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Direct measurement of the Gibbs free energy of mixing via atom probe tomography

The concept of thermodynamic free energy plays a central role across various disciplines, providing critical insights into system dynamics, energy flow, and sustainability. In materials science, Gibbs free energies are typically determined through phase diagram modeling, which relies on a broad range of thermodynamic data. This process requires the investigation of well-equilibrated materials, a task that can be time-consuming or even impractical for systems with low mobility. In ...

— Guido, Schmitz 2025-12-16 00:00:00

Enhancing Molecular High-Pressure Simulations by Implicit Solvation

Gaussians On Surface Tesserae Simulate HYdrostatic Pressure (GOSTSHYP) and the eXtended Hydrostatic Compression Force Field (X-HCFF) are two quantum chemical methods to simulate the effects of pressure on a single molecule. Both methods have the usage of discretized molecular surfaces in common which are also needed in implicit solvation models like the Conductor-like Polarizable Continuum Model (C-PCM). However, a combined usage of GOSTSHYP or X-HCFF with C-PCM was not possible in previous i...

— Tim, Neudecker 2025-12-16 00:00:00

Synthesis, Physicochemical and Computational Analysis of Tris(fluoromethyl)alkyl Building Blocks

A concise and scalable synthesis of tris(fluoromethyl)alkyl-building blocks (including amines, carboxylic acids, alcohols, and bromides) starting from commercially available 3,3-bis(bromomethyl)oxetane. Comprehensive physicochemical profiling of the corresponding amines and carboxylic acids (by measuring their pKa and LogP values), benchmarked against less fluorinated and non-fluorinated counterparts, showed that the tris(fluoromethyl)methyl (beta,beta',beta''-trifluro-tert-butyl, (FCH₂)₃...

— Yurii M., Pustovit 2025-12-16 00:00:00

Supramolecular Morphogenesis Driven by Nonequilibrium Break-and-Build Self-organisation

Controlling the nonequilibrium dynamics in synthetic systems is an important challenge in supramolecular chemistry. Biological morphogenesis exploits nonequilibrium reaction–diffusion processes to organise differentiated cell networks and functions in space. In contrast, artificial assemblies are mostly formed under thermodynamic control, and they thus lack autonomous spatial complexity. Here, we present supramolecular morphogenesis that enables spatial control over the differentiation and ...

— Itaru, Hamachi 2025-12-16 00:00:00

CO2 reduction by lanthanide borohydride complexes and hydroboration reactivity

Although lanthanide borohydride precursors are useful building blocks to access a variety of molecular lanthanide complexes, the nucleophilic reactivity of the attached [BH4]– unit has not been thoroughly investigated. We herein report the reaction of [La(Cpttt)2(BH4)] (1, Cpttt = 1,2,4-tris(tert-butyl)cyclopentadienyl) towards CO2, leading to the formation of a formate complex, which exists as an equilibrium mixture between the dimeric and monomeric forms in aromatic solvents. DOSY 1H NMR ...

— Grégory, Nocton 2025-12-16 00:00:00

Kinetic analysis of the nucleation-driven processes in condensed phase using the Turnbull–Fisher model

This study introduces a novel methodology for the kinetic analysis of the nucleation-driven processes using the Turnbull–Fisher model. The approach comprises two stages: first, the reaction rate is factorized to determine the conversion function and rate constant. This stage enables direct estimation of the Avrami exponent and is applicable to both isothermal and nonisothermal data. The second stage utilizes the derived rate constant to determine Turnbull–Fisher parameters, performing opt...

— Seyed Mohammad, Hajji Khorasani 2025-12-16 00:00:00

Electrochromic adaptive solar heater and sub-ambient passive daytime radiative cooler

Heating, ventilation, and air-conditioning (HVAC) systems are major contributors to global energy consumption, underscoring the urgent need for energy-efficient building envelope technologies. Synergistic solar and radiative electrochromism offers a promising solution by leveraging the sun and outer space as sustainable thermodynamic resources. In this study, we demonstrate a dual-mode electrochromic device that enables reversible, non-volatile switching between solar heating and sub-ambient ...

