Psychosis and the self: How spontaneous discussions of subjective experiences compare in the clinical high-risk and first-episode psychosis populations.

Objective: Prior qualitative studies show that individuals with psychoticlike experiences express difficulties concerning their identity. However, previous work has studied individuals at clinical high risk for psychosis (CHR) and individuals with first-episode psychosis (FEP) separately. Here, we compare the experiences of individuals at CHR, individuals with FEP, and healthy individuals.

Molecular-scale insights into the electrical double layer at oxide-electrolyte interfaces.

The electrical double layer (EDL) at metal oxide-electrolyte interfaces critically affects fundamental processes in water splitting, batteries, and corrosion. However, limitations in the microscopic-level understanding of the EDL have been a major bottleneck in controlling these interfacial processes. Herein, we use ab initio-based machine learning potential simulations incorporating long-range electrostatics to unravel the molecular-scale picture of the EDL at the prototypical anatase TiO-electrolyte interface under various pH conditions.

Insights into the structure and dynamics of K+ ions at the muscovite-water interface from machine learning potential simulations.

The surfaces of many minerals are covered by naturally occurring cations that become partially hydrated and can be replaced by hydronium or other cations when the surface is exposed to water or an aqueous solution. These ion exchange processes are relevant to various chemical and transport phenomena, yet elucidating their microscopic details is challenging for both experiments and simulations. In this work, we make a first step in this direction by investigating the behavior of the native K+ ions at the interface between neat water and the muscovite mica (001) surface with ab-initio-based machine learning molecular dynamics and enhanced sampling simulations.

Correlated electron-nuclear dynamics of photoinduced water dissociation on rutile TiO.

Elucidating the mechanism of photoinduced water splitting on TiO is important for advancing the understanding of photocatalysis and the ability to control photocatalytic surface reactions. However, incomplete experimental information and complex coupled electron-nuclear motion make the microscopic understanding challenging. Here we analyse the atomic-scale pathways of photogenerated charge carrier transport and photoinduced water dissociation at the prototypical water-rutile TiO(110) interface using first-principles dynamics simulations.

Aqueous Titania Interfaces.

Water-metal oxide interfaces are central to many phenomena and applications, ranging from material corrosion and dissolution to photoelectrochemistry and bioengineering. In particular, the discovery of photocatalytic water splitting on TiO has motivated intensive studies of water-TiO interfaces for decades. So far, a broad understanding of the interaction of water vapor with several TiO surfaces has been obtained.

Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics.

The chemical equilibrium between self-ionized and molecular water dictates the acid-base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)-based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid-base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 HO) cells.

A first-principles machine-learning force field for heterogeneous ice nucleation on microcline feldspar.

The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water under deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere.

Acid-Base Chemistry of a Model IrO Catalytic Interface.

Iridium oxide (IrO) is one of the most efficient catalytic materials for the oxygen evolution reaction (OER), yet the atomic scale structure of its aqueous interface is largely unknown. Herein, the hydration structure, proton transfer mechanisms, and acid-base properties of the rutile IrO(110)-water interface are investigated using based deep neural-network potentials and enhanced sampling simulations. The proton affinities of the different surface sites are characterized by calculating their acid dissociation constants, which yield a point of zero charge in agreement with experiments.

ChatGPT and Bard exhibit spontaneous citation fabrication during psychiatry literature search.

ChatGPT (Generative Pre-Trained Transformer) is a large language model (LLM), which comprises a neural network that has learned information and patterns of language use from large amounts of text on the internet. ChatGPT, introduced by OpenAI, responds to human queries in a conversational manner. Here, we aimed to assess whether ChatGPT could reliably produce accurate references to supplement the literature search process.

Modeling the aqueous interface of amorphous TiO2 using deep potential molecular dynamics.

Amorphous titanium dioxide (a-TiO2) is widely used as a coating material in applications such as electrochemistry and self-cleaning surfaces where its interface with water has a central role. However, little is known about the structures of the a-TiO2 surface and aqueous interface, particularly at the microscopic level. In this work, we construct a model of the a-TiO2 surface via a cut-melt-and-quench procedure based on molecular dynamics simulations with deep neural network potentials (DPs) trained on density functional theory data.

Differential Expression of Anomalous Self-Experiences in Spontaneous Speech in Clinical High-Risk and Early-Course Psychosis Quantified by Natural Language Processing.

Background: Basic self-disturbance, or anomalous self-experiences (ASEs), is a core feature of the schizophrenia spectrum. We propose a novel method of natural language processing to quantify ASEs in spoken language by direct comparison to an inventory of self-disturbance, the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE). We hypothesized that there would be increased similarity in open-ended speech to the IPASE items in individuals with early-course psychosis (PSY) compared with healthy individuals, with clinical high-risk (CHR) individuals intermediate in similarity.

Observation of electron orbital signatures of single atoms within metal-phthalocyanines using atomic force microscopy.

