Browse Articles

Redox chemistry meets semiconductor defect physics

Understanding how the electronic structure of electrodes influences electrocatalytic reactions has been a longstanding topic in the electrochemistry community, with predominant attention paid to metallic electrodes. In this work, we present a defect physics perspective on the effect of semiconductor band structure on electrochemical redox reactions. Specifically, the Haldane–Anderson model, originally developed to study multiple charge states of transition-metal defects in semiconductors, is extended to describe electrochemical redox reactions by incorporating the solvent effect, inspired by the Holstein model. The solvent coordinate and the actual charge on the redox species in reduced and oxidized states are assumed to be in instant equilibrium, and the transitions between these states are defined by the framework of Green’s function. With these treatments, the charge state transitions are handled in a self-consistent manner, and the implications of charge self-consistency (or, equivalently, charge self-regulation) on electrocatalysis can be investigated explicitly. We first confirm that this self-consistent approach is essential to accurately depict the hybridization effect of band structure by comparing the model-calculated ionization potential and electron affinity, as well as the redox potential of the species, with those obtained from density functional theory calculations. Next, we illustrate that the effect of charge self-consistency is key to obtaining a fuller understanding of the catalytic activities of semiconductor electrodes and the source of asymmetry in reorganization energies, which is often observed in prior ab initio molecular dynamics simulations. In addition, we discuss how band structure impacts redox reactions in the strong coupling limit. Finally, we compare our work with other relevant studies in the literature.

Impaired mitochondria-initiated crosstalk with lysosomes reciprocally aggravates mitochondrial defect through LManVI

Ne*(3P2,0) + CO chemi-ionization reactions: Atomic alignment and molecular orientation effects

The present study exploits the recent formulation of the optical potential that provided an internally consistent representation of the interaction between Ne*(3P2,0) + CO reagents and Ne + CO+(X2Σ, A2Π) products. The coupling between neutral entrance and ionic exit reaction channels, to isolate novel stereo-dynamic effects on chemical reactivity promoted by both atomic alignment and molecular orientation, has been proposed within the adopted theoretical approach. The control exhibited by such effects on each microscopic passage from reagents to products in defined initial and final quantum states has been characterized. In particular, the collisions of reagents in selected quantum states lead to the formation of the reaction transition state in specific configurations that open the passage to ionic products in the ground and in the first excited electronic state. Therefore, the characterization of state-to-state passages from reactants to products, often unknown, appears to be of great general interest for the stereo-dynamic control of these and many other elementary processes.

Gut microbiota mitigate the reproductive toxicity of silver nanoparticles through thiamine-derived metabolites

Comparative analysis of ferroelectric domain wall motion under cycling stress of HfZrO2 fabricated by thermal and plasma-enhanced atomic layer depositions

Ferroelectric HfZrO2 (HZO) formed by atomic layer deposition (ALD) has been widely studied due to its composition control of material contents and stable ferroelectric properties. However, the effect of various ALD methods on ferroelectric switching dynamics has not been thoroughly investigated. We conduct a comparative study on the differences in ferroelectric (FE) domain wall motion under electrical cycling stress between two ALD methods: thermal ALD (THALD) and plasma-enhanced ALD (PEALD). The extraction of activation energy from fatigue rate and FE switching speed analysis results shows that PEALD HZO has inherent defects during the deposition step, and the FE switching speed of PEALD HZO degraded faster under cycling stress than that of THALD HZO. XPS analysis results show that under cycling stress, oxygen vacancies are formed faster in PEALD than in THALD HZO. Furthermore, dynamic domain phase analysis shows that the electric fields required for switching in the relaxation to creep (E1) change in THALD HZO by +46%, while the electrical fields required for the transition from creep to flow (E2) rarely change under the cycling stress. However, E1 and E2 values of PEALD HZO change by +19% and −10%, respectively, depending on the cycling stress.