— Po-Chun, Hsu 2025-12-16 00:00:00

Comparing Machine Learning Techniques for Predicting Optical Data from Quantum Mechanical Calculations

Machine learning (ML) models have emerged as powerful tools for predicting optical properties of molecules, offering a computationally efficient alternative to time-dependent density functional theory (TD-DFT) calculations. In this study, we trained kernel ridge regression (KRR) and random forest (RF) models on a dataset of 2,000 small organic molecules to predict their excitation energies. The dataset, generated using a high-throughput PLAMS workflow, included molecules containing C, N, O, F...

— Maha, Alotaibi 2025-12-16 00:00:00

Overcoming Surface Irregularities-Induced Large Signal Variation in In Situ SERS via Tailored 1D-CNN for Accurate Quantification on Biological Tissues

Accurate in situ quantification by surface-enhanced Raman spectroscopy (SERS) on biological tissues with uneven surfaces is a persistent challenge due to signal variability from surface irregularities and the coffee-ring effect, which severely limits reproducibility and reliability. Overcoming these limitations is critical for advancing SERS toward practical, high-accuracy applications in biological, agricultural, and clinical settings. Herein, we present a streamlined strategy integrating mi...

— Zihan, Liao 2025-12-16 00:00:00

Photoreactive Pantetheinyl Mimics Reveal Design Limitations for Crypto-Acyl Carrier Proteins

Polyketide synthases (PKSs), fatty acid synthases (FAS), and nonribosomal peptide synthetases (NRPS) span a variety of protein architectures and catalytic modalities. Common to all these biosynthetic modalities is the centrality of a phosphopantetheinylated carrier protein, which shuttles substrate either inter- or intra-molecularly between discrete domains that catalyze enzymatic transformations within the assembly line, resulting in these biosynthetic classes being termed “thiotemplated....

— Mujeeb A., Wakeel 2025-12-16 00:00:00

Dual-Function Metal–Phenolic Networks-Capped Starch Nanoparticles for Postharvest Pesticide Removal and Produce Preservation

The safety and quality of fresh produce are increasingly challenged by pesticide residues and postharvest losses. Traditional postharvest treatments often show limited effectiveness in removing pesticide residues and may introduce micro/nanoplastics contaminations, leading to the need for innovative solutions that both enhance pesticide removal and preserve produce quality. Herein, we developed a novel dual-function postharvest wash based on metal–phenolic networks capped-starch nanoparticl...

— Rickey Y., Yada 2025-12-16 00:00:00

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal-Organic Framework

Metal-organic frameworks (MOFs), with their distinctive porous structures and tunable chemical properties, have shown immense promise in the separation and storage of gases. Currently, the accurate simulation of their adsorptive properties remains challenging, especially for systems where the molecules fit very tightly in the pores. Traditional simulation methods often approximate the frameworks as rigid and do not account for the framework flexibility seen in materials such as NbOFFIVE-1-Ni....

— Daniela, Kohen 2025-12-16 00:00:00

Selectivity in Gas–Liquid Interactions: Molecular Beam Scattering of CD₄ and ND₃ from an Aqueous Flat Liquid Jet

The dynamics of polar and nonpolar molecules colliding with an aqueous surface are characterized by scattering molecular beams of deuterated methane and ammonia, CD4 and ND3 (Ei = 28.9 and 30.3 kJ mol−1, respectively), from a flat liquid jet of cold salty water (8 m LiBr, 230 K). Translational energy distributions of scattered species collected as a function of collision geometry probe both impulsive scattering (IS) and thermal desorption (TD) mechanisms. We find that CD4 scattering is domi...

— Daniel M., Neumark 2025-12-16 00:00:00

Synergistic Effects of Solid Electrolyte Mild Sintering and Lithium Surface Passivation for Enhanced Lithium Metal Cycling in All-Solid-State Batteries

The argyrodite-type solid electrolyte (SE) Li6PS5Cl (LPSCl), recognized for its high ionic conductivity and low-temperature processability, offers substantial potential for enabling lithium metal anodes in all-solid-state batteries (ASSBs), promising high energy densities with enhanced safety. However, lithium dendrite penetration and unstable solid electrolyte interphase (SEI) formation hinder stable cycling at high current densities. This work presents a synergistic strategy to address thes...

