jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Annie M. Westerlund | Lakshidaa Saigiridharan | Samuel Genheden
Source: Chemical Science (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Human-guided synthesis planning <i>via</i> prompting Contemporary multistep retrosynthesis tools such as AiZynthFinder, which are frequently used by chemists, generate solved routes for the majority of target molecules, but do not consider the prior knowledge of the chemist, including specific bonds that should disconnect or remain connected throughout the routes. Such knowledge is for example integral when planning a joint synthesis route for a set of similar molecules where common disconnection sites can be identified across the molecules. Here, we present a novel strategy in AiZynthFinder for human-guided multistep retrosynthesis <i>via</i> prompting. This includes a filter for discarding reactions that violate bonds to freeze constraints. Furthermore, we benchmark four possible strategies for breaking selected bonds in the search for synthetic routes, and show that a combination of a disconnection-aware transformer and a multi-objective search generates routes which satisfy bond constraints for more targets in the PaRoutes dataset compared to the standard search (75.57% <i>vs.</i> 54.80%). Finally, we apply the strategy on a set of drug molecules to exemplify a real-world scenario. Our novel approach enables building a short joint synthesis route that satisfies the given bond constraints and covers eight of the ten molecules, demonstrating the added value of incorporating human prior knowledge in synthesis planning. Retrosynthetic analysis ; Monte Carlo tree search ; Disconnection ; Computer science ; Monte Carlo method ; Transformer ; Artificial intelligence ; Engineering ; Mathematics ; Chemistry Machine Learning in Materials Science ; Genomics and Phylogenetic Studies ; Domain Adaptation and Few-Shot Learning
Authors: Sascha Thinius
Source: Digital Discovery (article, 2025-11-17)
Field: Materials Science — Materials Chemistry

High throughput tight binding calculation of electronic HOMO–LUMO gaps and its prediction for natural compounds A high-throughput workflow uses RDKit descriptors from over 400 000 natural products to train tree-based and NN models, enabling the rapid and scalable prediction of their electronic HOMO–LUMO gaps. Workflow ; Scalability ; Tight binding ; Throughput ; Natural (archaeology) ; Artificial neural network Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Scientific Computing and Data Management
Authors: J. Zhou | Yuge Huang | Arman Boromand | Keian Noori | Lafe J. Purvis | Chulwoo Oh | Lu Lu | Zachary W. Ulissi | Vahe Gharakhanyan | Xinyue Zhang
Source: RSC Advances (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Genetic algorithm-accelerated computational discovery of liquid crystal polymers with enhanced optical properties Liquid crystal polymers with exceptional optical properties are highly promising for next-generation virtual, augmented, and mixed reality (VR/AR/MR) technologies, serving as high-performance, compact, lightweight, and cost-effective optical components. However, the growing demands for optical transparency and high refractive index in advanced optical devices present a challenge for material discovery. In this study, we develop a novel approach that integrates first-principles calculations with genetic algorithms to accelerate the discovery of liquid crystal polymers with low visible absorption and high refractive index. By iterating within a predefined space of molecular building blocks, our approach rapidly identifies reactive mesogens that meet target specifications. Additionally, it provides valuable insights into the relationships between molecular structure and properties. This strategy not only accelerates material screening but also uncovers key molecular design principles, offering a systematic and scalable alternative to traditional trial-and-error methods. Transparency (behavior) ; Polymer ; Refractive index ; Liquid crystal ; Absorption (acoustics) ; Scalability ; Key (lock) ; Optical transparency Liquid Crystal Research Advancements ; Advanced Materials and Mechanics ; Synthesis and Properties of Aromatic Compounds
Authors: Ayoub Laghrissi | Horst‐Günter Rubahn | Jacek Fiutowski
