Hasil untuk "Inorganic chemistry"

Mohamad Koohi-Moghadam, Hongzhe Sun, Hongyan Li et al.

The discovery of anticancer therapeutics has traditionally treated organic small molecules and metal-based coordination complexes as separate chemical domains, limiting knowledge transfer despite their shared biological objectives. This disparity is particularly pronounced in available data, with extensive screening databases for organic compounds compared to only a few thousand characterized metal complexes. Here, we introduce ChemCLIP, a dual-encoder contrastive learning framework that bridges this organic-inorganic divide by learning unified representations based on shared anticancer activities rather than structural similarity. We compiled complementary datasets comprising 44,854 unique organic compounds and 5,164 unique metal complexes, standardized across 60 cancer cell lines. By training parallel encoders with activity-aware hard negative mining, we mapped structurally distinct compounds into a shared 256-dimensional embedding space where biologically similar compounds cluster together regardless of chemical class. We systematically evaluated four molecular encoding strategies: Morgan fingerprints, ChemBERTa, MolFormer, and Chemprop, through quantitative alignment metrics, embedding visualizations, and downstream classification tasks. Morgan fingerprints achieved superior performance with an average alignment ratio of 0.899 and downstream classification AUCs of 0.859 (inorganic) and 0.817 (organic). This work establishes contrastive learning as an effective strategy for unifying disparate chemical domains and provides empirical guidance for encoder selection in multi-modal chemistry applications, with implications extending beyond anticancer drug discovery to any scenario requiring cross-domain chemical knowledge transfer.

Raphael T. Husistein, Markus Reiher

Computational chemistry has become an indispensable tool for generating data and insights, pervading all branches of experimental chemistry. Its most central concept is the potential energy hypersurface, key to all chemistry and materials science, as it assigns an energy to a molecular structure, the necessary ingredient for reaction mechanism elucidation and reaction rate calculation. Density functional theory (DFT) has been the most important method in practice for obtaining such energies, which is mirrored in the use of high-performance computing hardware. In the last two decades, a new class of surrogate potential energy functions has been evolving with remarkable properties: quantum accuracy combined with force-field speed. Until very recently, their application was hampered by the fact that they needed to be trained on truly large system-specific data sets, generated before a computational chemistry study could be started (in sharp contrast to DFT, which, as a first-principles method, works out of the box, but at a far higher price of computational cost). Very recently, this roadblock has been overcome by so-called foundation machine learning interatomic potentials, which are poised to completely change the way we do computational chemistry, likely prompting us to abandon DFT as the prime method of choice for this purpose in less than a decade.

Zhaohui Wu, Shuanglei Yang, Wei Wu

Xinglong Zhang, Huiwen Tan, Jingyi Liu et al.

CHEMSMART (Chemistry Simulation and Modeling Automation Toolkit) is an open-source, Python-based framework designed to streamline quantum chemistry workflows for homogeneous catalysis and molecular modeling. By integrating job preparation, submission, execution, results analysis, and visualization, CHEMSMART addresses the inefficiencies of manual workflow management in computational chemistry by ensuring seamless interoperability with quantum chemistry packages and cheminformatics platforms. Its modular architecture supports automated job submission and execution tasks for geometry optimization, transition state searches, thermochemical analysis, and non-covalent interaction plotting, while auxiliary scripts facilitate file conversion, data organization, and electronic structure analysis. Future developments aim to expand compatibility with additional software, incorporate QM/MM and classical MD, and align with FAIR data principles for enhanced reproducibility and data reuse. Available on GitHub, CHEMSMART empowers researchers with a robust, user-friendly platform for efficient and reproducible computational chemistry.

Izaskun Jimenez-Serra

Gas and dust in the Galactic Center are subjected to energetic processing by intense UV radiation fields, widespread shocks, enhanced rates of cosmic-rays and X-rays, and strong magnetic fields. The Giant Molecular Clouds in the Galactic Center present a rich chemistry in a wide variety of chemical compounds, some of which are prebiotic. We have conducted unbiased, ultrasensitive and broadband spectral surveys toward the G+0.693-0.027 molecular cloud located in the Galactic Center, which have yielded the discovery of new complex organic molecules proposed as precursors of the "building blocks" of life. I will review our current understanding of the chemistry in Galactic Center molecular clouds, and summarize the recent detections toward G+0.693-0.027 of key precursors of prebiotic chemistry. All this suggests that the ISM is an important source of prebiotic material that could have contributed to the process of the origin of life on Earth and elsewhere in the Universe.