— Mario, El Kazzi 2025-12-16 00:00:00

Computational modeling of PROTAC ternary complexes as ensembles using SILCS-PROTAC

Proteolysis targeting chimeras, or PROTACs, are an emerging class of drugs that offer the potential to develop therapeutics targeting “undruggable” proteins by stabilizing protein-protein interactions (PPI). This involves leveraging the physiological protein degradation mechanism based on ubiquitination through stabilization of target protein-E3 ubiquitin ligase PPI mediated by the PROTAC. Existing computational methods for ligand design are not typically designed for the ternary complex ...

— Wenbo, Yu 2025-12-16 00:00:00

Vibronic contributions to hyperfine-mediated spin kinetics

The hyperfine interaction is a cornerstone of spin-dependent processes, yet the kinetic mod- elling of this mechanism remains limited by the Born-Oppenheimer approximation, obscuring the observation of coherent pathways that underpin many photophysical systems. Here, we introduce a unified theoretical framework that rigorously incorporates vibronic contributions through a phase-consistent Herzberg-Teller expansion of the hyperfine Hamiltonian. Its ap- plication to the FMNH•-Cys• radical p...

— Holden, Paz 2025-12-16 00:00:00

Using bond characteristics to predict self-healing properties in materials for sustainable energy conversion

Sustainability of energy conversion materials depends on their functional resilience. Such can be achieved by self-healing, SH, which requires mass transfer inside the material. Unfortunately, we lack guidelines as to which physical and chemical material properties can help predict if a material can self-heal and how. We report a data-driven approach to find such properties, using experimental and computational data from materials databases. We focus on four properties: optical deformation po...

— Yevgeny , Rakita 2025-12-16 00:00:00

Accessing broader vinyl ether scope for sequential cationic-anionic block copolymers

The combination of multiple polymerization mechansisms in a single polymer chain allows for the synthesis of block copolymers with blocks of significantly different chemical structures. Previously, the combination of cationic polymerization of vinyl ethers and anionic polymerization of thiiranes was enabled through the use of a thiocarbonyl thio universal mediator, albiet limited in scope to just ethyl vinyl ether for the cationic block. Herein, we utilize a Brønsted acid-catalyzed reversibl...

— Nora, O'Connor 2025-12-16 00:00:00

Fast Prediction of Complex Molecular Crystals by Sensible Selection of Asymmetric Units

Effective crystal structure prediction (CSP) relies on thorough exploration of potential energy surfaces (PES). For this reason, molecular CSP has historically focussed on simple crystals with a single molecule in the asymmetric unit. Increasing the number of molecules in the asymmetric unit increases the degrees of freedom of the crystal structure, and the burden on the crystal structure predictor. We mitigate this burden by modifying quasi-random structure searching (QRSS) with "sensible as...

— Jordan, Dorrell 2025-12-16 00:00:00

The Structure of Nanoconfined THF-water Mixtures: From Local Hydrogen Bonding to Microphase Separation and Crystallization

Liquid behaviour can be significantly different when confined in nanopores compared to the bulk, for example miscibility and phase transitions. A central, application-relevant, regime in confined-liquids study is water and its mixtures with organic aprotic solvents. Yet it remains unclear how nanoconfinement affects the interfacial molecular structure and properties of such solutions. Here we combine total neutron scattering with data-driven atomistic simulations to analyse the liquid structu...

— Huanzhi, Hu 2025-12-16 00:00:00

Separation of Sulfated Fucose-containing Isomers found in L.digitata using Cyclic Ion Mobility Mass Spectrometry

Brown seaweeds and some marine invertebrates contain bioactive polysaccharides including fucoidan. These biopolymers have antimicrobial, antibacterial, and antifungal properties, and improved characterization of their structures would be valuable as it can correlated with their bioactivity. To our knowledge, fucoidan extracted from the macroalga Laminaria digitata has not been structurally determined. In this paper, we show that both singly and doubly sulfated fucose units, and singly sulfate...

— Olivia, Wyper 2025-12-16 00:00:00

A relaxed electric double layer accelerates photocatalytic oxygen evolution on TiO2 nanoparticles: Effects of Fe3+ redox shuttle concentration and pH

Two-step, Z-scheme reactors for photocatalytic water splitting have the potential to increase sunlight spectrum absorption while improving operational safety with an aqueous redox shuttle to transfer charge between two hydrogen- and oxygen-evolving catalysts. There is limited understanding of how the interactions between aqueous redox shuttle ions and the photocatalyst influences kinetics and reaction rates. To explore electrolyte-focused methods to enhance photocatalytic rates, this study p...