Time-resolved chemically-selective spectroscopic investigation of the redox reaction between hematite and aluminium

Abstract Thermite reactions –highly energetic redox processes between a metal and an oxide—are used in welding, propulsion, and the fabrication of advanced materials. When reduced to the nanoscale, these reactions exhibit enhanced energetic performance, but their ultrafast dynamics remain poorly understood. Gaining insight into charge transfer during these processes is essential for advancing applications in energy conversion and materials design. Here we show that the reaction between aluminium and hematite, a common iron oxide, can be tracked with femtosecond resolution using extreme ultraviolet (EUV) time-resolved absorption spectroscopy at the Fe M 2,3 and Al L 2,3 edges. By exciting the system with an ultrashort optical pulse and probing element-specific absorption changes, we observe an early spectral shift that reveals the formation of localized charge carriers (polarons). Comparing samples with different supporting substrates highlights ultrafast electron transfer from aluminium to hematite. These results demonstrate an approach to investigating charge flow in energetic materials and provide a basis for studying fast chemical reactions with chemical specificity.

Unraveling the impact of interaction types on phase separation of intrinsically disordered protein chains

Biomolecular condensates, formed through liquid–liquid phase separation (LLPS) of biomolecules, play essential roles in various cellular processes. Despite significant advances in understanding the driving forces behind LLPS, the specific impact of different types of interactions on phase separation behaviors remains underexplored. In this study, we utilized dissipative particle dynamics simulations to analyze the network structure, material properties, and dynamic behavior of intrinsically disordered protein (IDP) chains under hydrophobic and specific interactions with varying strengths. Our results demonstrate that while both hydrophobic and specific interactions can lead to phase separation, they produce distinct behaviors. Hydrophobic interactions promote the formation of more dynamic clusters, whereas specific interactions result in more stable condensates due to longer bond lifetimes and reduced mobility among IDP chains. Notably, the viscosity and diffusion coefficients of the condensates varied significantly between the two types of interactions, reflecting their differing material properties. Furthermore, in the case of alternating chains, specific interactions were not sufficient to induce phase separation structures. Overall, this study highlights the critical role of interaction types in shaping the phase separation behaviors of IDPs, providing valuable insights for fine-tuning the properties of biomolecular condensates.

SuperSalt: equivariant neural network force fields for multicomponent molten salts system

Bath-engineering technique for criticality-based quantum metrology with amplitude noise

Quantum critical systems are extremely sensitive to parameter variation near the critical point. Moreover, the derivatives with respect to the order parameter may exhibit divergence. This quantum criticality is widely utilized to enhance the performance of quantum metrology. In this study, we take the dissipative quantum Rabi model (QRM) as an example and use the bath-engineering technique to simulate the dissipative QRM to explore the impact of the quantum criticality on the quantum metrology under dissipation. We numerically calculate the dynamics of the inverse variance of the dissipative QRM around the critical point by using the quantum-simulation method and compare our results with those obtained by the numerically exact hierarchical equations of motion (HEOM). Our simulations show that in the case of the strong dissipation or the high temperature, the precision does not exhibit divergence when approaching the point of the quantum phase transition, and the enhancement of quantum metrology by quantum criticality is relatively limited. More importantly, the quantum-simulation method based on the bath-engineering technique can accurately simulate the dynamical evolution of the critical system and consumes significantly fewer resources as compared with the HEOM. Thus, it can be an alternative solution for investigating the dynamical evolution of larger critical systems for quantum metrology.

Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics

Abstract Targeting cancer-specific HLA-peptide complexes is a promising approach in immunotherapy. Mutated neoantigens are excellent targets due to their immunogenicity and cancer-specificity. Mass spectrometry (MS)-based immunopeptidomics guides the selection of naturally presented immunogenic targets within the immunopeptidome, refining immunogenicity predictions. Implementation in clinical settings, however, must achieve global depth, capturing the entirety of the immunopeptidome, maintain high target sensitivity, and cater to scarce sample inputs and short turnaround time. Here, we present NeoDiscMS, an extension of NeoDisc that enables the acquisition of personalized immunopeptidomics data. Leveraging next-generation sequencing-guided real-time spectral acquisitions, NeoDiscMS maximizes sensitivity with minimal loss of global depth. Designed for effectiveness and ease of use, with minimal effort required for implementation, NeoDiscMS enhances the detection of peptides derived from tumor-associated antigens by up to 20% and improves confidence in neoantigen identification compared to the gold standard method. NeoDiscMS advances personalization in clinical antigen discovery with more confident neoantigen detection and easy implementation.