Sanchi Monga, Saswata Bhattacharya

Inorganic antiperovskite nitrides have recently emerged as promising materials for photovoltaic applications, yet their nonradiative recombination dynamics remain largely unexplored. Here, we examine the influence of X-site cation substitution on the nonradiative electron-hole recombination in $\mathrm{X_{3}NSb}$ ($X = \mathrm{Ca}, \mathrm{Sr}, \mathrm{Ba}$). Ca- and Sr-based compounds adopt a cubic phase, whereas Ba stabilizes in a hexagonal structure, introducing pronounced symmetry-driven effects. Substituting Ca with Sr narrows the band gap, suppresses octahedral and band-edge fluctuations, reduces nonadiabatic (NA) coupling by $\sim 54\%$, and extends carrier lifetimes by a factor of $2.5$. In contrast, Ba substitution increases lattice distortion, widens the band gap, and enhances NA coupling beyond that of $\mathrm{Sr_{3}NSb}$, thereby accelerating recombination through stronger lattice fluctuations. The resulting band gap fluctuations in $\mathrm{Ba_{3}NSb}$ also shorten decoherence times, following the trend $\mathrm{Ba_{3}NSb} < \mathrm{Ca_{3}NSb} < \mathrm{Sr_{3}NSb}$. Our results demonstrate how the interplay between band gap, NA coupling, and decoherence time governs recombination lifetimes, with $\mathrm{Sr_{3}NSb}$ exhibiting the longest lifetime. These findings highlight the coupled influence of cation chemistry and crystal symmetry in tailoring carrier dynamics for high-performance antiperovskite-based optoelectronics materials.

Alexander Bäumchen, Johnn Majd Balsters, Beate-Sophie Nenninger et al.

Alginate hydrogels are integral to many cell-based models in tissue engineering and regenerative medicine. As a natural biomaterial, the properties of alginates can vary and be widely adjusted through the gelation process, making them versatile additives or bulk materials for scaffolds, microcarriers or encapsulation matrices in tissue engineering and regenerative medicine. The requirements for alginates used in biomedical applications differ significantly from those for technical applications. Particularly, the generation of novel niches for stem cells requires reliable and predictable properties of the resulting hydrogel. Ultra-high viscosity (UHV) alginates possess alginates with special physicochemical properties, and thus far, numerical simulations for the gelation process are currently lacking but highly relevant for future designs of stem cell niches and cell-based models. In this article, the gelation of UHV alginates is studied using a microscopic approach for disc- and sphere-shaped hydrogels. Based on the collected data, a multiphase continuum model was implemented to describe the cross-linking process of UHV alginate polysaccharides. The model utilizes four coupled kinetic equations based on mixture theory, which are solved using finite element software. A good agreement between simulation results and experimental data was found, establishing a foundation for future refinements in the development of an interactive tool for cell biologists and material scientists.

Xun Zhong, Yuxuan Yang, Jiating Chen et al.

Nano-silica is widely used to enhance gel properties, but its size, concentrations, and aggregation behaviors all matter. The influencing rules of these factors remain unclear especially in harsh reservoir conditions. This study presented a comprehensive investigation into the gelation, rheological, and plugging properties of phenolic polymer gels reinforced by modified nano-silica (GSNP) of different sizes and concentrations in harsh reservoir conditions. Specifically, the nano-silica was modified with a highly soluble silane, and gel properties were evaluated through rheological, differential scanning calorimetry (DSC), and sandpack flooding tests. The results showed that the incorporation of GSNP prolonged the gelation time, enhanced gel strength, and improved stability, allowing the gelation solution to enter deeper into the formation while maintaining long-time effectiveness. The optimal gel system was obtained with 0.4 wt.% GSNP-30, under which condition the storage modulus increased by approximately 14 times, and the content of non-freezable bound water more than doubled. This system exhibited plugging efficiency exceeding 80% in formations with permeabilities ranging from 1000 to 6000 millidarcy and enhanced the oil recovery factor by over 25%. The reinforcement mechanisms were attributed to the adsorption of GSNP onto polymer chains and its role in filling the gel matrix, which enhanced polymer hydrophilicity, suppressed polymer aggregation/curling, prevented ion penetration, and promoted the formation of a more uniform gel network. Careful optimization of nanoparticle size and concentration was essential to avoid the detrimental effects due to nanoparticle overfilling and aggregation. The novelty of this study lies in the practicable formulation of thermal and salt-tolerant gel systems with facile modified nano-silica of varying sizes and the systematic study of size and concentration effects. These findings offer practical guidance for tailoring nanoparticle parameters to cater for high-temperature and high-salinity reservoir conditions.