— Rohini, Bala Chandran 2025-12-16 00:00:00

Benchmarking Physics-inspired Machine Learning Models for Transition Metal Complexes with Diverse Charge and Spin States

Physics-inspired machine learning (ML) models can be categorized into two classes: those relying solely on three-dimensional structure and those incorporating electronic information. In this work, we benchmark both classes for predicting quantum-chemical properties of transition metal complexes with diverse charge and spin states, using three complementary datasets. The evaluated methods include molecular representations (SLATM, FCHL, SOAP, and SPAHM family) combined with kernel ridge regress...

— Clemence, Corminboeuf 2025-12-16 00:00:00

CAU-10-H: synthesis scale-up at pilot scale, techno-economic analysis and application in a full-scale cooling system

Metal-organic frameworks (MOFs) offer a wide range of advantages to modern society. In particular, the growing societal challenges of energy consumption for cooling and water scarcity can be addressed by high-performance MOFs, such as CAU-10-H, Al-MIL-160 and MOF-303. To enable the application of MOFs, their sustainable and large-scale production must be established. Here, we report the green, low-cost multi-kg scale-up of CAU-10-H in a pilot-scale batch reactor leading to 27.5 kg of dry MOF,...

— Ralph, Herrmann 2025-12-16 00:00:00

Tuning Connectivity in Hybrid Organic-Inorganic Antimony Halides through Reactant Concentration Effects

In this study, we report the synthesis and characterization of two hybrid organic in- organic (HOI) antimony halides using DABCO (DABCO = 1,4-diazabicyclo[2.2.2]octane) as the organic cation. Varying the concentration of the starting materials leads to dif- ferent oxidation states, resulting in different inorganic substructures ranging from iso- lated units to layers and a new interconnected metal halide framework. The structure of (DABCOH2)SbVCl7 (1) contains isolated [SbVCl6]– units separ...

— Douglas H., Fabini 2025-12-16 00:00:00

ConforFormer: representation for molecules through understanding of conformers

Recent years have seen a growing interest in machine learning approaches for chemical tasks. The best existing methods focus on building base models that combine molecular graphs (“2D structures”) with atomic coordinates in 3D to predict molecular properties, typically through pre-training followed by fine-tuning on benchmark datasets. However, current approaches require updating the weights of the entire model during the fine-tuning procedure for each prediction task. While this enables ...

— Mas, Klein 2025-12-16 00:00:00

Gradients not needed: ML-driven propagation of nonadiabatic molecular dynamics without reference gradients

The recent development of machine learning (ML) methods for quantum chemistry has tremendously boosted the efficiency of molecular calculations. In this work, we use ML to enable nonadiabatic molecular dynamics (NAMD) simulations without access to the analytical energy gradients from the underlying electronic structure method. By fine-tuning our foundational model for excited-states, OMNI-P2x, on energies alone, and leveraging automatic differentiability to obtain forces, we eliminate the gr...

— Pavlo O., Dral 2025-12-16 00:00:00

Vacuum-free spectroscopy reveals metastable oxygen redox intermediates in oxygen-redox cathodes

Capturing metastable reaction intermediates through spectroscopy is a fundamental challenge across many fields, as their intrinsic metastability often leads to transformation while being measured. This challenge is acute in oxygen redox in battery intercalation cathodes, where metastable intermediates, despite their long lifetime, remain difficult to capture reliably. Here, we demonstrate that vacuum conditions can destabilize oxidized oxygen intermediates and drive their transformation to th...

— William, Chueh 2025-12-16 00:00:00

Powering Hyperscale AI Data Centers with Off-grid Solar, Battery, and Hydrogen

AI data centers are emerging as the fastest growing electricity load in the world. Meeting this demand with grid power has become increasingly difficult due to multi-year interconnection queues and gas turbines that are in limited supply with rising capital costs. As a result, hyperscalers are exploring off-grid and self-generation solutions to deliver reliable electricity on accelerated deployment timelines. One solution for consideration is solar PV, but the mismatch due to insolation inter...

