely damaged regions. For validating the proposed model, results of computational simulations are compared to data from selected tests considering different multi-axial stress states. Comparisons of the numerical results with data from laboratory experiments demonstrate the capabilities of the proposed framework.

42 ENGINEERING↗

A subdivision-stabilized B-spline mixed material point method

Subjected to external loadings, polymeric materials, e.g., biological tissues, hydrogels, and elastomers, may undergo extreme, nearly incompressible, (self-)contact deformations. For numerical modeling employing mesh-based techniques such as the finite element method (FEM), these deformations pose significant challenges due to large distortions in the deformed geometry, accuracy issues stemming from volumetric locking effects, and increased computational cost from complex contact searches. As an alternative to mesh-based methods, the material point method (MPM), a continuum-based particle technique, is gaining attention for its ability to handle extreme distortions and capture no-slip contact without added cost. For nearly incompressible material behaviors, while mixed formulations can address locking effects by treating displacements and pressure as independent fields, they can suffer from numerical instabilities close to the incompressibility limit due to the violation of the inf-sup condition, leading to inaccurate nodal pressure solutions. Here we propose an efficient and stable mixed B-spline material point method with highest achievable regularity for quasi-compressible polymeric materials. Using the two-scale relation of B-splines, we introduce a subdivision-stabilization for the two-field mixed MPM and obtain numerically stable, oscillation-free nodal solutions with equal-order interpolations with optimal regularity. Building on the Eulerian-Lagrangian nature of MPM, a previously-converged solution framework is adopted to mitigate issues related to cell-crossing and numerical fracture artifact present in standard MPM. We assess the stability and accuracy of the developed mixed MPM at large deformations for soft materials through the benchmark Cook’s membrane problem. Additionally, we test the robustness of the proposed MPM by modeling several examples, including the compression and indentation of a circular block into a quasi-compressible substrate and the twisting deformation of a rectangular block. The findings demonstrate the MPM’s capabilities for modeling practical soft material applications.

36 MATERIALS SCIENCE↗

Real-time inference and extrapolation with Time-Conditioned UNet: Applications in hypersonic flows, incompressible flows, and global temperature forecasting

Neural Operators are fast and accurate surrogates for nonlinear mappings between functional spaces within training domains. Extrapolation beyond the training domain remains a grand challenge across all application areas. We present Time-Conditioned UNet (TC-UNet) as an operator learning method to solve time-dependent PDEs continuously in time without any temporal discretization, including in extrapolation scenarios. TC-UNet incorporates the temporal evolution of the PDE into its architecture by combining a parameter conditioning approach with the attention mechanism from the Transformer architecture. After training, TC-UNet makes real-time inferences on an arbitrary temporal grid. We demonstrate its extrapolation capability on a climate problem by estimating the global temperature for several years and also for inviscid hypersonic flow around a double cone. We propose different training strategies involving temporal bundling and sub-sampling. We demonstrate performance improvements for several benchmarks, performing extrapolation for long time intervals and zero-shot super-resolution time.

Deep learning↗

A MPET 2 -mPBPK model for subcutaneous injection of biotherapeutics with different molecular weights: From local scale to whole-body scale

Subcutaneous injection of biotherapeutics has attracted considerable attention in the pharmaceutical industry. However, there is limited understanding of the mechanisms underlying the absorption of drugs with different molecular weights and the delivery of drugs from the injection site to the targeted tissue. Here, we propose the MPET 2 -mPBPK model to address this issue. This multiscale model couples the MPET 2 model, which describes subcutaneous injection at the local tissue scale from a biomechanical view, with a post-injection absorption model at injection site and a minimal physiologically-based pharmacokinetic (mPBPK) model at whole-body scale. Utilizing the principles of tissue biomechanics and fluid dynamics, the local MPET 2 model provides solutions that account for tissue deformation and drug absorption in local blood vessels and initial lymphatic vessels during injection. Additionally, we introduce a model accounting for the molecular weight effect on the absorption by blood vessels, and a nonlinear model accounting for the absorption in lymphatic vessels. The post-injection model predicts drug absorption in local blood vessels and initial lymphatic vessels, which are integrated into the whole-body mPBPK model to describe the pharmacokinetic behaviors of the absorbed drug in the circulatory and lymphatic system. We establish a numerical model which links the biomechanical process of subcutaneous injection at local tissue scale and the pharmacokinetic behaviors of injected biotherapeutics at whole-body scale. With the help of the model, we propose an explicit relationship between the reflection coefficient and the molecular weight and predict the bioavalibility of biotherapeutics with varying molecular weights via subcutaneous injection. The considered drug absorption mechanisms enable us to study the differences in local drug absorption and whole-body drug distribution with varying molecular weights. This model enhances the understanding of drug absorption mechanisms and transport routes in the circulatory system for drugs of different molecular weights, and holds the potential to facilitate the application of computational modeling to drug formulation.

