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This work investigated the 0Cr16Ni5Mo1 stainless steel using laser selective melting (SLM) technology and explored the effect of the tempering temperature on the microstructure and properties. After the tempering treatment, the quenched martensite transformed from a metastable to steady state, and residual austenite was formed. The results indicated that the elongation of the transverse specimen showed an upward trend as the tempering temperature increased, while the elongation of the longitudinal specimen first increased and then decreased. The fracture mode was ductile. There was an obvious fiber, radial, and shear lip zone on the fracture surface of transverse specimens. When the tempering temperature was 650 °C, the shear lip area of the fracture surface was the largest. For longitudinal specimens, there was no obvious zoning on the fracture surface. [ABSTRACT FROM AUTHOR]

Prompted by visionary political leaders and a flowering economy, the University of La Plata was founded in 1905, the third Argentinian university after the Universities of Cordoba (1613) and Buenos Aires (1821). Differing from the older universities, more prone to professional formation, the new university was oriented towards teaching and scientific research following western European academic tradition. Along with the university was created the Institute of Physics, the first of its kind in Latin America. To pursue the foundational plan, the university recruited distinguished German physicists, some of whom became the first directors. From the start, the institute became acquainted with Röntgen rays, their generation and use, initially for radiographic images and later in occasional diffraction studies. The first dedicated crystallographic X‐ray diffraction laboratory was set up in the early 1970s, when it solved the first molecular structures. Soon the fascination brought about by a methodology that afforded the visualization of atoms, molecules and crystals lured the local and national physical chemistry communities. In close partnership with an equally oriented laboratory at the University of Sao Paulo, Brazil, and in collaboration with several physical chemistry laboratories from Argentina and the Latin American region, and also from Europe, we undertook studies on the crystal structures and physicochemical and spectroscopic properties of a wide range of materials, including inorganic, organic, bioinorganic, metal–organic, organic–metal, supramolecular, pharmaceutical, organic minerals and liquid crystals. The present essay is a personal account of the origin and development of structural X‐ray crystallography at the University of La Plata and its impact on the scientific research of Argentina and Latin America. [ABSTRACT FROM AUTHOR]

Identifying transitional states is crucial for understanding protein conformational changes that underlie numerous biological processes. Markov state models (MSMs), built from Molecular Dynamics (MD) simulations, capture these dynamics through transitions among metastable conformational states, and have demonstrated success in studying protein conformational changes. However, MSMs face challenges in identifying transition states, as they partition MD conformations into discrete metastable states (or free energy minima), lacking description of transition states located at the free energy barriers. Here, we introduce Transition State identification via Dispersion and vAriational principle Regularized neural networks (TS-DAR), a deep learning framework inspired by out-of-distribution (OOD) detection in trustworthy artificial intelligence (AI). TS-DAR offers an end-to-end pipeline that can simultaneously detect all transition states between multiple free minima from MD simulations using the regularized hyperspherical embeddings in latent space. The key insight of TS-DAR lies in treating transition state structures as OOD data, recognizing that they are sparsely populated and exhibit a distributional shift from metastable states. We demonstrate the power of TS-DAR by applying it to a 2D potential, alanine dipeptide, and the translocation of a DNA motor protein on DNA, where it outperforms previous methods in identifying transition states. Understanding transition states (TS) of protein conformational changes is vital for biological discovery. Here, the authors present a deep learning method that simultaneously identifies all TS of conformational changes within a latent hypersphere. [ABSTRACT FROM AUTHOR]

We demonstrate that a short oligonucleotide complementary to a G-quadruplex domain can invade this iconic, noncanonical DNA secondary structure in ways that profoundly influence the properties and differential occupancies of the resulting DNA polymorphic products. Our spectroscopic mapping of the conformational space of the associated reactants and products, both before and after strand invasion, yield unanticipated outcomes which reveal several overarching features. First, strand invasion induces the disruption of DNA secondary structural elements in both the invading strand (which can assume an iDNA tetrad structure) and the invaded species (a G-quadruplex). The resultant cascade of coupled alterations represents a potential pathway for the controlled unfolding of kinetically trapped DNA states, a feature that may be characteristic of biological regulatory mechanisms. Furthermore, the addition of selectively designed, exogenous invading oligonucleotides can enable the manipulation of noncanonical DNA conformations for biomedical applications. Secondly, our results highlight the importance of metastability, including the interplay between slower and faster kinetic processes in determining preferentially populated DNA states. Collectively, our data reveal the importance of sample history in defining state populations, which, in turn, determine preferred pathways for further folding steps, irrespective of the position of the thermodynamic equilibrium. Finally, our spectroscopic data reveal the impact of topological constraints on the differential stabilities of base-paired domains. We discuss how our collective observations yield insights into the coupled and uncoupled cascade of strand-invasion-induced transformations between noncanonical DNA forms, potentially as components of molecular wiring diagrams that regulate biological processes. [ABSTRACT FROM AUTHOR]

Binary nanoparticles of the copper-silver alloy of are of great practical interest due to the possibility of fine-tuning their physical and chemical properties by changing the composition, size, shape and structure of nanoparticles. The processes of formation of the internal structure of Ag-Cu nanoparticles with a diameter from 2.0 to 8.0 nm during their crystallization with three different rates of thermal energy dissipation were studied by the molecular dynamics method. The features of this process were found to be dependent on the target chemical composition of nanoparticles, their size and the intensity of the thermal energy dissipation. The actual appearance and structure of the studied nanoparticles were determined using OVITO and xmakemol visualizers. It was shown that as a result of crystallization from the melt of binary Ag-Cu nanoparticles, metastable states that are sufficiently stable at room temperature (300 K), and the stability of such states after annealing at a temperature of 600 K is also evaluated.

Surface reconstruction plays an essential role in electrochemical catalysis. The structures, compositions, and functionalities of the real catalytic species and sites generated by reconstruction, however, are yet to be clearly understood, for the metastable or transit state of most reconstructed structures. Herein, a series of NiFe oxalates (NixFe1‐xC2O4, x = 1, 0.9, 0.7, 0.6, 0.5, and 0) are synthesized for overall water splitting electrocatalysis. Whilst NixFe1‐xC2O4 shows great hydrogen evolution reaction (HER) activity, the in situ reconstructed NixFe1‐xOOH exhibits outstanding oxygen evolution reaction (OER) activity. As identified by the in situ Raman spectroscopy and quasi‐in situ X‐ray absorption spectroscopy (XAS) techniques, reconstructions from NixFe1‐xC2O4 into defective NixFe1‐xOOH and finally amorphous NixFe1‐xOOH active species (R‐NixFe1‐xOOH) are confirmed upon cyclic voltammetry processes. Specifically, the fully reconstructed R‐Ni0.6Fe0.4OOH demonstrates the best OER activity (179 mV to reach 10 mA cm−2), originating from its abundant real active sites and optimal d‐band center. Benefiting from the reconstruction, an alkaline electrolyzer composed of a Ni0.6Fe0.4C2O4 cathode and an in situ reconstructed R‐Ni0.6Fe0.4OOH anode achieves a superb overall water splitting performance (1.52 V@10 mA cm−2). This work provides an in‐depth structure‐property relationship understanding on the reconstruction of catalysts and offers a new pathway to designing novel catalyst. [ABSTRACT FROM AUTHOR]