Guiyun Wang, Yanxia Qi, Zhuang Liu et al.

As a non-invasive modality, sonodynamic therapy (SDT) offers several advantages in cancer treatment, including deep tissue penetration and precise spatiotemporal control, resulting from the interplay between low-intensity ultrasound and sonosensitizers. Piezoelectric materials, known for their remarkable capacity of interconversion of mechanical and electrical energy, have garnered considerable attention in biomedical applications, which can serve as pivotal sonosensitizers in SDT. These materials can generate internal electric fields via ultrasound-induced mechanical deformation, which modulates the alteration of charge carriers, thereby initiating surface redox reactions to generate reactive oxygen species (ROS) and realizing the therapeutic efficacy of SDT. This review provides an in-depth exploration of piezoelectric materials utilized in SDT, with a particular emphasis on recent innovations, elucidation of underlying mechanisms, and optimization strategies for advanced biomedical piezoelectric materials. Furthermore, the incorporation of piezoelectric sonosensitizers with immunotherapy, photodynamic, chemodynamic, and chemotherapy is explored, emphasizing their potential to enhance cancer therapy outcomes. By examining the basic principles of the piezoelectric effect and its contributions to SDT, this review sheds light on the promising applications of piezoelectric materials in oncology. It also highlights future directions for improving these materials and expanding their clinical utility in tumor sonodynamic therapy.

Dongnian Chen, Hui Yu, Jiajia Hao et al.

Kelp is a natural hydrogel material, which has been widely used in food industry. However, as a natural material, its properties have not been well explored. In this work, the surface and mechanical properties of kelp were investigated. The surface of kelp exhibited superoleophobicity and a self-clean property. The friction coefficient (COF) of the kelp surface was also low (<0.1). Interestingly, kelp demonstrated anisotropic mechanical properties either with or without metal ions. The tensile strength and toughness of kelp along with the growth direction (H) were better than those at the direction vertical to the growth direction (V). The adsorption of metal ions would significantly enhance the mechanical properties and ionic conductivity. Triboelectric nanogenerator (TENG) was assembled using kelp with NaCl, which showed excellent output performance (open-circuit voltage of 30 V, short-circuit current of 0.73 μA and charge transfer on contact of 10.5 nC). A writing tablet was prepared to use as the kelp-based self-powered tactile sensor. This work provides a new insight into natural kelp, which may be used as a renewable material.

Yugyung Lee, Chi H. Lee

Collagen is a versatile material, and collagen in the human body strengthens the muscles and related organs, allowing good substances to be absorbed into the bloodstream while preventing the absorption of toxic substances. Thus, collagen has been broadly applied in regenerative medicine and tissue engineering. A comprehensive framework for various collagen products has been created by integrating collagen resources with additive components. The application of 3D-bioprinting technologies for designing physiological models further allows for the introduction of enhanced preclinical testing tools that can contribute to successful elucidation of the mechanisms behind host–pathogen interactions, and subsequent prevention and treatment of various diseases. In this review, novel strategies for the 3D-printing production of collagen-sourced biomedical devices, as well as diverse applications customized with advanced artificial intelligence (AI) technologies, were thoroughly examined. Ongoing challenges, including the inherent limitations in the mechanical weakness of collagen-based bioinks, such as printability and stability, along with cell viability and bioavailability, and advanced strategies addressing those challenges, were also reviewed. An integration of 3D printing with collagen as a bioink is enormously efficient in biomedical applications, demonstrating its great potential for clinical translation against infectious diseases, including cardiovascular diseases.

S. Parola, Beatriz Julián‐López, L. Carlos et al.

Paul J. Robinson, Adam Rettig, Hieu Q. Dinh et al.

Molecular quantum chemistry has seen enormous progress in the last few decades thanks to the more advanced and sophisticated numerical techniques and computing power. Following the recent interest in extending these capabilities to condensed-phase problems, we summarize basic knowledge of condensed-phase quantum chemistry for ones with experience in molecular quantum chemistry. We highlight recent efforts in this direction, including solving the electron repulsion integrals bottleneck and implementing hybrid density functional theory and wavefunction methods, and lattice dynamics for periodic systems within atom-centered basis sets. Many computational techniques presented here are inspired by the extensive method developments rooted in quantum chemistry. In this Focus Article, we selectively focus on the computational techniques rooted in molecular quantum chemistry, emphasize some challenges, and point out open questions. We hope our perspectives will encourage researchers to pursue this exciting and promising research avenue.

