Neuraxial clonidine is not associated with lower post-cesarean opioid consumption or pain scores in parturients on chronic buprenorphine therapy: a retrospective cohort study.

Purpose: Adequate post-cesarean delivery analgesia can be difficult to achieve for women diagnosed with opioid use disorder receiving buprenorphine. We sought to determine if neuraxial clonidine administration is associated with decreased opioid consumption and pain scores following cesarean delivery in women receiving chronic buprenorphine therapy.

Methods: This was a retrospective cohort study at a tertiary care teaching hospital of women undergoing cesarean delivery with or without neuraxial clonidine administration while receiving chronic buprenorphine.

Alcohol Prevention in Urgent and Emergency Care (APUEC): Development and Evaluation of Workforce Digital Training on Screening, Brief Intervention, and Referral for Treatment.

Excessive alcohol consumption carries a significant health, social and economic burden. Screening, brief intervention and referral to treatment (SBIRT) is one approach to identifying patients with excessive alcohol consumption and providing interventions to help them reduce their drinking. However, healthcare workers in urgent and emergency care settings do not routinely integrate SBIRT into clinical practice and raise a lack of training as a barrier to SBIRT delivery.

Assessing the performance of approximate density functional theory on 95 experimentally characterized Fe(II) spin crossover complexes.

Spin crossover (SCO) complexes, which exhibit changes in spin state in response to external stimuli, have applications in molecular electronics and are challenging materials for computational design. We curate a dataset of 95 Fe(II) SCO complexes (SCO-95) from the Cambridge Structural Database that have available low- and high-temperature crystal structures and, in most cases, confirmed experimental spin transition temperatures (T1/2). We study these complexes using density functional theory (DFT) with 30 functionals spanning across multiple rungs of "Jacob's ladder" to understand the effect of exchange-correlation functional on electronic and Gibbs free energies associated with spin crossover.

Identifying Underexplored and Untapped Regions in the Chemical Space of Transition Metal Complexes.

We survey more than 240 000 crystallized mononuclear transition metal complexes (TMCs) to identify trends in preferred geometric structure and metal coordination. While we observe that an increased level of d filling correlates with a lower coordination number preference, we note exceptions, and we observe undersampling of 4d/5d transition metals and 3p-coordinating ligands. For the one-third of mononuclear TMCs that are octahedral, analysis of the 67 symmetry classes of their ligand environments reveals that complexes often contain monodentate ligands that may be removable, forming an open site amenable to catalysis.

Architector for high-throughput cross-periodic table 3D complex building.

Rare-earth and actinide complexes are critical for a wealth of clean-energy applications. Three-dimensional (3D) structural generation and prediction for these organometallic systems remains a challenge, limiting opportunities for computational chemical discovery. Here, we introduce Architector, a high-throughput in-silico synthesis code for s-, p-, d-, and f-block mononuclear organometallic complexes capable of capturing nearly the full diversity of the known experimental chemical space.

Readability, Content, and Quality of Online Patient Education Materials on Anesthesia and Neurotoxicity in the Pediatric Population.

Objective: Internet-based patient education materials (PEMs) are often above the recommended sixth grade reading level recommended by the U.S. Department of Health and Human Services.

Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands.

Accurate virtual high-throughput screening (VHTS) of transition metal complexes (TMCs) remains challenging due to the possibility of high multireference (MR) character that complicates property evaluation. We compute MR diagnostics for over 5,000 ligands present in previously synthesized octahedral mononuclear transition metal complexes in the Cambridge Structural Database (CSD). To accomplish this task, we introduce an iterative approach for consistent ligand charge assignment for ligands in the CSD.

Molecular orbital projectors in non-empirical jmDFT recover exact conditions in transition-metal chemistry.

Low-cost, non-empirical corrections to semi-local density functional theory are essential for accurately modeling transition-metal chemistry. Here, we demonstrate the judiciously modified density functional theory (jmDFT) approach with non-empirical U and J parameters obtained directly from frontier orbital energetics on a series of transition-metal complexes. We curate a set of nine representative Ti(III) and V(IV) d transition-metal complexes and evaluate their flat-plane errors along the fractional spin and charge lines.

Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles.

Virtual high-throughput screening (VHTS) with density functional theory (DFT) and machine-learning (ML)-acceleration is essential in rapid materials discovery. By necessity, efficient DFT-based workflows are carried out with a single density functional approximation (DFA). Nevertheless, properties evaluated with different DFAs can be expected to disagree for cases with challenging electronic structure (, open-shell transition-metal complexes, TMCs) for which rapid screening is most needed and accurate benchmarks are often unavailable.

Deciphering Cryptic Behavior in Bimetallic Transition-Metal Complexes with Machine Learning.

We demonstrate an alternative, data-driven approach to uncovering structure-property relationships for the rational design of heterobimetallic transition-metal complexes that exhibit metal-metal bonding. We tailor graph-based representations of the metal-local environment for these complexes for use in multiple linear regression and kernel ridge regression (KRR) models. We curate a set of 28 experimentally characterized complexes to develop a multiple linear regression model for oxidation potentials.

Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning.

Transition-metal complexes are attractive targets for the design of catalysts and functional materials. The behavior of the metal-organic bond, while very tunable for achieving target properties, is challenging to predict and necessitates searching a wide and complex space to identify needles in haystacks for target applications. This review will focus on the techniques that make high-throughput search of transition-metal chemical space feasible for the discovery of complexes with desirable properties.

Peripartum Considerations for the Transgender Parturient: A Case Report.

Despite efforts by medical and social activists, transgender parturients encounter barriers to adequate and gender-inclusive health care, resources, and support. We present a case of a 38-year-old transgender man presenting for induction of labor at term. Our case highlights the importance of multidisciplinary planning, appropriate gender-related language, and interventions that may ameliorate gender dysphoria during childbirth.