The authors have given results of experimental study of metastable states of a nonwetting liquid (distilled water) dispersed in the pore space of hydrophobizated silica gel Fluka 100 C18 under the conditions of partial filling. The results were obtained for 10 and 22°C with a varying degree of filling (11 to 100%) at expectation times from 1 to 1000 s. According to the obtained data, the dependence of the fraction of fast states on the initial degree of filling has been obtained at different temperatures. It has been shown that the increase in temperature and the increase in the initially filled fraction of the volume of nanoporous material lead to a growth in the fraction of fast states with a characteristic time of outflow of the order of several seconds. [ABSTRACT FROM AUTHOR]

[Display omitted] Phase behavior of nanoconfined fluids adsorbed in metal–organic frameworks is of paramount importance for the design of advanced materials for energy and gas storage, separations, electrochemical devices, sensors, and drug delivery, as well as for the pore structure characterization. Phase transformations in adsorbed fluids often involve long-lasting metastable states and hysteresis that has been well-documented in gas adsorption–desorption and nonwetting fluid intrusion-extrusion experiments. However, theoretical prediction of the observed nanophase behavior remains a challenging problem. The mesoscopic canonical, or mesocanonical, ensemble (MCE) is devised to study the nanophase behavior under conditions of controlled fluctuations to stabilize metastable and labile states. Here, we implement and apply the MCE Monte Carlo (MCEMC) simulation scheme to predict the origins of reversible and hysteric adsorption phase transitions in a series of practical MOF materials, including IRMOF-1, ZIF-412, UiO-66, Cu-BTC, IRMOF-74-V, VII, and IX. The MCEMC method, called the gauge cell method, allows to produce Van der Waals type isotherms with distinctive swings around the phase transition regions. The constructed isotherms determine the positions of phase equilibrium and spinodals, as well as the nucleation barriers separating metastable states. We demonstrate the unique capabilities of the MCEMC method in quantitative predictions of experimental observations compared with the conventional grand canonical and canonical ensemble simulations. The MCEMC method is implemented in the open-source RASPA and LAMMPS software packages and recommended for studies of adsorption behavior and pore structure characterization of MOFs and other nanoporous materials. [ABSTRACT FROM AUTHOR]

In polarizable materials, electronic charge carriers interact with the surrounding ions, leading to quasiparticle behavior. The resulting polarons play a central role in many materials properties including electrical transport, interaction with light, surface reactivity, and magnetoresistance, and polarons are typically investigated indirectly through these macroscopic characteristics. Here, noncontact atomic force microscopy (nc-AFM) is used to directly image polarons in Fe2O3 at the single quasiparticle limit. A combination of Kelvin probe force microscopy (KPFM) and kinetic Monte Carlo (KMC) simulations shows that the mobility of electron polarons can be markedly increased by Ti doping. Density functional theory (DFT) calculations indicate that a transition from polaronic to metastable free-carrier states can play a key role in migration of electron polarons. In contrast, hole polarons are significantly less mobile, and their hopping is hampered further by trapping centers. [ABSTRACT FROM AUTHOR]

Defect-related spin-to-photon interfaces in silicon promise the realization of quantum repeaters by combining advanced semiconductor and photonics technologies. Recently, controlled creation/erasure of simple carbon interstitial defects have been successfully realised in silicon. This defect has a stable structure near room temperature and coherently emits in the wave-length where the signal loss is minimal in optical fibres used in communication technologies. Our in-depth theoretical characterization confirms the assignment of the observed emission to the neutral charge state of this defect, as arising due to the recombination of a bound exciton. We also identified a metastable triplet state that could be applied as a quantum memory. Based on the analysis of the electronic structure of the defect and its similarities to a known optically detected magnetic resonance centre in silicon, we propose that a carbon interstitial can act as a quantum bit and may realize a spin-to-photon interface in complementary metal-oxide semiconductor-compatible platforms. This work presents a theoretical investigation of the single carbon interstitial (Ci) defect in silicon as a potential candidate for spin-photon interfaces. Computed charge transition levels and optical properties show good agreement with the experimental results and allow assigning the experimentally observed telecom zero-phonon emission (1448 nm) to the neutral Ci defect. [ABSTRACT FROM AUTHOR]

The recent discovery of nickelate superconductivity represents an important step toward understanding the four‐decade mastery of unconventional high‐temperature superconductivity. However, the synthesis of the infinite‐layer nickelate superconductors shows great challenges. Particularly, surface capping layers are usually unitized to facilitate the sample synthesis. This leads to an important question whether nickelate superconductors with d9 configuration and ultralow valence of Ni1+ are in metastable state and whether nickelate superconductivity can be robust? In this work, a series of redox cycling experiments are performed across the phase transition between perovskite Nd0.8Sr0.2NiO3 and infinite‐layer Nd0.8Sr0.2NiO2. The infinite‐layer Nd0.8Sr0.2NiO2 is quite robust in the redox environment and can survive the cycling experiments with unchanged crystallographic quality. However, as the cycling number goes on, the perovskite Nd0.8Sr0.2NiO3 shows structural degradation, suggesting stability of nickelate superconductivity is not restricted by the ultralow valence of Ni1+, but by the quality of its perovskite precursor. The observed robustness of infinite‐layer Nd0.8Sr0.2NiO2 up to ten redox cycles further indicates that if an ideal high‐quality perovskite precursor can be obtained, infinite‐layer nickelate superconductivity can be very stable and sustainable under environmental conditions. This work provides important implications for potential device applications for nickelate superconductors. [ABSTRACT FROM AUTHOR]

CO is one of the important molecules in dense molecular clouds, and its dissociation induced by cosmic ray heavy ions is a fundamental process for molecular breaking up and rearrangement in astronomical networks. Extensive laboratory simulations are required to understand molecular evolution in astrophysical contexts. Here, we investigate the CO dissociation induced by 1 keV/u Ar 2 + using cold target recoil ion momentum spectroscopy. Kinetic energy release for double electron capture Ar 2 + + CO → Ar 0 + C + + O + and transfer ionization Ar 2 + + CO → Ar + + C + + O + + e − was obtained. The dissociation mechanisms are attributed to different KER distributions. The autoionization process is identified below the CO 2 + double ionization threshold. [ABSTRACT FROM AUTHOR]