Alternative escape for run-and-tumble particles from a potential with spatially random perturbations

The dynamics of self-propelled particles are naturally affected by both spatial and temporal perturbations due to the disordered landscapes and thermal fluctuations in their living environment. Here, we investigate the escape properties of run-and-tumble particles, a special kind of self-propelled particle characterized by a constant self-propulsion speed and random tumbling of heading direction, from a random potential that combines an asymmetric smooth component with spatially random perturbations (SRPs). The statistical reversal of escape direction is primarily governed by both self-propulsion speed and tumbling rate. SRPs tend to enhance the escape probability over the higher barrier relative to the base smooth potential in most cases and remarkably reduce the peak of the first passage time distributions in both escape directions, resulting in long tails. Specifically, we find that the logarithm of mean first passage time shows a linear dependence on the intensity and correlation length of SRPs. However, in contrast to the significant influence on the escape process, the SRPs have a weak effect on the overall shape of the probability density function except for some small-scale fluctuations. Our results support the oriented transportation and sorting of active particles with disordered substrates.

RIPK1 kinase drove brain microvascular endothelial cells death and blood-brain barrier disruption in neonatal Escherichia coli meningitis

How important is the dielectric constant in water modeling? Evaluation of the performance of the TIP4P/<i>ɛ</i> force field and its compatibility with the Joung–Cheatham NaCl model

Efficient large-scale computer simulations of aqueous solutions require the use of accurate but simple empirical force fields for water. However, the complexity of these systems evidences the difficulties in describing solution properties without due account of polarization. Different strategies to remedy this problem are parameterizing water force fields to the dielectric constant or charge scaling of solvated ions. In this work, we compare results from TIP4P/ɛ and OPC models, which are parameterized to predict the dielectric constant, with results from TIP4P/2005, which is closer in spirit to the charge scaling strategy. The performance of the models is rated according to the Vega–Abascal benchmark. Our results show that TIP4P/ɛ and TIP4P/2005 perform equally well, with the OPC model lying significantly behind. TIP4P/ɛ can predict bulk phase properties (transport properties, thermal expansion coefficients, and densities) of both liquid water and ice polymorphs, but also surface tensions, with an accuracy very similar to TIP4P/2005, while performing very well for dielectric constants over a wide range of pressures and temperatures. On the other hand, TIP4P/2005 provides a better description of phase boundaries, including liquid–vapor and freezing transitions. However, the accurate prediction of dielectric constants allows TIP4P/ɛ to describe densities of NaCl solutions for models parameterized to their crystal and melt properties only. This is achieved without the need to rescale charges, modify the Lorentz–Berthelot rule, or tune the ion’s Lennard-Jones parameters. Our findings hinge on the significance of dielectric constants as a target property and show that a robust parameterization can be achieved without invoking the concept of charge scaling.

Harnessing screw dislocations in shell-lattice metamaterials for efficient, stable electrocatalysts

Abstract Developing highly active and robust catalysts remains a critical challenge for the industrial realization and implementation of nitrate reduction. Here, we proposed a screw dislocation-mediated three-dimensional (3D) printing strategy for scalable, integrated manufacturing of metamaterial catalysts. Specifically, screw dislocation was introduced into the 3D printing process to mediate the simultaneous synthesis of 3D architecture and chiral surface nanostructures, effectively eliminating conventional heterointerfaces. Additionally, severe strain effects induced by dislocation multiplication in curved spaces enhance intrinsic catalytic activity by promoting NO3 − adsorption and lowering the energy barrier of NO3 −-to-NH3 conversion. Consequently, the FeCoNi dual-scale shell-lattice metamaterials with high dislocation density achieve a Faraday efficiency of 95.4%, an NH3 yield rate of 20.58 mg h−1 cm−2, and long-term stability exceeding 500 hours. A flow-through electrolyzer coupled with an acid absorption unit successfully produced NH4Cl fertilizer products. Our work opens a new perspective for advancing 3D printing technology in catalysis applications.