Xinrui Ren, Hongqing Wu, Ruoyue Tang et al.

Understanding the combustion chemistry of acetaldehyde is crucial to developing robust and accurate combustion chemistry models for practical fuels, especially for biofuels. This study aims to reevaluate the important rate and thermodynamic parameters for acetaldehyde combustion chemistry. The rate parameters of 79 key reactions are reevaluated using more than 100,000 direct experiments and quantum chemistry computations from >900 studies, and the thermochemistry (Δhf(298K), s0(298K) and cp) of 24 key species are reevaluated based on the ATCT database, the NIST Chemistry WebBook, the TMTD database, and 35 published chemistry models. The updated parameters are incorporated into a recent acetaldehyde chemistry model, which is further assessed against available fundamental experiments (123 ignition delay times and 385 species concentrations) and existing chemistry models, with clearly better performance obtained in the high-temperature regime. Sensitivity and flux analyses further highlight the insufficiencies of previous models in representing the key pathways, particularly the branching ratios of acetaldehyde- and formaldehyde-consuming pathways. Temperature-dependent and temperature-independent uncertainties are statistically evaluated for kinetic and thermochemical parameters, respectively, where the large differences between the updated and the original model parameters reveal the necessity of reassessment of kinetic and thermochemical parameters completely based on direct experiments and theoretical calculations for rate and thermodynamic parameters.

Yessenia Oyarzún, José Ulloa, Matías Ceballos et al.

Herein, we investigated hydrogels composed of boronic-acid-functionalized alginate and blended with polyvinyl alcohol (PVA) of different molecular weights to control the release of metoclopramide hydrochloride as a function of pH and shear stress. The functionalization of alginate introduced dynamic covalent bonding and pH-responsive properties that can modulate network connectivity. The study investigated the viscoelastic properties of the hydrogels, their drug release profiles, and their responsiveness to changes in pH and shear forces. The results showed that a higher PVA molecular weight and alkaline pH conditions increased hydrogel viscosity and stiffness due to a more stable and interconnected network structure than acidic pH. Metoclopramide release revealed that the hydrogels exhibited pH-responsive drug release behavior. The drug was more readily released under acidic conditions due to the instability of sp²-hybridized boronate ester bonds. The influence of shear forces on the release of metoclopramide was also investigated at shear rates of 1, 10, and 100 s⁻¹, revealing their effect on matrix stiffening. Research shows that AlgBA/PVA hydrogels have unique properties, such as dynamic covalent bonding, that make them sensitive to external mechanical forces. This sensitivity makes them ideal for applications where physiological conditions trigger drug release.

Teichtmeister Tobias A., Bernhart Alexander Hugo, Huppertz Hubert

NdB6O8(OH)5·H3BO3, triclinic, P 1‾ $\overline{1}$ (no. 2), a = 6.8304(7) Å, b = 7.2004(5) Å, c = 12.707(2) Å, α = 95.479(5)°, β = 98.652(6)°, γ = 101.758(5)°, V = 599.7(2) Å3, Z = 2, R gt(F) = 0.0378, wR ref(F 2) = 0.0826, T = 289(1) K.

R. Yang, R. Yang, J. Skelton et al.

The local crystal structures of many perovskite-structured materials deviate from the average space-group symmetry. We demonstrate, from lattice-dynamics calculations based on quantum chemical force constants, that all of the cesium-lead and cesium-tin halide perovskites exhibit vibrational instabilities associated with octahedral titling in their high-temperature cubic phase. Anharmonic double-well potentials are found for zone-boundary phonon modes in all compounds with barriers ranging from 108 to 512 meV. The well depth is correlated with the tolerance factor and the chemistry of the composition, but is not proportional to the imaginary harmonic phonon frequency. We provide quantitative insights into the thermodynamic driving forces and distinguish between dynamic and static disorder based on the potential-energy landscape. A positive band gap deformation (spectral blue shift) accompanies the structural distortion, with implications for understanding the performance of these materials in applications areas including solar cells and light-emitting diodes.