After reviewing the peculiar thermodynamics and statistical mechanics of self-gravitating systems, we consider the case of a "binary star" consisting of two particles of size a in gravitational interaction in a box of radius R. The caloric curve of this system displays a region of negative specific heat in the microcanonical ensemble, which is replaced by a first-order phase transition in the canonical ensemble. The free energy viewed as a thermodynamic potential exhibits two local minima that correspond to two metastable states separated by an unstable maximum forming a barrier of potential. By introducing a Langevin equation to model the interaction of the particles with the thermal bath, we study the random transitions of the system between a "dilute" state, where the particles are well separated, and a "condensed" state, where the particles are bound together. We show that the evolution of the system is given by a Fokker–Planck equation in energy space and that the lifetime of a metastable state is given by the Kramers formula involving the barrier of free energy. This is a particular case of the theory developed in a previous paper (Chavanis, 2005) for N Brownian particles in gravitational interaction associated with the canonical ensemble. In the case of a binary star ( N = 2 ), all the quantities can be calculated exactly analytically. We compare these results with those obtained in the mean field limit N → + ∞ . [ABSTRACT FROM AUTHOR]

Oscillatory complex networks in the metastable regime have been used to study the emergence of integrated and segregated activity in the brain, which are hypothesised to be fundamental for cognition. Yet, the parameters and the underlying mechanisms necessary to achieve the metastable regime are hard to identify, often relying on maximising the correlation with empirical functional connectivity dynamics. Here, we propose and show that the brain's hierarchically modular mesoscale structure alone can give rise to robust metastable dynamics and (metastable) chimera states in the presence of phase frustration. We construct unweighted 3-layer hierarchical networks of identical Kuramoto-Sakaguchi oscillators, parameterized by the average degree of the network and a structural parameter determining the ratio of connections between and within blocks in the upper two layers. Together, these parameters affect the characteristic timescales of the system. Away from the critical synchronization point, we detect the emergence of metastable states in the lowest hierarchical layer coexisting with chimera and metastable states in the upper layers. Using the Laplacian renormalization group flow approach, we uncover two distinct pathways towards achieving the metastable regimes detected in these distinct layers. In the upper layers, we show how the symmetry-breaking states depend on the slow eigenmodes of the system. In the lowest layer instead, metastable dynamics can be achieved as the separation of timescales between layers reaches a critical threshold. Our results show an explicit relationship between metastability, chimera states, and the eigenmodes of the system, bridging the gap between harmonic based studies of empirical data and oscillatory models. [ABSTRACT FROM AUTHOR]

Sampling rare events in proteins is crucial for comprehending complex phenomena like cryptic pocket opening, where transient structural changes expose new binding sites. Understanding these rare events also sheds light on protein-ligand binding and allosteric communications, where distant site interactions influence protein function. Traditional unbiased molecular dynamics simulations often fail to sample such rare events, as the free energy barrier between metastable states is large relative to the thermal energy. This renders these events inaccessible on the timescales typically simulated by unbiased molecular dynamics, limiting our understanding of these critical processes. In this paper, we proposed a novel unsupervised learning approach termed as slow feature analysis (SFA) which aims to extract slowly varying features from high-dimensional temporal data. SFA trained on small unbiased molecular dynamics simulations launched from AlphaFold generated conformational ensembles manages to capture rare events governing cryptic pocket opening, protein-ligand binding, and allosteric communications in a kinase. Metadynamics simulations using SFA as collective variables manage to sample 'deep' cryptic pocket opening within a few hundreds of nanoseconds which was beyond the reach of microsecond long unbiased molecular dynamics simulations. SFA augmented metadynamics also managed to capture conformational plasticity of protein upon ligand binding/unbinding and provided novel insights into allosteric communication in receptor-interacting protein kinase 2 (RIPK2) which dictates protein-protein interaction. Taken together, our results show how SFA acts as a dimensionality reduction tool which bridges the gap between AlphaFold, molecular dynamics simulation and metadynamics in context of capturing rare events in biomolecules, extending the scope of structure-based drug discovery in the era of AlphaFold. [ABSTRACT FROM AUTHOR]

Over the past few decades, titanium (Ti) alloys containing fully or mostly body-centred cubic β phase in metastable state have received considerable interest due to their elevated strength with remarkable ductility. Apart from dislocation slip, the plastic deformation of metastable β Ti alloys involves either twinning-induced plasticity (TWIP), transformation-induced plasticity (TRIP), or the complex coupling of both (TWIP/TRIP). The pursuance of better mechanical performance necessitates the fundamental understanding of these various deformation mechanisms and has driven substantial studies. Therefore, the present work reviews recent research on the mechanical behaviour of TWIP and/or TRIP metastable β Ti alloys, with special emphasis on the role of different plasticity modes in enhancing work hardening. The effective inhibition to dislocation slip produced by deformation-induced twins and phases which gives rise to the dynamic Hall–Petch effect is discussed in detail since it underpins the TWIP/TRIP engineering. In particular, the correlation between deformation twinning and stress-induced phase transformation is well addressed. It is expected that such review may shed light on the underlying physics of the intricate deformation behaviour of metastable β Ti alloys and inspire more studies in designing novel Ti alloys with superior mechanical properties. [ABSTRACT FROM AUTHOR]

The superhydrophobicity of submerged surfaces typically pertains to the trapped air film at the liquid–solid interface, subject to wettability transitions from a Cassie–Baxter state to more unstable states that gradually collapse to high retention regimes, which are energetically more favorable. In this work, the dynamic evolution of those transient metastable states is correlated to the underwater acoustic performance of laser textured superhydrophobic surfaces, resolving the dependence of the ultrasound spectral response with the immersion time to capture the genuine contribution of the hierarchical subwavelength morphology, regardless of the air layer effects. Acoustic wave attenuation of the incident ultrasound energy is extensively quantified in transmission, accounting for instantaneous broadband sound blocking (>30 dB) within the spectral range 0.5–1.5 MHz. As a result of the air layer detachment with the immersion time, transmission coefficients increase accordingly, while acoustic fields in reflection unexpectedly evolve toward stealthiness and naïve acoustic camouflage, mostly ascribable to dissipative mechanisms at air layer interfaces. The intrinsic decay of the air layer effect is tentatively determined at different frequencies, since quantitative understanding of the transient lifetime governing underwater surface wettability is critical to design stable superhydrophobic character of laser induced subwavelength metastructures on the most promising acoustic materials – from eco‐friendly natural to artificial. [ABSTRACT FROM AUTHOR]