— Yushan, Yan 2025-12-16 00:00:00

Integrating Structure-Based Genetic Algorithms and Reinforcement Learning for the De Novo Discovery of Novel BACE1 Inhibitors

Alzheimer’s disease (AD) remains one of the most pressing neurodegenerative challenges, with β-secretase 1 (BACE1) representing a key therapeutic target for amyloid-β reduction. Despite extensive discovery efforts, the development of clinically viable BACE1 inhibitors remains hindered by poor selectivity, off-target toxicity, and limited blood–brain barrier penetration; to overcome these challenges, we introduce an integrated generative framework that synergistically couples ligand-base...

— Thang, Dang 2025-12-16 00:00:00

Spin-polarized oxygen evolution catalysis enabled by a honeycomb quantum magnet

The spin state of electrocatalysts has recently emerged as a critical factor governing the kinetics of the oxygen evolution reaction (OER). Here, we demonstrate that intrinsic spin polarization, enabled by magnetic anisotropy in frustrated quantum magnets, can drive highly efficient OER without external magnetic fields. Using the honeycomb cobaltate series Na2Co2–xNixTeO6 (0 ≤ x ≤ 1.0), we systematically modulate spin interactions via chemical substitution while preserving crystal sy...

— Xiawa , Wang 2025-12-16 00:00:00

Use of halogenated units for the construction of artificial carbohydrate receptors

To investigate the potential of halogen-containing building blocks in the development of artificial carbohydrate receptors, the 1,3,5-trisubstituted 2,4,6-triethylbenzene scaffold with halogenated subunits and classical hydrogen bonding sites was used as a model system. In the first studies, the influence of the presence of halogens on the binding properties of compounds bearing benzamidomethyl units was investigated, whereby the type of halogen and its ring position were varied. The question...

— Conrad, Hübler 2025-12-16 00:00:00

Catalytic Nitrogen Fixation Using Molybdenum–Oxo Com-plexes Bearing NHC-Based PCP-Type Pincer Ligands via Oxo-to-Nitride Conversion

Development of molecular catalysts compatible with water is essential for achieving sustainable ammonia synthesis. In this context, met-al–oxo species have rarely been recognized as catalysts for nitrogen fixation, but rather regarded as dead-end species formed through the reaction of low-valent metal complexes with water. Herein, we report a series of cationic molybdenum–oxo complexes bearing NHC-based PCP-type pincer ligands and their utility as catalyst precursors for ammonia formati...

— Kazunari, Yoshizawa 2025-12-16 00:00:00

Rational Optimization of a Palladium-Nickel Core-Shell Semi-Hydrogenation Catalyst

Heterogeneous catalysts have substantial practical advantages for large-scale reactions, but the development of highly selective heterogeneous catalysts remains challenging. For homogeneous catalysts, which are prized for their ability to deliver highly selective reaction outcomes, rational catalyst optimization from a promising lead structure is possible due to the uniformity of catalytic active sites as well as the ability to make precise structural changes to the structure of the catalyst....

— Norbert, Pfänder 2025-12-16 00:00:00

Practical Data-Driven Interrogation of Reactivity in Acid-Catalyzed Carbonyl–Olefin Metathesis with Machine Learning and Large Language Models

Carbonyl–olefin metathesis (COM) has emerged as a powerful yet mechanistically complex transformation for forging carbon–carbon bonds. Although diverse Brønsted and Lewis acid catalysts enable COM reactivity, predicting which catalyst will be effective for a given substrate remains challenging. Likewise, machine learning (ML) and large language models (LLMs) are emerging tools for planning experiments in organic synthesis, but their relative strengths in mechanistically rich catalytic sy...

— Sean, Burns 2025-12-16 00:00:00

Modeling and parameterization of size-dependent processes in multiphase aerosol chemistry

Many atmospherically relevant multiphase reactive systems exhibit size-dependent kinetics in laboratory studies, with apparent reaction rates increasing with decreasing droplet size, suggesting an important role for interfacial processes. Here, we present CHAI (CHemistry of Aerosol Interfaces), a physicochemical modeling framework that describes these reactive systems using an additive resistance approach, considering the various mass transfer and reaction processes taking place simultaneousl...