Munan Gong, Ka-Wai Ho, James M. Stone et al.

Chemistry plays a key role in many aspects of astrophysical fluids. Atoms and molecules are agents for heating and cooling, determine the ionization fraction, serve as observational tracers, and build the molecular foundation of life. We present the implementation of a chemistry module in the publicly available magneto-hydrodynamic code Athena++. We implement several chemical networks and heating and cooling processes suitable for simulating the interstellar medium (ISM). A general chemical network framework in the KIDA format is also included, allowing the user to easily implement their own chemistry. Radiation transfer and cosmic-ray ionization are coupled with chemistry and solved with the simple six-ray approximation. The chemical and thermal processes are evolved as a system of coupled ODEs with an implicit solver from the CVODE library. We perform and present a series of tests to ensure the numerical accuracy and convergence of the code. Many tests combine chemistry with gas dynamics, including comparisons with analytic solutions, 1D problems of the photo-dissociation regions and shocks, and realistic 3D simulations of the turbulent ISM. We release the code with the new public version of Athena++, aiming to provide a robust and flexible code for the astrochemical simulation community.

Alessandro Cataldo, Pinaka Pani Tummala, Christian Martella et al.

In the last years, transition metal dichalcogenides (TMDs), especially at the two-dimensional (2D) limit, gained a large interest due to their unique optical and electronic properties. Among them, MoS2 received great attention from the scientific community due to its versatility, workability, and applicability in a large number of fields such as electronics, optoelectronics and electrocatalysis. To open the possibility of 2D-MoS2 exploitation, its synthesis over large macroscopic areas using cost-effective methods is fundamental. In this study, we report a method for the synthesis of large-area (~ cm2) few-layers MoS2 via liquid precursor CVD (L-CVD), where the Mo precursor (i.e. ammonium heptamolybdate AHM) is provided via a solution that is spin-coated over the substrate. Given the capability of organic and inorganic molecules, such as alkaline salts, to enhance MoS2 growth, we investigated the action of different inorganic salts as seed promoters. In particular, by using visible Raman spectroscopy, we focused on the effect of Na(OH), KCl, KI, and Li(OH) on the thickness, morphology, uniformity and degree of coverage of the grown MoS2. We optimized the process tuning parameters such as the volume of spin-coated solution, the growth temperature, and the seed promoter concentration, to synthesise the lowest possible thickness which resulted to be 2 layers (2L) of the highest quality. We witnessed that the addition of an inorganic seed promoter in the solution improves the extension of the grown MoS2 promoting lateral growth front, and therefore the degree of coverage. From this study, we conclude that, amongst the investigated seed promoters, K-based salts proved to grant the growth of high-quality two-layer MoS2 with optimal and uniform coverage of the SiO2/Si substrate surface.

Alexander S. Lenshin, Kseniya B. Kim, Boris L. Agapov et al.

Porous silicon is a promising nanomaterial for optoelectronics and sensorics, as it has a large specific surface area and is photoluminescent under visible light. The deposition of copper particles on the surface of porous silicon will greatly expand the range of applications of the resulting nanocomposites. Copper was chosen due to its low electrical resistivity and high resistance to electromigration compared to other metals. The purpose of this research was to study changes in the structure and composition of porous silicon after the chemical deposition of copper. Porous silicon was obtained by the anodisation of monocrystalline silicon wafers KEF (100) (electronic-grade phosphorus-doped silicon) with an electrical resistivity of 0.2 Ohm·cm. An HF solution in isopropyl alcohol with the addition of H2O2 solution was used to etch the silicon wafers. The porosity of the samples was about 70 %. The porous silicon samples were immersed in copper sulphate solution (CuSO4·5H2O) for 7 days. We used scanning electron microscopy, IR spectroscopy, and ultrasoft X-ray emission spectroscopy to obtain data on the morphology and composition of the initial sample and the sample with deposited copper. The chemical deposition of copper on porous silicon showed a significant distortion of the pore shape as well as the formation of large cavities inside the porous layer. However, in the lower part the pore morphology remained the same as in the original sample. It was found that the chemical deposition of copper on porous silicon leads to copper penetrating into the porous layer, the formation of a composite structure, and it prevents the oxidation of the porous layer during storage. Thus, it was demonstrated that the chemical deposition of copper on a porous silicon surface leads to visible changes in the surface morphology and composition. Therefore, it should have a significant impact on the catalytic, electrical, and optical properties of the material