Low-dimensional multiferroics, which simultaneously possess at least two primary ferroic order parameters, hold great promise for post-Moore electronic devices. However, intrinsic one-dimensional (1D) multiferroics with the coexistence of ferroelectricity and ferromagnetism are still yet to be realized, which will be not only crucial for exploring the interplay between low-dimensionality and ferroelectric/ferromagnetic ordering but also significant in rendering application approaches for high density information technologies. Here, we present a theoretical prediction of intrinsic multiferroicity in 1D molybdenum oxytrihalides nanowires, especially focusing on MoOBr3 nanowires which could be readily extracted from experimentally synthesized van der Waals MoOBr3 bulk materials. Due to the spatial inversion symmetry spontaneously broken by Mo atoms' displacements, MoOBr3 nanowires exhibit 1D ferroelectricity with small coercive electric field and exceptional Curie temperature (~570 K). Additionally, MoOBr3 nanowires also possess 1D antiferroelectric metastable states. On the other hand, both ferroelectric and antiferroelectric MoOBr3 nanowires exhibit ferromagnetic ordering on account of the half-filled Mo-dyz orbitals, a moderate tensile strain (~5%) can greatly boost the spontaneous polarization (~40%) and a mild compress strain (~−2%) may readily switch the magnetic easy axis of ferroelectric MoOBr3 nanowires. Our work holds potential candidates for developing innovative devices that exploit intrinsic multiferroic properties, enabling advancements in novel electronic and spintronic applications. [ABSTRACT FROM AUTHOR]

Inflammation is a protective stress response triggered by external stimuli, with 5-lipoxygenase (5LOX) playing a pivotal role as a potent mediator of the leukotriene (Lts) inflammatory pathway. Nordihydroguaiaretic acid (NDGA) functions as a natural orthosteric inhibitor of 5LOX, while 3-acetyl-11-keto-β-boswellic acid (AKBA) acts as a natural allosteric inhibitor targeting 5LOX. However, the precise mechanisms of inhibition have remained unclear. In this study, Gaussian accelerated molecular dynamics (GaMD) simulation was employed to elucidate the inhibitory mechanisms of NDGA and AKBA on 5LOX. It was found that the orthosteric inhibitor NDGA was tightly bound in the protein's active pocket, occupying the active site and inhibiting the catalytic activity of the 5LOX enzyme through competitive inhibition. The binding of the allosteric inhibitor AKBA induced significant changes at the distal active site, leading to a conformational shift of residues 168–173 from a loop to an α-helix and significant negative correlated motions between residues 285–290 and 375–400, reducing the distance between these segments. In the simulation, the volume of the active cavity in the stable conformation of the protein was reduced, hindering the substrate's entry into the active cavity and, thereby, inhibiting protein activity through allosteric effects. Ultimately, Markov state models (MSM) were used to identify and classify the metastable states of proteins, revealing the transition times between different conformational states. In summary, this study provides theoretical insights into the inhibition mechanisms of 5LOX by AKBA and NDGA, offering new perspectives for the development of novel inhibitors specifically targeting 5LOX, with potential implications for anti-inflammatory drug development. [ABSTRACT FROM AUTHOR]

This study investigates the microstructure and first hydrogenation properties of Fe52Ti40Zr3V5 and Fe37Ti44Zr9V10 alloys, which are individual phases present in the as-cast TiFe + 12 wt.% ZrV2 alloy (parent alloy). The parent alloy exhibited fast first hydrogenation kinetics due to the interplay of these two phases. Our objective is to study the hydrogen storage behavior of these individual phases. The samples were synthesized by arc melting and characterized by X-ray diffraction, scanning electron microscopy, and energy-dispersive spectroscopy. The results show that when these alloys are melted separately, they do not exhibit the same phase composition as in the parent alloy, indicating a metastable state under our synthesis conditions, which significantly impacts their hydrogen storage behavior. Hydrogenation capacity was measured using a homemade Sieverts apparatus. Both alloys demonstrated excellent first hydrogenation kinetics, with an absorption capacity of 0.9 wt.% for the Fe52Ti40Zr3V5 alloy and 2.3 wt.% for Fe37Ti44Zr9V10 alloy. Our key finding is that the final crystal structure of multi-element alloys is highly dependent on the synthesis method. [ABSTRACT FROM AUTHOR]

Understanding the microstructure of materials and their impact on performance is crucial for new electronic devices design. The strong interaction between multiple degrees of freedom (spin, orbit, charge, and lattice) within perovskite type oxides can generate rich electron phase diagrams. The microscopic modulation of manganese ions electron states in rare earth manganate perovskites is the root of many novel macroscopic quantum behaviors, such as giant magnetoresistance phenomenon. For ABO3 type perovskites, the differences of radii and valence states of A‐site ions are used to regulate the coexistence of B site manganese multivalent states (Mn3+, Mn4+, Mn5+), and its ordered structure in the metastable state will create a new combination of electronic states. The ordered arrangement of the multi‐dimensional space of electronic states can induce unique transport properties. Therefore, the preparation of manganate perovskites will provide strong chemical support to construct new generation quantum devices. This review summarizes the challenges and difficulties on constructing trivalent coexisting metastable phase in manganate perovskites through disproportionation reactions, and discusses the status and potential of designing ideal rectified p‐n junctions taking advantage of this unique structure. Finally, the foregrounds of new quantum states driven by this chemical reaction are prospected. [ABSTRACT FROM AUTHOR]

A collisional radiative model for Kr III in the ultraviolet regime is developed. For this purpose, atomic parameters for 4 s 2 4 p 4 , 4 s 4 p 5 , 4 s 2 4 p 3 n l , and 4 s 2 4 p 3 5 d configurations with n ranging from 5 to 7 and l = s , p , using the multiconfiguration Dirac–Hatree–Fock method are calculated. The effects of Breit and radiative quantum electrodynamic corrections are also included. Electron impact excitation cross-sections from the ground state, along with four metastable states arising from the 4 s 2 4 p 4 configuration to all fine structure levels of interest, are calculated using the relativistic distorted wave method. The reliability of the model is tested by comparing the predicted results with the previous measurements. [ABSTRACT FROM AUTHOR]

Evidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons have enhanced synaptic connections among groups of neurons forming structures called cell assemblies; such networks are capable of producing metastable dynamics that is in agreement with many experimental results. However, it is unclear how a clustered network structure producing metastable dynamics may emerge from a fully local plasticity rule, i.e., a plasticity rule where each synapse has only access to the activity of the neurons it connects (as opposed to the activity of other neurons or other synapses). Here, we propose a local plasticity rule producing ongoing metastable dynamics in a deterministic, recurrent network of spiking neurons. The metastable dynamics co-exists with ongoing plasticity and is the consequence of a self-tuning mechanism that keeps the synaptic weights close to the instability line where memories are spontaneously reactivated. In turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. Overall, our results show that it is possible to generate metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics. Author summary: Neural activity in cortex is often characterized by sequences of transient patterns called metastable states. These metastable states have been found to code for important task variables such as stimuli, expectations, and decisions; their switching dynamics can be thought of as reactivations of the corresponding neural representations. This dynamics can be explained by a neural network model wherein neurons are organized in clusters, with neurons inside the same cluster connected by stronger synapses than neurons belonging to different clusters. But what is the origin of this structure? In this work, we demonstrate how such a structure may emerge via synaptic plasticity. In our model, the synapses continuously adapt their values based on the activities of the neurons they connect. This leads to the structuring of the network and metastable dynamics in the presence of repeated stimuli, but also to robustness to the network's self-generated fluctuations in the absence of consistent stimuli. Most importantly, our model uncovers a self-organizing mechanism that keeps the network in a regime where metastability is the only steady dynamics: weaker or stronger synapses would both lead to the absence of metastable states, but the synaptic plasticity rule interacts with the neural dynamics to keep the values of the synaptic weights within the necessary bounds. [ABSTRACT FROM AUTHOR]

Silicon and Germanium oxide (SiOx and GeOx) nanostructures are promising materials for energy storage applications due to their potentially high energy density, large lithiation capacity (~10X carbon), low toxicity, low cost, and high thermal stability. This work reports a unique approach to achieving controlled synthesis of SiOx and GeOx nanostructures via photonic curing. Unlike conventional methods like rapid thermal annealing, quenching during pulsed photonic curing occurs rapidly (sub‐millisecond), allowing the trapping of metastable states to form unique phases and nanostructures. We explored the possible underlying mechanism of photonic curing by incorporating laws of photophysics, photochemistry, and simulated temperature profile of thin film. The results show that photonic curing of spray coated 0.1 M molarity Si and Ge Acetyl Acetate precursor solution, at total fluence 80 J cm−2 can yield GeOx and SiOx nanostructures. The as‐synthesized nanostructures are ester functionalized due to photoinitiated chemical reactions in thin film during photonic curing. Results also showed that nanoparticle size changes from ~48 nm to ~11 nm if overall fluence is increased by increasing the number of pulses. These results are an important contribution towards large‐scale synthesis of the Ge and Si oxide nanostructured materials which is necessary for next‐generation energy storage devices. [ABSTRACT FROM AUTHOR]

The electron transport in current-biased superconducting nano-bridges is determined by the motion of the quantum vortex confined in the internal disorder landscape. Here we consider theoretically a simple case of a single or two neighbouring linear defects crossing a nano-bridge. The strong anharmonicity of the vortex motion along the defect leads, upon radio frequency (RF) excitation, to fractional Shapiro steps. In the case of two defects, the vortex motion becomes correlated, characterised by metastable states that can be locked to the RF-drive. The lock-unlock process causes sudden voltage jumps and drops in the voltage-current characteristics that can be observed in experiments. We analyse the parameters that promote these metastable dynamic states and discuss their possible experimental realisations. Vortex motion defines transport properties of type II superconductors. Here, authors study the effect of vortex synchronisation with an external periodic drive, that leads to the effects of integer and fractional Shapiro steps and even creates metastable states. [ABSTRACT FROM AUTHOR]

Relaxation dynamics of complex many-body quantum systems trapped into metastable states is a very active field of research from both the theoretical and experimental point of view with implications in a wide array of topics from macroscopic quantum tunnelling and nucleosynthesis to non-equilibrium superconductivity and energy-efficient memory devices. In this work, we investigate quantum domain reconfiguration dynamics in the electronic superlattice of a quantum material using time-resolved scanning tunneling microscopy and unveil a crossover from temperature to noisy quantum fluctuation dominated dynamics. The process is modeled using a programmable superconducting quantum annealer in which qubit interconnections correspond directly to the microscopic interactions between electrons in the quantum material. Crucially, the dynamics of both the experiment and quantum simulation is driven by spectrally similar pink noise. We find that the simulations reproduce the emergent time evolution and temperature dependence of the experimentally observed electronic domain dynamics. Metastable states found in superconductors and charge density wave materials are of fundamental interest. Vodeb et al. study the domain wall dynamics in 1T-TaS2 using scanning tunneling microscopy and a quantum annealer, finding that in both cases the dynamics is driven by spectrally similar noise. [ABSTRACT FROM AUTHOR]

We review recent work on Ising-like models with "compressible cells" of fluctuating volume that, as such, are naturally treated in N p T and μ p T ensembles. Besides volumetric phenomena, local entropic effects crucially underlie the models. We focus on "compressible cell gases" (CCG), namely, lattice gases with fluctuating cell volumes, and "compressible cell liquids" (CCL) with singly occupied cells and fluctuating cell volumes. CCGs contemplate singular diameters and "Yang–Yang features" predicted by the "complete scaling" formulation of asymmetric fluid criticality, with a specific version incorporating "ice-like" hydrogen bonding further describing the "singularity-free scenario" for the low-temperature unusual thermodynamics of supercooled water. In turn, suitable CCL variants constitute adequate prototypes of water-like liquid–liquid criticality and the freezing transition of a system of hard spheres. On incorporating vacant cells to such two-state CCL variants, one obtains three-state, BEG-like models providing a satisfactory description of water's "second-critical-point scenario" and the whole phase behavior of a simple substance like argon. Future challenges comprise water's crystal–fluid phase behavior and metastable states. [ABSTRACT FROM AUTHOR]

Anti-COVID19 drugs, such as nirmatrelvir, have been developed targeting the SARS-CoV-2 main protease, Mpro, based on the critical requirement of its proteolytic processing of the viral polyproteins into functional proteins essential for viral replication. However, the emergence of SARS-CoV-2 variants with Mpro mutations has raised the possibility of developing resistance against these drugs, likely due to therapeutic targeting of the Mpro catalytic site. An alternative to these drugs is the development of drugs that target an allosteric site distant from the catalytic site in the protein that may reduce the chance of the emergence of resistant mutants. Here, we combine computational analysis with in vitro assay and report the discovery of a potential allosteric site and an allosteric inhibitor of SARS-CoV-2 Mpro. Specifically, we identified an Mpro metastable state with a deformed catalytic site harboring potential allosteric sites, raising the possibility that stabilization of this metastable state through ligand binding can lead to the inhibition of Mpro activity. We then performed a computational screening of a library (∼4.2 million) of drug-like compounds from the ZINC database and identified several candidate molecules with high predicted binding affinity. MD simulations showed stable binding of the three top-ranking compounds to the putative allosteric sites in the protein. Finally, we tested the three compounds in vitro using a BRET-based Mpro biosensor and found that one of the compounds (ZINC4497834) inhibited the Mpro activity. We envisage that the identification of a potential allosteric inhibitor of Mpro will aid in developing improved anti-COVID-19 therapy.

