Browse Articles

High-pressure-induced phase transition in 2-amino-6-nitrobenzothiazole

In situ high-pressure synchrotron angular dispersive x-ray diffraction (ADXRD) experiments reveal a pressure-induced structural phase transition in the molecular crystal of 2-amino-6-nitrobenzothiazole (C7H5N3O2S, 2A6NBT) at ∼2.0 GPa. Furthermore, in situ high-pressure Fourier transform-infrared absorption and Raman spectroscopy experiments confirm the occurrence of this phase transition and clarify the structural evolution. The N–H⋯N and C–H⋯O hydrogen bonds (along the c-axis direction), as well as the N–H⋯O hydrogen bonds (along the b-axis direction) and van der Waals force, are enhanced due to interlayer compression. When the pressure reaches about 2.0 GPa, the collapse of the molecular layer space and the distortion of the N–H⋯N hydrogen bond make the hydrogen-bonding network rearrange, leading to the phase transition. Finally, the evolution of molecular stacking is further illustrated by first principles calculations. This study provides important insights for the development of new supramolecular polymorphism containing various types of hydrogen-bonded interactions.

Artificial transneurons emulate neuronal activity in different areas of brain cortex

Abstract Rapid development of memristive elements emulating biological neurons creates new opportunities for brain-like computation at low energy consumption. A first step toward mimicking complex neural computations is the analysis of single neurons and their characteristics. Here we measure and model spiking activity in artificial neurons built using diffusive memristors. We compare activity of these artificial neurons with the spiking activity of biological neurons measured in sensory, pre-motor, and motor cortical areas of the monkey (male) brain. We find that artificial neurons can operate in diverse self-sustained and noise-induced spiking regimes that correspond to the activity of different types of cortical neurons with distinct functions. We demonstrate that artificial neurons can function as trans-functional devices (transneurons) that reconfigure their behaviour to attain instantaneous computational needs, each capable of emulating several biological neurons.

Author Correction: Stress dynamically modulates neuronal autophagy to gate depression onset

Iron speciation and coordination in lithium borate glasses

This study explores the impact of Li2O content and Fe2O3 addition on the physical, optical, and structural properties of lithium borate glasses. Optical absorption spectra and XANES pre-edge features confirm the absence of significant Fe2+, indicating that iron is predominantly present as Fe3+. The optical absorption spectra exhibit characteristic features of Fe3+ ions, including a blue shift of the absorption edge as Li2O content increases, which is attributed to the conversion of BO3 to BO4 units. X-ray absorption spectroscopy reveals that Fe3+ ions are present in tetrahedral coordination, with the coordination number increasing at low Li2O concentrations. Raman spectroscopy further confirms that iron alters the connectivity of the borate network by disrupting superstructural borate units and forming links with boron atoms, particularly when Fe3+ occupies tetrahedral sites.

Seedless: on-the-fly pulse calculation for NMR experiments

Abstract NMR experiments require sequences of radio frequency (RF) pulses to manipulate nuclear spins. Signal is lost due to non-uniform excitation of nuclear spins resonating at different energies (chemical shifts) and inhomogeneity in the RF unavoidably generated by hardware over the sample volume. To overcome this, we present Seedless, a tool to calculate NMR pulses that compensate for these effects to enhance control of magnetisation and boost signal. As calculations take only a few seconds using an optimised GRadient Ascent Pulse Engineering (GRAPE) implementation, this now allows pulses to be generated in a few seconds, allowing them to be optimised for individual samples and spectrometers (“on-the-fly”). Each calculated pulse requires bands of chemical shift to be identified, over which one of 4 transforms will be performed, selected from a set that covers all commonly used applications. Using imaging experiments, we demonstrate our pulses effectively both increase the size of the coil volume and signal-to-noise in all experiments. We illustrate the approach by showing sensitivity gains in 1, 2 and 3D applications suitable for chemical and biological NMR. Seedless provides a means to enhance sensitivity in all pulse sequences in a manner that can be tailored to different samples and hardware being used.

Polaritronics: Energy and electron transport through polaritonic states

Polaritronics is a new branch of research that involves the study of polaritonic states and their applications in optoelectronic devices. Polaritonic states are distinguished by the inheritance of light and matter properties together. The cavity quantum electrodynamics picture of a two-level system interacting with a photon can define these states. Here, polaritonic devices perform classical operations through the collective interactions of an Avogadro number of molecules. By doing so, the newly formed states inherit a low effective mass and, therefore, behave similar to lightweight carriers of charge. At the same time, it possesses a collective coherence length as large as the mode volume of the cavity. This allows us to engineer hybrid devices that are specific in functions with quantization in both energy and momentum. This perspective gives glimpses of our views on polaritronics and its applications in quantum sensing and communication. We also pitch into understanding the limitations of such techniques along with the future outlook to obtain outperforming devices for real-world applications.

Single-atom Zr promoter boosts oxygen activation on ceria-supported Pt catalysts

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.