Modeling interconnected minerals markets with multicommodity supply curves: examining the copper-cobalt-nickel system

Abstract Demand for many of the metals used in the energy transition is expected to grow rapidly. Many of these are by-products, often considered critical because their production responds weakly to prices and is instead tied to the economics of the host mineral. We present a model of prices and production for jointly produced commodities that accounts for interconnectivity between host and by-product markets at the mine level. We demonstrate this method using the copper–cobalt–nickel system, in which approximately 99% of cobalt is a by-product of copper or nickel mining. Our results show that the model more accurately captures the economic benefits of diversified mine outputs than previous approaches. Furthermore, changes in demand drivers for any two commodities produce non-linear effects on production and price. We challenge the prior best-practice assumption that cobalt cannot impact the copper or nickel markets. Recognizing the importance of both copper and cobalt for future electrification, we emphasize that incentivizing the copper industry to reduce cobalt supply risks could inadvertently undermine copper supply.

Highly efficient non-relativistic Edelstein effect in nodal p-wave magnets

Abstract The origin and efficiency of charge-to-spin conversion, known as the Edelstein effect (EE), has been typically linked to spin-orbit coupling mechanisms, which require materials with heavy elements within a non-centrosymmetric environment. Here we demonstrate that the high efficiency of spin-charge conversion can be achieved even without spin-orbit coupling in the recently identified coplanar p-wave magnets. The non-relativistic Edelstein effect (NREE) in these magnets exhibits a distinct phenomenology compared to the relativistic EE, characterized by a strongly anisotropic response and an out-of-plane polarized spin density resulting from the spin symmetries. We illustrate the NREE through minimal tight-binding models, allowing a direct comparison to different systems. Through first-principles calculations, we further identify the nodal p-wave candidate material CeNiAsO as a high-efficiency NREE material, revealing a  ~ 25 times larger response than the maximally achieved relativistic EE and other reported NREE in non-collinear magnetic systems with broken time-reversal symmetry. This highlights the potential for efficient spin-charge conversion in p-wave magnetic systems.

Galectin-3-integrin α5β1 phase separation disrupted by advanced glycation end-products impairs diabetic wound healing in rodents

Constructing concepts without feedback: An empirical investigation of how relational information affects multidimensional concept completion behavior in an unsupervised task

The ability of humans to intentionally learn, without feedback, unidimensional stimulus relations in categorization tasks has been empirically established over the past two decades. However, whether observers can learn more complex multidimensional stimulus relations across these unsupervised tasks has not yet been determined. We demonstrate across an unsupervised concept completion experiment that the failure to observe multidimensional learning in previous experiments may be attributable to factors such as increased stimulus or task complexity. We posit that concept completion is related to category learning in that it reveals the underlying tendencies that are associated with some categories being easier to learn than others. In our experiments, we found observers readily learned to complete a two-dimensional exclusive-or concept, evidenced by an increase in object selection as the task progressed with a decrease in choice response times. We also found that observers readily learned to complete, as evidenced by similar patterns in object selection and response time behavior, a more complex three-dimensional stimulus relation that has empirically been associated with large amounts of categorization errors in related supervised classification tasks. Accordingly, we tested two existing formal models to determine their ability to account for our observations: namely, the Simplicity Model and the Generalized Representational Information Theory (GRIT) basic measure. We show how relational information processing as expounded in GRIT accounts for the observed completion behavior. Overall, our findings show how people gravitate, in a gradual and composite fashion, towards minimizing the perceived complexity of categories as much as possible.