Ordered mechanical systems typically have one or only a few stable rest configurations, and hence are not considered useful for encoding memory. Multistable and history-dependent responses usually emerge from quenched disorder, for example in amorphous solids or crumpled sheets. In contrast, due to geometric frustration, periodic magnetic systems can create their own disorder and espouse an extensive manifold of quasi-degenerate configurations. Inspired by the topological structure of frustrated artificial spin ices, we introduce an approach to design ordered, periodic mechanical metamaterials that exhibit an extensive set of spatially disordered states. While our design exploits the correspondence between frustration in magnetism and incompatibility in meta-mechanics, our mechanical systems encompass continuous degrees of freedom, and thus generalize their magnetic counterparts. We show how such systems exhibit non-Abelian and history-dependent responses, as their state can depend on the order in which external manipulations were applied. We demonstrate how this richness of the dynamics enables to recognize, from a static measurement of the final state, the sequence of operations that an extended system underwent. Thus, multistability and potential to perform computation emerge from geometric frustration in ordered mechanical lattices that create their own disorder. Frustrated magnetic systems typically have multiple ground state configurations. While such multistability is common in amorphous materials, periodic mechanical systems have long range elastic interactions that tend to lead to a long-range ordered ground state. Herein, Sirote-Katz, Shohat et al. introduce periodic mechanical systems that have many disordered metastable states. [ABSTRACT FROM AUTHOR]

Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state and the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits leak and refractory properties, the NW was placed in a homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of artificial neural networks (ANNs) based on reversible changes in the topology of magnetic NWs. [ABSTRACT FROM AUTHOR]

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness. Author summary: We studied disorders of consciousness (DoC) by defining a brain state as a repertoire of metastable substates with different probabilities of occurrence. We created whole-brain computational models of DoC to uncover the causal mechanisms underlying recovery. These models allowed us to simulate transitions by studying the effects of artificial individual local perturbations under different protocol regimes. We demonstrated successful transitions in the synchronization protocol and showed that the most sensitive areas were located in the somatomotor network, thalamus, precuneus and insula. In the long-term, this could bring valuable insights for understanding DoC and open new avenues for future clinical therapies. [ABSTRACT FROM AUTHOR]

Attenuated total internal reflection (ATR) spectra of polyimide PI-2610 films deposited on single-crystal silicon wafers by centrifugation were studied after irradiation with 5-MeV electrons in a linear accelerator at doses of 1∙1014–2∙1015 cm–2. The strongest bands in the spectrum of the PI-2610 polyimide films were attributed to vibrations of the imide ring C–N–Cst (1349 cm–1) and aromatic ring (1517 cm–1), stretching vibrations of the imide ring C=Ostr (1700 cm–1) and CO–Cst-group C–C bonds (1074 cm-1), and bending vibrations of C–H bonds with maxima at 734 and 828 cm–1. The spectral shape and intensities of bands with maxima at 1700 and 1349 cm–1 due to C=O and C=N–Cstr vibrations were observed to change at an initial dose of 1∙1014 cm–2. It was assumed that this was due to relaxation of metastable states of these groups. The intensities of bands corresponding to asymmetric and symmetric stretching vibrations of C–H2 bonds decreased at a dose of 2∙1015 cm–2. The intensities of ATR bands due to vibrations of C=O and C–N bonds and aromatic and imide rings practically did not change. [ABSTRACT FROM AUTHOR]

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications. [ABSTRACT FROM AUTHOR]

We investigate the ability of the pairwise maximum entropy (PME) model to describe the spiking activity of large populations of neurons recorded from the visual, auditory, motor, and somatosensory cortices. To quantify this performance, we use (1) Kullback-Leibler (KL) divergences, (2) the extent to which the pairwise model predicts third-order correlations, and (3) its ability to predict the probability that multiple neurons are simultaneously active. We compare these with the performance of a model with independent neurons and study the relationship between the different performance measures, while varying the population size, mean firing rate of the chosen population, and the bin size used for binarizing the data. We confirm the previously reported excellent performance of the PME model for small population sizes N < 20. But we also find that larger mean firing rates and bin sizes generally decreases performance. The performance for larger populations were generally not as good. For large populations, pairwise models may be good in terms of predicting third-order correlations and the probability of multiple neurons being active, but still significantly worse than small populations in terms of their improvement over the independent model in KL-divergence. We show that these results are independent of the cortical area and of whether approximate methods or Boltzmann learning are used for inferring the pairwise couplings. We compared the scaling of the inferred couplings with N and find it to be well explained by the Sherrington-Kirkpatrick (SK) model, whose strong coupling regime shows a complex phase with many metastable states. We find that, up to the maximum population size studied here, the fitted PME model remains outside its complex phase. However, the standard deviation of the couplings compared to their mean increases, and the model gets closer to the boundary of the complex phase as the population size grows. Author summary: With recent major advances in recording technology, much of computational neuroscience has effectively turned into describing patterns in large amounts of data as succinctly as possible. One way to do this is to construct simple parametric models of the probability distribution over patterns of neuronal activity, such as the pairwise maximum entropy model. Intuitively, the pairwise model makes the distribution over all patterns as flat or uniform as possible, while keeping all firing rates and pairwise correlations the same as in the data. This model has been shown to effectively capture the observed distribution of activity patterns well for small populations (∼ 10), but it has not been systematically studied for large populations. Here, we study the performance of the pairwise model using a Neuropixel dataset recorded from the visual, auditory, somatosensory, and motor cortices of freely moving rats exposed to different stimuli. Consistent with previous findings, we find good performance for small populations, before it falls sharply as the population size increases (>∼ 25). However, we also find that this decrease in performance reveals interesting differences between the correlation structure of the data recorded under different sensory conditions. [ABSTRACT FROM AUTHOR]

A new equation of state for argon was developed with the view of extending the range of validity of the equation of state previously proposed by Tegeler et al. and obtaining a better physical description of the experimental thermodynamic data for the whole fluid region (single-phase, metastable, and saturation states). As proposed by Tegeler et al., this equation is also based on a functional form of the residual part of the reduced Helmholtz free energy. However, in this work, the fundamental equation for Helmholtz free energy was derived from the measured quantities CV(ρ, T) and P(ρ, T). The empirical description of the isochoric heat capacity CV(ρ, T) was based on an original empirical description explicitly containing the metastable states. The thermodynamic properties (internal energy, entropy, and free energy) were then obtained by combining the integration of CV(ρ, T). The arbitrary functions introduced by the integration process were deduced from a comparison between calculated and experimental pressure P(ρ, T) data. The new formulation is valid for the whole fluid region from the melting line to 2300 K and for pressures up to 50 GPa. It also predicts the existence of a maximum of the isochoric heat capacity CV along isochors, as experimentally observed in several other fluids. For many applications, an approximate form of the equation of state for the liquid phase may be sufficient. A Tait–Tammann equation is therefore proposed between the triple-point temperature and 148 K. [ABSTRACT FROM AUTHOR]

