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Design and analysis of terahertz trilayer achromatic grating metasurface wave plate

‘Targeted and belittled’: scientists at US environmental agency speak out as layoffs begin

Tracking and controlling dissociative ionization of formic acid molecules by femtosecond laser fields

We present an experimental investigation aimed at tracking and controlling the dissociative ionization of formic acid molecules using intense femtosecond laser pulses. The resulting ionic products, formyl and hydroxyl radicals, are measured in coincidence. By analyzing the kinetic energy release spectra of these ionic radicals as a function of the time delay between the pump and probe laser pulses, we identify two distinct formation pathways. Furthermore, we show the manipulation of the spatial emission characteristics of these ionic radicals by adjusting the relative phase of spatiotemporally shaped two-color femtosecond laser fields. These findings offer valuable insights into the fragmentation dynamics of formic acid molecules in femtosecond laser pulses.

Cold seeps are potential hotspots of deep-sea nitrogen loss driven by microorganisms across 21 phyla

Shielding effect of moving SiC ceramic fragments on jets

Silicon carbide (SiC) is a promising candidate material as a component in lightweight and high-performance protective systems. However, its performance subjected to high-speed ejecta remains unclear. To this end, MD (molecular dynamics) simulations were utilized to investigate the jets induced damage and fragmentation of SiC ceramic. The effect of moving speed of SiC as a target and fragment size on the overall impact resistance were revealed. Then, we developed a damage efficiency criterion for the dispersion effect of the target on the jet and assessed the damage effectiveness at various target moving speeds. It is found that the moving speed of the fractured target significantly affects the effectiveness of resistance to ejecta. An optimized strategy to achieve better resistance to jets was proposed accordingly. Our work provides new insights into the damage and fragmentation of SiC and would benefit for the design of the protection system.

Daidzin improves the cisplatin chemosensitivity for osteosarcoma via binding to β-catenin protein and suppressing the wnt pathway

Daily briefing: Scientists use AI to design life-like enzymes from scratch

Freezing, melting, and the onset of glassiness in binary mixtures

We clarify the relationship between freezing, melting, and the onset of glassy dynamics in a prototypical glass-forming mixture model. Our starting point is a precise operational definition of the onset of glassiness, as expressed by the emergence of inflections in time-dependent correlation functions. By scanning the temperature–composition phase diagram of the mixture, we find a disconnect between the onset of glassiness and freezing. Surprisingly, however, the onset temperature closely tracks the melting line, along which the excess entropy is approximately constant. At fixed composition, all characteristic temperatures display nonetheless similar pressure dependencies, which are very well predicted by the isomorph theory. While our results rule out a general connection between thermodynamic metastability and glassiness, they call for a reassessment of the role of crystalline precursors in glass-forming liquids.

Single-cell analysis identifies Ifi27l2a as a gene regulator of microglial inflammation in the context of aging and stroke in mice

Neutron standing wave at total reflection and neutron bandpass filter using periodic superlattices

The quantum mechanical phenomena of frustrated total reflection of neutrons in periodic ternary (Ti/Ni/Si) superlattices have been investigated using the polarized neutron reflectivity (PNR) technique. We have experimentally demonstrated that periodic ternary superlattices can efficiently produce a resonant enhanced coherent neutron source with a smaller cross-sectional size, which can probe large-scale inhomogeneities in condensed matter. Using PNR experiments and simulations, we have also studied the applications of periodic ternary superlattices for a possible neutron bandpass filter in the wavelength ranges of 1–10 Å. A comparison of neutron bandpass filter applications for the periodic ternary systems with periodic binary systems is also carried out. The PNR results revealed that the periodic ternary superlattices, which show quantum resonant behaviors, provide a smaller bandwidth for the neutron bandpass filter applications. Our measurements suggest that such periodic superlattices may, therefore, be used for making neutron beams suitable for applications in biochemical and nanoscience research, as well as for studying the fundamental quantum behaviors of neutron beams.

Synthesis of divanillic acid-based aromatic polyamides with linear and branched side-chains and the effect of side-chain structure on thermal and mechanical properties

Why I retracted part of my PhD dissertation

Non-ideal mixing of lipids: A molecular dynamics perspective

Lipid membranes have complex compositions, and modeling the thermodynamic properties of multi-component lipid systems remains a remote goal. In this work, we attempt to describe the thermodynamics of binary lipid mixtures by mapping coarse-grained molecular dynamics systems to two-dimensional simple fluid mixtures. By computing and analyzing the density fluctuations of this model lipid bilayer, we determine the numerical value of the quadratic coupling term appearing in a model of regular solutions for the dipalmitoylphosphatidylcholine–dilinoleoylphosphatidylcholine pair of lipids at three different compositions. Our methodology is general and discussed in detail.

Non-Hermitian Dirac cones with valley-dependent lifetimes

Abstract Relativistic quasiparticles emerging from band degeneracies in crystals play crucial roles in the transport and topological properties of materials and metamaterials. Quasiparticles are commonly described by Hermitian Hamiltonians, with non-Hermiticity usually considered detrimental. In this work, we show that such an assumption of Hermiticity can be lifted to bring quasiparticles into non-Hermitian regime. We propose a concrete lattice model containing two Dirac cones with valley-dependent lifetimes. The lifetime contrast enables an ultra-strong valley selection rule: only one valley can survive in the long-time limit regardless of the excitation, lattice shape and other details. This property leads to an effective parity anomaly with a single Dirac cone and offers a simple way to generate vortex states. Additionally, extending non-Hermitian features to boundaries generates valley kink states with valley-locked lifetimes, making them effectively unidirectional and more resistant against inter-valley scattering. All these phenomena are experimentally demonstrated in a non-Hermitian electric circuit lattice.