— Vicki, Grassian 2025-12-16 00:00:00

Superior Lattice Oxygen-Mediated Oxygen Evolution Reaction Using a High Entropy Metal Phosphate Precatalyst

The oxygen evolution reaction is recognized as a kinetic bottleneck in the process of water splitting. Activating the lattice oxygen-mediated mechanism (LOM) can surpass the theoretical limitations of the traditional adsorbate evolution mechanism (AEM) and improve the kinetics of the oxygen evolution reaction; however, inadequate stability continues to pose a significant issue for the operation of LOM. In this regard, high entropy materials with their multi-component configuration and entropy...

— Amit, Paul 2025-12-16 00:00:00

Combined machine learning approaches to predict thermal conductivity for liquid mixtures

The application of Machine Learning (ML)-based techniques was explored to create a fully predictive framework for estimating the thermal conductivity of multi-component mixtures containing hydrocarbons and oxygenated compounds. The study followed these steps: (i) three datasets were constructed using experimental thermal conductivity data for both pure compounds and binary mixtures available in the literature, (ii) Symbolic regression was then applied to generate mixing rules considering five...

— Theodoros E., Karakasidis 2025-12-16 00:00:00

Enabling Accurate Chemical Modeling of Shocked Energetic Materials Using a Machine Learning Interatomic Potential

Understanding the complex chemistry of organic materials under dynamic compression is important for many applications, but is challenging due to the large number of reactions occurring at various time scales. Here, we develop a machine learning potential based on Chebyshev polynomials to study the insensitive energetic material 1,3,5- triamino-2,4,6-trinitrobenzene (TATB) under detonation. We discuss a strategy for constructing diverse training data needed to capture the complex chemistry of ...

— Timo, Bremer 2025-12-16 00:00:00

Interlayer Force Field for the Anisotropic Interaction between Planar Organic Molecules and Two-dimensional Hexagonal Boron Nitride

We introduce a new interlayer potential (ILP) for simulating the adsorption and diffusion of planar organic molecules with partially charged heteroatoms on hexagonal boron nitride (hBN). Unlike previous models, this ILP incorporates all-atom electrostatic interactions alongside short-range repulsion and long-range attraction, enabling accurate treatment of polar molecules. Parametrized against Density Functional Theory data for pentacene and PTCDI, the ILP demonstrates transferability to rela...

— Tolibjon , Abdurakhmonov 2025-12-15 00:00:00

Biomimetic Targeting and Autonomous Optimization in Nanomedicine

Despite $100 billion in investment and more than 100,000 publications, nanomedicine translation fails primarily at biological validation, not at synthesis or characterization. We present the first systematic technology readiness assessment across autonomous nanomedicine components, revealing a critical finding: while individual technologies achieve TRL 5-8 (commercial organ-chips with 87% sensitivity and 100% specificity for hepatotoxicity; microfluidic platforms processing 96 formulations in...

— Izabella, Komperda 2025-12-15 00:00:00

Radiotracer Competition Binding Experiments with α-Synuclein Fibrils Reveal Insights into Designs for Ligand Specificity

To identify structure activity relationships of ligands competing with the site-specific positron emission tomography probe [3H]BF-2846 in α-synuclein aggregates, we have synthesized and characterized the binding of over 300 compounds, exploring three distinct scaffolds and identifing 30 <10 nM affinity binders.

— Yanbo, Yu 2025-12-15 00:00:00

Biomolecular Multiscale Simulation (BMS25) Dataset to Train Neural Network Potentials for QM/MM Settings with Electrostatic Embedding

Neural network potentials (NNPs) can provide insight into biological processes at atomic resolution. Training these NNPs requires large and diverse datasets of molecules, conformations, and configurations. However, so far little attention has been paid to the description of solvation, despite its importance for biomolecular systems. This work lays the foundation for NNPs where solvation is an integral part of the model. Following a quantum-mechanics/molecular-mechanics (QM/MM) formalism with ...

— Igor, Gordiy 2025-12-15 00:00:00

SOPPCL: Sequence-based Order Parameter Prediction with Contrastive Learning

Protein dynamics are pivotal to biological function, and elucidating these dynamic properties is essential for understanding their behavior in cellular processes. Nuclear magnetic resonance (NMR) spectroscopy quantifies residue-specific motional freedoms through order parameters (S²), thereby providing critical insights into local structural flexibility and conformational dynamics. Nevertheless, accurate prediction of NMR order parameters remains a critical challenge in structural biology. T...