We study the gravitational tidal response of D1D5, Top Star and (1,0,n) strata horizonless geometries. We find that the tidal interactions in fuzzball geometries, unlike in the case of black holes, exhibits a sequence of resonant peaks associated to the existence of metastable bound states. The spectrum of resonant frequencies is computed by semianalytical and numerical methods. [ABSTRACT FROM AUTHOR]

Results of XRD and TEM studies of a metastable phase state in Fe73Ti5B19O3 and Fe55Ti16B27O2 films, which is formed upon magnetron deposition under preset conditions, and of the evolution of the state in the course of subsequent annealing at 500 °C for 1, 5, and 9 h and experimental data on the magnetic microstructure and magnetic properties are reported. The annealed films were found to be characterized by a nanocrystalline structure, which is represented by two crystalline phases, namely, the ferromagnetic solid solution αFe(Ti), and nonferromagnetic boride FenB. The Ti content in the films determines the grain size of the αFe(Ti) phase, whereas the content of B localized within the grain boundaries determines the ratio of the volume fractions of amorphous and nanocrystalline phases in the structure. In contrast to the ferromagnetic Fe73Ti5B19O3 films, the Fe55Ti16B27O2 films are superparamagnets both in the deposited state and after annealing at 500 °C for 1 and 5 h because of the higher volume fraction of the amorphous phase in the structure. The 9 h annealing of the Fe55Ti16B27O2 films transfers them into the ferromagnets owing to the development of the amorphous phase crystallization, increase in the content of nanocrystalline ferromagnetic phase αFe(Ti) grains, and realization of exchange interaction between them. [ABSTRACT FROM AUTHOR]

We present the fabrication of a MoS2−xSex thin film from a co-sputtering process using MoS2 and MoSe2 commercial targets with 99.9% purity. The sputtering of the MoS2 and MoSe2 was carried out using a straight and low-cost magnetron radio frequency sputtering recipe to achieve a MoS2−xSex phase with x = 1 and sharp interface formation as confirmed by Raman spectroscopy, time-of-flight secondary ion mass spectroscopy, and cross-sectional scanning electron microscopy. The sulfur and selenium atoms prefer to distribute randomly at the octahedral geometry of molybdenum inside the MoS2−xSex thin film, indicated by a blue shift in the A1g and E1g vibrational modes at 355 cm−1 and 255 cm−1, respectively. This work is complemented by computing the thermodynamic stability of a MoS2−xSex phase whereby density functional theory up to a maximum selenium concentration of 33.33 at.% in both a Janus-like and random distribution. Although the Janus-like and the random structures are in the same metastable state, the Janus-like structure is hindered by an energy barrier below selenium concentrations of 8 at.%. This research highlights the potential of transition metal dichalcogenides in mixed phases and the need for further exploration employing low-energy, large-scale methods to improve the materials' fabrication and target latent applications of such structures. [ABSTRACT FROM AUTHOR]

The extractant-assisted transport of metal ions from aqueous to organic environments by liquid--liquid extraction has been widely used to separate and recover critical elements on an industrial scale. While current efforts focus on designing better extractants and optimizing process conditions, the mechanism that underlies ionic transport remains poorly understood. Here, we report a nonequilibrium process in the bulk aqueous phase that influences interfacial ion transport: the formation of metastable ion--extractant precipitates away from the liquid--liquid interface, separated from it by a depletion region without precipitates. Although the precipitate is soluble in the organic phase, the depletion region separates the two and ions are sequestered in a long-lived metastable state. Since precipitation removes extractants from the aqueous phase, even extractants that are sparingly soluble in water will continue to be withdrawn from the organic phase to feed the aqueous precipitation process. Solute concentrations in both phases and the aqueous pH influence the temporal evolution of the process and ionic partitioning between the precipitate and organic phase. Aqueous ion--extractant precipitation during liquid--liquid extraction provides a reaction path that can influence the extraction kinetics, which plays an important role in designing advanced processes to separate rare earths and other minerals. [ABSTRACT FROM AUTHOR]

This study introduces an innovative outdoor nephelometer system designed to monitor the dynamic hygroscopic behavior of aerosols in ambient air. Field measurements conducted in the Pearl River Delta region of China unveil significant roles of relative humidity (RH) swings on aerosol phase states. Highlighting the occurrence of aerosol crystallization in the afternoon followed by gradual deliquescence as RH increases, particularly when minimum afternoon RH drops below 35%, with no such behavior observed when it exceeds 40%. Emphasizing that aerosol phase states are shaped not only by RH and chemical composition but also by their RH history, illustrating that RH levels of 70% in the morning or evening may correspond to fully dissolved metastable or partially dissolved metastable states of ambient aerosols. These findings underscore the need to account for RH history when predicting aerosol phase states and have broader implications for comprehending aerosol behavior and its atmospheric impacts. Plain Language Summary: This research introduces a new device to study how tiny particles called atmospheric aerosols in the air behave when they encounter moisture. We tested it in a region of China and discovered that relative humidity fluctuations from morning to evening impact significantly on phase state of atmospheric aerosols. In the afternoon, some of the particles might become solid, like tiny crystals, and later turn into liquid gradually as humidity increases. This phenomenon occurs when the afternoon minimum relative humidity is low, below 35%, but does not take place when it exceeds 40%. Suggesting that relative humidity history matters for aerosol phase. For example, relative humidity of 70% in the morning or evening, particles may be in a liquid or semi‐liquid state. This study helps us understand phase changes of atmospheric particles and their effects on our environment. Key Points: Innovative outdoor nephelometer system was developed to monitor aerosol hygroscopic behavior in ambient airAerosol crystallization in the afternoon followed by gradual deliquescence observedRelative humidity history plays significant roles in determining aerosol phase state [ABSTRACT FROM AUTHOR]