Wasting and short-term outcomes among children with cancer in resource-limited settings: A prospective study in Uganda

Background Wasting contributes to poor treatment outcomes in children with cancer, especially in low-resource settings. In these settings, there is inadequate routine, systematic assessment of the wasting status of children with cancer. Wasting is diagnosed based on visual evidence, with a subjective bias for recognition. This study determined the prevalence of wasting at diagnosis among children with cancer at the Uganda Cancer Institute (UCI) and the diagnostic accuracy of “visible wasting” in identifying children with wasting as measured by anthropometric indices, and identified predictors of 6-months negative outcomes. Methods We assessed the wasting status at diagnosis, diagnostic accuracy of visible wasting, and 6-month outcomes of children newly diagnosed with cancer at the UCI (both ambulatory and hospitalized) between April 2022 and March 2023. Data were analyzed using SPSS version 26. Descriptive, bivariate, multivariate, and survival analyses were performed as appropriate. Statistical significance was determined at P-value&lt;0.05. Results One hundred forty-four children with cancer, with a median age of 10.0 years (interquartile range [IQR] 4.0–14.0 years), were included. The majority, 89 (61.8%), had solid tumor, whereas 55 (38.2%) had hemato-lymphoid malignancies. Thirty-two (22.2%) of the participants had visible wasting, and 57 (39.6%) were wasted based on anthropometric measurements, 32 (56.1%) of whom showed no visible wasting. Visible wasting had a low sensitivity of 43.9% (95% CI 30.7–57.6) – ROC 0.32 (95% CI 0.23–0.42), with a false negative rate of 56.1%. Overall, visible wasting missed up to 80.6% (25/31) of children with moderate wasting and 26.9% (7/26) with severe wasting. Twenty-one (14.6%) of the patients died, 8 (38.1%) of whom were deemed to be wasted, and 15 (71.4%) had anthropometrically-defined wasting. Neutropenia occurred in 20.8% (n = 30) of the participants and sepsis in 13.9% (n = 20). In univariate analyses, wasted patients were more likely to develop neutropenia (OR 3.63; 95% CI 1.56–8.42; p = 0.003), sepsis (OR 4.50; 95% CI 1.65–12.29; p = 0.003), and die (OR 3.08; 95% CI 1.15–8.28; p = 0.026). Conclusion Wasting at diagnosis is a common problem among children with cancer in this resource-limited setting and is associated with increased risks of neutropenia, sepsis, and mortality. Reliance on visible wasting as a marker for wasting misses other wasted children, some of who may be malnourished and at risk of poor outcome. For accurate categorization of wasting, all patients should undergo a standard anthropometric evaluation.

Mobile-collector capture of particles in a chaotic flow

Removing dispersed material, such as pollutants, from dynamic fluid environments like the ocean or the atmosphere is challenging when the flow is chaotic. Here the capture of passive tracer particles by a mobile collector (MC) is studied in a model two-dimensional chaotic flow with vortices. Four simple capture strategies for determining the MC direction are considered, all of which rely on periodic measurement of the local particle distribution. The ultimate success of a strategy depends on its associated motion and detection parameters as well as the underlying fluid flow. When the flow is fully chaotic or the relative velocity of the MC is large, the four strategies exhibit nearly equal effectiveness. However, when the flow is less chaotic and the relative MC velocity is small, the collector can become trapped in or outside of a vortex. Changing the particle detection parameters can prevent trapping, which improves capture. In the absence of trapping and for both high and low relative velocities of the MC, a scaling analysis explains the dependence of the capture rate on the relevant dimensionless variables based on timescales for the mobile collector and the underlying flow. For a wide range of parameters and all four capture strategies, the capture timescale depends linearly on a combination of the characteristic kinematic timescale related to the relative motion of the collector and the gradient timescale related to the underlying flow field, confirming that the capture process is properly characterized.