— Maili, Liu 2025-12-15 00:00:00

Self-training Improves Prediction of NMR Order Parameters

As a crucial parameter obtained through NMR spectroscopy for elucidating the dynamic behavior of proteins in solution, backbone N-H order parameters indicate the flexibility of atoms or groups on the picosecond to nanosecond timescale, thereby facilitating a comprehensive understanding of protein function and mechanisms. In NMR experiments, obtaining order parameters involves measuring relaxation parameters and steady-state NOE, followed by conducting Lipari-Szabo model-free analysis, which i...

— Maili, Liu 2025-12-15 00:00:00

Wells-Dawson Polyoxometalate Complexes with Actinides (Part 2): Californium.

We report the first example of a polyoxometalate (POM) compound containing californium. Using a Wells-Dawson POM ligand, K17Cf(P2W17O61)2·2H2O was synthesized and characterized. Californium is the heaviest element ever crystalized with a POM. Since its discovery in 1950, only 13 coordination compounds of Cf have been isolated and structurally characterized, including the one reported here. The structure of the Cf(III)-POM compound complements the equivalent structures with Am(III) and Cm(II...

— Ian, Colliard 2025-12-15 00:00:00

Wells-Dawson Polyoxometalate Complexes with Actinides (Part 1): Americium and Curium

We report the isolation, plus spectroscopic and structural characterization, of the first trivalent actinide complexes with a Wells–Dawson polyoxometalate (POM), using the lacunary ligand [α2-P2W17O61]10- (P2W17). Americium(III) forms two distinct phases: triclinic (K17Am(P2W17O61)2·42.5H2O) and monoclinic (K17Am(P2W17O61)2·12H2O), while curium(III) crystallizes exclusively in the monoclinic phase (K17Cm(P2W17O61)2·8H2O). These two phases for Am(III) exhibit systematic differences in be...

— Ian, Colliard 2025-12-15 00:00:00

Rational Design of a Ruthenium–Cupin Complex as an Artificial Ketone Reductase with High Hydride-Coupling Efficiency

A ruthenium(p-cymene)–cupin complex functioning as an artificial ketone reductase was constructed via structure-guided rational engineering. 1-His variants of the native 4-His tetrad enabled productive ruthenium anchoring and the asymmetric transfer hydrogenation of trifluoroacetophenone in aqueous media using sodium formate as a benign hydrogen donor. Primary and secondary coordination sphere refinement markedly enhanced the ruthenium–hydride generation and hydride transfer efficiency. T...

— Yoshitsugu , Morita 2025-12-15 00:00:00

A Computational Modeling of ADLumin Chemiluminescence: Oxygenation and Dioxetanone Formation

ADLumin is a new class of turn-on chemiluminescent probes that have shown increased luminescent intensity in the presence of amyloid beta (Aβ) plaques, which are commonly associated with Alzheimer’s disease (AD). ADLumin shares an imidazopyrazinone (IPO) moiety with the well known Cypridina luciferin, which reacts with O2 and produces bioluminescence. While the reaction mechanism for many other luciferins has been studied extensively, the chemiluminescent mechanism for ADLumin molecules ha...

— Chongzhao , Ran 2025-12-15 00:00:00

Would the Tandem Sequential Cycloaddition Reactions of Functionalized Acetylene, Cyclopentadienyl Derivatives, and Phenyl Azide for the Formation of Norbornene 1,2,3-Triazolines Proceed via the [4+2]/[3+2] or [3+2]/[4+2] Reaction Sequences? A DFT Mechanistic Study

In this study, the M06 global hybrid functional coupled with the 6-311G(d,p) basis set has been employed to systematically investigate the reaction mechanisms and the energetics of the titled reaction having been inspired by the established unique pharmacological attributes of the products, among other scientific and/or synthetic benefits. Herein, the reaction involving the unsubstituted molecules- A1(R1 = H), A2(X = CH2), and A3 (R = Ph)- is considered the reference reaction. Generally, the ...

— Evans, Adei 2025-12-15 00:00:00