Phase-separated amorphous Si2BN: A computational study

This study investigates the atomic structure, bonding, and electrical and mechanical properties of amorphous silicon boron nitride (a-Si2BN) using ab initio molecular dynamics simulations. The simulations reveal a distinct phase-separated structure comprising Si-rich and BN-rich domains. BN layers are embedded within the amorphous Si matrix, with only a few bridging atoms linking these regions. The Si-rich region exhibits topological similarities to amorphous silicon, albeit with notable structural distortions. Electronic structure calculations indicate semiconducting behavior with a small bandgap, while mechanical property analysis shows a moderate bulk modulus and Young's modulus, achieving a balance between rigidity and elasticity. These findings position a-Si2BN as a promising material for advanced applications, including flexible electronics, high-temperature semiconductors, and energy storage devices. While the proposed structure is currently hypothetical, its potential experimental realization could open new avenues in material design for emerging technologies.

The media morphosis of science communication during crises

Abstract Effective science communication is crucial in informing citizens in times of crisis. The ICT-driven metamorphosis of the media industry (media-morphosis) has facilitated the shift from a rather one-directional information deficit model in science communication to a more bidirectional communication corresponding to a dialogue model. Little is known about the preferences for social media communication from the supply side of institutional and scholarly communication. Analyzing survey data from nearly 8,700 scientists, we compared their preferences for press media and social media, proxies of traditional centralized communication channels and modern decentralized channels, respectively. Our empirical results show that trust in governments and prioritizing access to all perspectives on the crisis are important factors that influence scientists’ preferences regarding forms of communication. Trust favors centralized systems, while social media serves as an alternative in contexts lacking trust in politics. Prioritizing the diffusion of different perspectives drives a shift to stated preferences for decentralized communication systems. We also show that scientists’ stated preferences for communication systems depend on the socio-political context.

NASA embraced diversity. Trump’s DEI purge is hitting space scientists hard

Insights into the impact of small anionic additives on Mg-silicate hydrate nucleation

Magnesium silicate (MS) cement, which uses magnesium silicate hydrate (M-S-H) as its primary binding phase, is a promising low-carbon alternative to Portland cement. However, the slow dissolution of MgO limits the release of Mg ions, which is critical for the formation of M-S-H. To address this issue, solubilizers that complex Mg2+ and promote MgO dissolution have been proposed, provided that they do not significantly hinder M-S-H formation. This study systematically examined the effects of four anionic additives—acetate, citrate, orthophosphate, and carbonate—on M-S-H nucleation and early growth, developing a highly reproducible crystallization scenario. The observed reduction in supersaturation at the nucleation point for specific additive concentrations suggests that Mg-anion complexes may play an active role in M-S-H nucleation, potentially allowing M-S-H to form at lower supersaturation levels, which could be beneficial for MS cement applications. However, as shown here, additives such as citrate, while not inhibiting nucleation, can significantly slow the growth of M-S-H, potentially compromising the strength development of MS cement. Among the additives studied, moderate concentrations of phosphate and carbonate show the most promise, as they have minimal effects on the formation process while potentially reducing the supersaturation for M-S-H nucleation. Although further research is necessary to fully understand the effects of these anions, this study provides valuable insights into their impact on M-S-H nucleation and early growth.

Structural insights into human brachyury DNA recognition and discovery of progressible binders for cancer therapy

Abstract Brachyury is a transcription factor that plays an essential role in tumour growth of the rare bone cancer chordoma and is implicated in other solid tumours. Brachyury is minimally expressed in healthy tissues, making it a potential therapeutic target. Unfortunately, as a ligandless transcription factor, brachyury has historically been considered undruggable. To investigate direct targeting of brachyury by small molecules, we determine the structure of human brachyury both alone and in complex with DNA. The structures provide insights into DNA binding and the context of the chordoma associated G177D variant. We use crystallographic fragment screening to identify hotspots on numerous pockets on the brachyury surface. Finally, we perform follow-up chemistry on fragment hits and describe the progression of a thiazole chemical series into binders with low µM potency. Thus we show that brachyury is ligandable and provide an example of how crystallographic fragment screening may be used to target protein classes that are difficult to address using other approaches.

Unified neural network model for predicting optical responses in gold nanostructures

In this paper, we present a deep neural network model capable of simultaneously predicting the optical transmittance spectra of three distinct gold nanostructures: nanodisks, truncated cones, and nanocones. Our model achieved a mean squared error loss as low as 0.0015. By systematically varying geometric parameters, we generated a comprehensive dataset to train the model, which captures complex dependencies between structure and optical response. A key finding is the redshift in resonance dip associated with increasing sidewall tilt. We further validated the model by comparing its predictions with experimental results, showing excellent agreement. This work demonstrates a powerful, data-driven approach for the rapid design and optimization of plasmonic nanostructures, opening new possibilities for nanophotonic applications.