Solvent manipulation of the pre-reduction metal-ligand complex and particle-ligand binding for controlled synthesis of Pd nanoparticles.

Understanding how to control the nucleation and growth rates is crucial for designing nanoparticles with specific sizes and shapes. In this study, we show that the nucleation and growth rates are correlated with the thermodynamics of metal-ligand/solvent binding for the pre-reduction complex and the surface of the nanoparticle, respectively. To obtain these correlations, we measured the nucleation and growth rates by in situ small angle X-ray scattering during the synthesis of colloidal Pd nanoparticles in the presence of trioctylphosphine in solvents of varying coordinating ability.

Heteroatom Tracing Reveals the 30-Atom Au-Ag Bimetallic Nanocluster as a Dimeric Structure.

Understanding the formation of face-centered cubic (fcc) nanostructures at the atomic level remains a major task. With atomically precise nanoclusters (NCs) as model systems, herein we devised an atom-tracing strategy by heteroatom doping into Au(SR) (SR = S-CH) to label the specific positions in M(SR) NCs (M = Au/Ag), which clearly reveals the dimeric nature of M. Interestingly, the specific position is also consistent with the Ag-doping site in M(SR).

Heterometal-Doped M (M = Au/Ag/Cd) Nanoclusters with Large Dipole Moments.

Dipole moment (μ) is a critical parameter for molecules and nanomaterials as it affects many properties. In metal-thiolate (SR) nanoclusters (NCs), μ is commonly low (0-5 D) compared to quantum dots. Herein, we report a doping strategy to give giant dipoles (∼18 D) in M (M = Au/Ag/Cd) NCs, falling in the experimental trend for II-VI quantum dots.

Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions.

Determination of ground-state spins of open-shell transition-metal complexes is critical to understanding catalytic and materials properties but also challenging with approximate electronic structure methods. As an alternative approach, we demonstrate how structure alone can be used to guide assignment of ground-state spin from experimentally determined crystal structures of transition-metal complexes. We first identify the limits of distance-based heuristics from distributions of metal-ligand bond lengths of over 2000 unique mononuclear Fe(II)/Fe(III) transition-metal complexes.

Unfolding adsorption on metal nanoparticles: Connecting stability with catalysis.

Metal nanoparticles have received substantial attention in the past decades for their applications in numerous areas, including medicine, catalysis, energy, and the environment. Despite these applications, the fundamentals of adsorption on nanoparticle surfaces as a function of nanoparticle size, shape, metal composition, and type of adsorbate are yet to be found. Herein, we introduce the first universal adsorption model that accounts for detailed nanoparticle structural characteristics, metal composition, and different adsorbates by combining first principles calculations with machine learning.

Rethinking Heterometal Doping in Ligand-Protected Metal Nanoclusters.

Heterometal doping is a promising avenue toward tailoring properties of ligand-protected metal nanoclusters for specific applications. Though successful doping has been demonstrated in several structures, the underlying reasons for the dopant preference on occupying specific locations on the nanocluster with different concentrations remain unclear. In this study we apply our thermodynamic stability model, originally developed for ligand-protected monometallic nanoclusters, to rationalize the synthetic accessibility, dopant location, and concentrations of various heterometals on ligand-protected Au nanoclusters.

Size-, Shape-, and Composition-Dependent Model for Metal Nanoparticle Stability Prediction.

Although tremendous applications for metal nanoparticles have been found in modern technologies, the understanding of their stability as related to morphology (size and shape) and chemical ordering (e.g., in bimetallics) remains limited.

Reconstructing the Surface of Gold Nanoclusters by Cadmium Doping.

Atomically precise metal nanoclusters with tailored surface structures are important for both fundamental studies and practical applications. The development of new methods for tailoring the surface structure in a controllable manner has long been sought. In this work, we report surface reconstruction induced by cadmium doping into the [Au(SR)] (R = cyclohexyl) nanocluster, in which two neighboring surface Au atomic sites "coalesce" into one Cd atomic site and, accordingly, a new bimetal nanocluster, [AuCd(SR)], is produced.

Thermodynamic stability of ligand-protected metal nanoclusters.

Despite the great advances in synthesis and structural determination of atomically precise, thiolate-protected metal nanoclusters, our understanding of the driving forces for their colloidal stabilization is very limited. Currently there is a lack of models able to describe the thermodynamic stability of these 'magic-number' colloidal nanoclusters as a function of their atomic-level structural characteristics. Herein, we introduce the thermodynamic stability theory, derived from first principles, which is able to address stability of thiolate-protected metal nanoclusters as a function of the number of metal core atoms and thiolates on the nanocluster shell.

Site-selective substitution of gold atoms in the Au(SR) nanocluster by silver.

The synthesis and structure determination of atomically precise alloy nanoclusters have attracted much attention in recent research. Herein, we report a new alloy nanocluster AuAg(TBBM) (x∼1) synthesized via a ligand-exchange-induced size/structure transformation method. Its X-ray structure is obtained successfully and the dopant Ag is found to occupy three special positions in the kernel, rather than equivalently over all the kernel sites.

Molecular "surgery" on a 23-gold-atom nanoparticle.

Compared to molecular chemistry, nanochemistry is still far from being capable of tailoring particle structure and functionality at an atomic level. Numerous effective methodologies that can precisely tailor specific groups in organic molecules without altering the major carbon bones have been developed, but for nanoparticles, it is still extremely difficult to realize the atomic-level tailoring of specific sites in a particle without changing the structure of other parts (for example, replacing specific surface motifs and deleting one or two metal atoms). This issue severely limits nanochemists from knowing how different motifs in a nanoparticle contribute to its overall properties.