Resolving the electronic structure of a single atom within a molecule is of fundamental importance for understanding and predicting chemical and physical properties of functional molecules such as molecular catalysts. However, the observation of the orbital signature of an individual atom is challenging. We report here the direct identification of two adjacent transition-metal atoms, Fe and Co, within phthalocyanine molecules using high-resolution noncontact atomic force microscopy (HR-AFM).

Activating Bi p-orbitals in Dispersed Clusters of Amorphous BiO for Electrocatalytic Nitrogen Reduction.

Catalytic strategies based on main group metals are significantly less advanced than those of transition metal catalysis, leaving untapped areas of potentially fruitful research. We here demonstrate an effective approach for the modulation of Bi 6p energy levels during the construction of atomically dispersed clusters of amorphous BiO . Bi oxidation state is proposed to strongly affects the nitrogen fixation activity, with the half-occupied p orbitals of the Bi ions being highly efficient toward electron injection into the inert N molecule.

The SPEAK study rationale and design: A linguistic corpus-based approach to understanding thought disorder.

Aim: Psychotic symptoms are typically measured using clinical ratings, but more objective and sensitive metrics are needed. Hence, we will assess thought disorder using the Research Domain Criteria (RDoC) heuristic for language production, and its recommended paradigm of "linguistic corpus-based analyses of language output". Positive thought disorder (e.

Water dissociation at the water-rutile TiO(110) interface from ab initio-based deep neural network simulations.

The interaction of water with TiO surfaces is of crucial importance in various scientific fields and applications, from photocatalysis for hydrogen production and the photooxidation of organic pollutants to self-cleaning surfaces and bio-medical devices. In particular, the equilibrium fraction of water dissociation at the TiO-water interface has a critical role in the surface chemistry of TiO, but is difficult to determine both experimentally and computationally. Among TiO surfaces, rutile TiO(110) is of special interest as the most abundant surface of TiO's stable rutile phase.

Modeling the Solvation and Acidity of Carboxylic Acids Using an Deep Neural Network Potential.

Formic and acetic acid constitute the simplest of carboxylic acids, yet they exhibit fascinating chemistry in the condensed phase such as proton transfer and dimerization. The go-to method of choice for modeling these rare events have been accurate but expensive molecular dynamics simulations. In this study, we present a deep neural network potential trained using accurate data that can be used in tandem with enhanced-sampling methods to perform an efficient exploration of the free-energy surface of aqueous solutions of weak carboxylic acids.

Realizing Two-Electron Transfer in Ni(OH) Nanosheets for Energy Storage.

The theoretical capacity of a given electrode material is ultimately determined by the number of electrons transferred in each redox center. The design of multi-electron transfer processes could break through the limitation of one-electron transfer and multiply the total capacity but is difficult to achieve because multiple electron transfer processes are generally thermodynamically and kinetically more complex. Here, we report the discovery of two-electron transfer in monolayer Ni(OH) nanosheets, which contrasts with the traditional one-electron transfer found in multilayer materials.

Multimodal Correlates of Cannabis Use among U.S. Veterans with Bipolar Disorder: An Integrated Study of Clinical, Cognitive, and Functional Outcomes.

Cannabis use (CU) is common among persons with bipolar disorder (BD). Evidence suggests that CU is associated with poorer outcomes among persons with BD; however, these findings remain inconsistent. The present exploratory study aims to examine clinical, functional, and cognitive correlates of CU among persons with BD.

Consensus paper of the WFSBP task force on cannabis, cannabinoids and psychosis.

Objectives: The liberalisation of cannabis laws, the increasing availability and potency of cannabis has renewed concern about the risk of psychosis with cannabis.

Methods: The objective of the WFSBP task force was to review the literature about this relationship.

Results: Converging lines of evidence suggest that exposure to cannabis increases the risk for psychoses ranging from transient psychotic states to chronic recurrent psychosis.

Pathways for Electron Transfer at MgO-Water Interfaces from Molecular Dynamics.

The nature of electron transfer across metal oxide-water interfaces depends significantly on the band gap of the oxide and its band edge energies relative to the potentials of relevant aqueous redox couples. Here we focus on the water interface with MgO, a prototypical wide band gap oxide whose conduction band edge is close in energy to that of water. We investigate the behavior of an excess electron at and out of equilibrium near the interface using molecular dynamics based on hybrid density functional theory.

Breaking a dative bond with mechanical forces.

Bond breaking and forming are essential components of chemical reactions. Recently, the structure and formation of covalent bonds in single molecules have been studied by non-contact atomic force microscopy (AFM). Here, we report the details of a single dative bond breaking process using non-contact AFM.

Increasing Iridium Oxide Activity for the Oxygen Evolution Reaction with Hafnium Modification.

Synthesis and implementation of highly active, stable, and affordable electrocatalysts for the oxygen evolution reaction (OER) is a major challenge in developing energy efficient and economically viable energy conversion devices such as electrolyzers, rechargeable metal-air batteries, and regenerative fuel cells. The current benchmark electrocatalyst for OER is based on iridium oxide (IrO) due to its superior performance and excellent stability. However, large scale applications using IrO are impractical due to its low abundance and high cost.