59 BASIC BIOLOGICAL SCIENCES↗

Recent advances in single-atom catalysts and single-atom alloys: opportunities for exploring the uncharted phase space in-between

Single-atom catalysts (SACs) have gained significant world-wide attention for exhibiting distinct reactivity and selectivity for important reactions, while utilizing precious metals at the ultimate limit of efficiency. SACs involving reducible oxide supports are good catalysts for oxidation reactions, and metal-acid site pairs enable Csingle bondC bond formation, but SACs can deactivate by sintering under reducing conditions. On the other hand, single-atom alloys (SAAs) are robust towards sintering and exhibit exceptional catalytic performance for a wide range of reactions under reducing conditions but can deactivate under oxidizing environments. Therefore, there is tremendous opportunity to explore and exploit catalytic reactivity between the SAC and SAA extremes. Furthermore, this paper focuses on recent advances in both fields and highlights prospects for future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A review of emerging photoinduced degradation methods for per- and polyfluoroalkyl substances in water

The remediation of per- and polyfluoroalkyl substances (PFAS) in water continues to garner significant attention due to their environmental persistence and adverse health effects. Among the various PFAS remediation methods, photoinduced approaches have recently emerged as promising techniques for the degradation of these persistent contaminants. However, many questions remain unanswered regarding the detailed mechanisms in these photoinduced methods as well as the best ways to leverage these approaches for PFAS degradation. In this review, we provide an update on recent experimental and theoretical developments in photoinduced PFAS degradation techniques over the past 2–5 years. We conclude with a perspective of promising research directions in this vibrant area and give recommendations on future experimental and computational approaches needed to further advance these photoinduced remediation capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical reduction of per- and polyfluorinated alkyl substances (PFAS): is it possible? Applying experimental and quantum mechanical insights from the reductive defluorination literature

Remediation of per- and polyfluorinated alkyl substances (PFAS) in global water systems is a critical human and environmental health challenge facing society. PFAS consumption is associated with a litany of adverse health effects, and our knowledge of these dangers is still evolving. Current techniques to remove PFAS from water include adsorption to media (e.g. granular activated carbon, ion-exchange resin), nanofiltration, and reverse osmosis. However, these processes create a concentrated PFAS residual that requires further management. Destructive techniques are therefore needed to detoxify these residuals. Oxidative techniques have garnered the most attention (e.g. supercritical water oxidation, electrochemical oxidation) but are energy intensive and potentially form toxic by-products. As an alternative, several groups have researched advanced reduction processes that form aqueous electrons, but these processes are still chemical and energy intensive (e.g. ultraviolet/SO 3 2− , electron beam). This concise review therefore focuses on whether electrochemical reduction — a chemical-free, modular process — could be technically feasible for PFAS destruction.

King, Jacob F.↗

Recent developments in Pt–Co catalysts for proton-exchange membrane fuel cells

Development of Pt-based oxygen reduction reaction catalysts with high efficiency and high durability is central to the application of proton-exchange membrane fuel cell systems. Pt–Co bimetallic catalysts have drawn extensive attention owing to their capability of delivering high performance and long lifetime for fuel cell applications including light-duty and heavy-duty vehicles. However, further improvements in durability and performance are needed to meet market requirements. To fully exploit the potential of Pt–Co catalysts, new insights into the relationship between catalyst properties and fuel cell performance and durability are needed, and more effective methods to tailor the features of Pt–Co catalysts need to be developed. This review provides a summary and perspective on recent efforts, including work on customizing the Pt shell and Pt:Co ratio, tailoring the crystal structure, and improving carbon support properties, with a particular emphasis on mechanisms leading to enhancement of mass activity, power density, and durability in membrane electrode assembly testing.

25 ENERGY STORAGE↗

Nonflammable Nonaqueous Electrolytes for Lithium Batteries

As the energy density of state-of-the-art lithium (Li)-ion batteries (LIBs) increases, the safety concern of LIBs using liquid electrolytes is drawing increasing attention. Flammability of electrolytes is a critical link of the overall safety performance of LIBs and Li metal batteries. For this reason, intensive efforts have been devoted to suppressing the flammability of liquid electrolytes. In this short review, the common approaches to reduce the flammability of the liquid electrolytes will be summarized. The advantages and limitations of these approaches will also be discussed.

Jia, Hao↗