We describe a new Fortran computer program to solve the system of equations for the NH 4+ –Na + –Ca 2+ –K + –Mg 2+ –SO 42- –NO 3- –Cl - –H 2 O system, based on the algorithms of ISORROPIA II. Specifically, the code solves the system of equations describing the "forward" (gas + aerosol input) metastable state but with algorithm improvements and corrections. These algorithm changes allow the code to deliver more accurate solution results in formal evaluations of accuracy of the roots of the systems of equations, while reducing processing time in practical applications by about 50 %. The improved solution performance results from several implementation improvements relative to the original ISORROPIA algorithms. These improvements include (i) the use of the "interpolate, truncate and project" (ITP) root-finding approach rather than bisection, (ii) the allowance of search interval endpoints as valid roots at the onset of a search, (iii) the use of a more accurate method to solve polynomial subsystems of equations, (iv) the elimination of negative concentrations during iterative solutions, (v) corrections for mass conservation enforcement, and (vi) several code structure improvements. The new code may be run in either a "vectorization" mode wherein a global convergence criterion is used across multiple tests within the same chemical subspace or a "by case-by-case" mode wherein individual test cases are solved with the same convergence criteria. The latter approach was found to be more efficient on the compiler tested here, but users of the code are recommended to test both options on their own systems. The new code has been constructed to explicitly conserve the input mass for all species considered in the solver and is provided as open-source Fortran shareware. [ABSTRACT FROM AUTHOR]

A novel class of protein misfolding characterized by either the formation of non-native noncovalent lasso entanglements in the misfolded structure or loss of native entanglements has been predicted to exist and found circumstantial support through biochemical assays and limited-proteolysis mass spectrometry data. Here, we examine whether it is possible to design small molecule compounds that can bind to specific folding intermediates and thereby avoid these misfolded states in computer simulations under idealized conditions (perfect drug-binding specificity, zero promiscuity, and a smooth energy landscape). Studying two proteins, type III chloramphenicol acetyltransferase (CAT-III) and D-alanyl-D-alanine ligase B (DDLB), that were previously suggested to form soluble misfolded states through a mechanism involving a failure-to-form of native entanglements, we explore two different drug design strategies using coarse-grained structure-based models. The first strategy, in which the native entanglement is stabilized by drug binding, failed to decrease misfolding because it formed an alternative entanglement at a nearby region. The second strategy, in which a small molecule was designed to bind to a non-native tertiary structure and thereby destabilize the native entanglement, succeeded in decreasing misfolding and increasing the native state population. This strategy worked because destabilizing the entanglement loop provided more time for the threading segment to position itself correctly to be wrapped by the loop to form the native entanglement. Further, we computationally identified several FDA-approved drugs with the potential to bind these intermediate states and rescue misfolding in these proteins. This study suggests it is possible for small molecule drugs to prevent protein misfolding of this type. Author summary: A variety of diseases are caused by protein misfolding. Therefore, the recent evidence suggesting there is an entire unexplored class of protein misfolding that may be widespread opens the possibility they contribute to disease and may be therapeutic targets. Here, we bypass the question of what diseases such misfolding may contribute to and ask whether it is even possible to restore proper folding and function to proteins that misfold in this manner. We tried the most obvious strategy first: in the computer simulations we created a drug that binds to the folded, native entanglement. The rationale being that this would thermodynamically stabilize the native state relative to misfolded states, and thereby shift the population of molecules to the folded states. But thermodynamic reasoning neglects the folding pathways and kinetics connecting metastable states on the energy landscape, and this strategy had the unintended consequence of slowing down native state formation by stabilizing the entanglement loop without the threading segment piercing it, resulting in the loss of the native entanglement and formation of a non-native entanglement. Building on this observation, we took a different route, and designed a drug that would delay formation of the entanglement loop allowing more time for the threading segment to position itself and allow proper folding of the native entanglement. While this study was carried out using coarse-grained structure-based models, the results indicate it is possible in principle for drugs to be designed to avoid such misfolding and suggest our second design strategy is more likely to work in future experiments. [ABSTRACT FROM AUTHOR]

We developed a radio frequency discharge apparatus for He gas to investigate the spin states of metastable helium (He*) interacting with solid-state surfaces. Our apparatus consisted of a stainless steel vacuum chamber, in which a coil produced He* by discharging introduced He gas. The spin states of the He* were detected using optical pumping and probing techniques. The chamber was designed to accommodate various solid-state samples. We measured the He* polarization produced at a dielectric prism surface by total internal reflection of the circularly polarized pumping light. Our apparatus can be used to investigate possible spin transfer from various solid surfaces to He* atoms. [ABSTRACT FROM AUTHOR]

The search for low-energy antideuterons in cosmic rays allows the addressing of fundamental physics problems testing for the presence of primordial antimatter and the nature of Dark Matter. The PHeSCAMI (Pressurized Helium Scintillating Calorimeter for AntiMatter Identification) project aims to exploit the long-living metastable states of the helium target for the identification of low-energy antideuterons in cosmic rays. A space-based pressurized helium calorimeter would provide a characteristic identification signature based on the coincident detection of a prompt scintillation signal emitted by the antideuteron energy loss during the slowing-down phase in the gas, and the (≈µs) delayed scintillation signal provided by the charged pions produced in the subsequent annihilation. The performance of a high-pressure (200-bar) helium scintillator prototype, tested in the INFN-TIFPA laboratory, will be summarized. [ABSTRACT FROM AUTHOR]

CO is one of the important molecules in dense molecular clouds, and its dissociation induced by cosmic ray heavy ions is a fundamental process for molecular breaking up and rearrangement in astronomical networks. Extensive laboratory simulations are required to understand molecular evolution in astrophysical contexts. Here, we investigate the CO dissociation induced by 1 keV/u Ar2+ using cold target recoil ion momentum spectroscopy. Kinetic energy release for double electron capture Ar2++CO→Ar0+C++O+ and transfer ionization Ar2++CO→Ar++C++O++e− was obtained. The dissociation mechanisms are attributed to different KER distributions. The autoionization process is identified below the CO2+ double ionization threshold.

While the search for topological triplet-pairing superconductivity has remained a challenge, recent developments in optically stabilizing metastable superconducting states suggest a new route to realizing this elusive phase. Here, we devise a testable theory of competing superconducting orders that permits ultrafast switching to an opposite-parity superconducting phase in centrosymmetric crystals with strong spin-orbit coupling. Using both microscopic and phenomenological models, we show that dynamical inversion symmetry breaking with a tailored light pulse can induce odd-parity (spin triplet) order parameter oscillations in a conventional even-parity (spin singlet) superconductor, which when driven strongly can send the system to a competing minimum in its free energy landscape. Our results provide new guiding principles for engineering unconventional electronic phases using light, suggesting a fundamentally non-equilibrium route toward realizing topological superconductivity. S. Gassner et al. propose using light pulses to drive a centrosymmetric s-wave superconductor with strong spin-orbit coupling into a metastable triplet p-wave superconductor with non-trivial topology. The two superconducting orders must be closely competing in equilibrium and the light pulse must break a generalized, dynamic form of inversion symmetry. [ABSTRACT FROM AUTHOR]