Source: ACS Omega (article, 2025-08-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Direct On-Analyte Fabrication of Au Nanoparticles for Substrate-Free SERS Detection of Micro and Nanoplastics Detection of micro- and nanoplastic particles at extremely low concentrations in complex matrices is a critical goal in environmental science and regulatory frameworks. Surface-enhanced Raman spectroscopy (SERS) offers unique advantages for detecting molecular species in such mixtures, relying solely on their characteristic fingerprints. However, its application for plastic particles has been constrained due to weak analyte-substrate interactions. Here, we demonstrate a fabrication proof of concept where gold nanoparticles are synthesized directly onto polystyrene (PS) beads, creating hybrid bead structures specifically designed as substrate-free digital SERS (dSERS). This approach allows direct optical detection of the bead fingerprint, highlighting the interplay between bead fabrication and detection. Based on these findings, we anticipate that substrate-free dSERS will emerge as the method of choice for reliable and ultrasensitive detection of a wide range of analytes, laying the groundwork for a "facial recognition-like" approach to plastic identification. Analyte ; Fabrication ; Substrate (aquarium) ; Nanotechnology ; Nanoparticle ; Materials science ; Chemistry ; Chromatography Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Quantum Dots Synthesis And Properties
Authors: Pengfei Xing | Xinyue Wu | Mengliang Zhu
Source: Biophysics Reports (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Molecular design and excited state dynamics regulation in phototheranostics Phototheranostic, as an emerging non-invasive cancer diagnosis and treatment modality, combines optical imaging with phototherapy, showcasing advantages such as precision, high efficiency, and low toxicity. The core of phototheranostics lies in photosensitizers (PSs), where molecular design and excited state dynamics regulation are crucial for performance optimization. This review systematically summarizes recent advancements in phototheranostic agents, focusing on strategies for molecular design and their critical role in excited-state energy conversion. Through strategies such as molecular structure optimization, coordination modulation, and self-assembly, the excited-state energy dissipation pathways of phototheranostic agents are precisely regulated, achieving a functional output balance while significantly enhancing therapeutic efficacy. Novel phototheranostic agents integrate multifunctional designs to realize theranostic integration, offering innovative solutions for complex cancer treatment. Finally, this paper explores the development prospects of nanotechnology-based phototheranostic strategies, providing new perspectives and potential breakthroughs for the next generation of phototheranostics. Excited state ; Dynamics (music) ; State (computer science) ; Molecular dynamics ; Chemistry ; Computational chemistry ; Statistical physics ; Chemical physics ; Physics ; Atomic physics ; Computer science Photochromic and Fluorescence Chemistry ; Photochemistry and Electron Transfer Studies ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Max Stierle | Daniel Bitterlich | Julia Westermayr | Thorsten Bach
Source: Chemical Science (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Photochemical deracemization of 2,3-allenoic acids mediated by a sensitizing chiral phosphoric acid catalyst Photochemistry opens the possibility to convert a racemic mixture of a chiral compound into a distinct enantiomer in a single operation. Seven chiral phosphoric acids with a pendant thioxanthone chromophore were synthesized and evaluated as catalysts for the visible light-driven deracemization of 2,4-disubstituted 2,3-allenoic acids. A catalyst derived from 1,1'-spirobiindane-7,7'-diol (spinol) performed best and delivered 2-benzyl-4-<i>tert</i>-butyl-2,3-allenoic acids in 58-97% yield and with enantiomeric ratios (e.r.) varying between 71/29 and 85/15 depending on the benzyl substitution pattern. The major enantiomer was shown to be (<i>R</i>)-configured, and other 2,3-allenoic acids were also probed in the reaction. A mechanistic scenario for the observed enantioselectivity is provided that rests on experimental and quantum-chemical studies. Phosphoric acid ; Enantiomer ; Catalysis ; Yield (engineering) ; Chromophore ; Enantiomeric excess ; Chirality (physics) Radical Photochemical Reactions ; Porphyrin and Phthalocyanine Chemistry ; Photochromic and Fluorescence Chemistry
Authors: Jesse DiCenso | Chance Lander | Zheng Pei | Sanghita Sengupta | Tien Le | Yu Zhang | G. T. Kasun Kalhara Gunasooriya | Bin Wang | Yuezhi Mao | Yihan Shao
Source: JACS Au (article, 2025-06-11)
Field: Materials Science — Materials Chemistry

Toward an Understanding of Linear Scaling Relations through Energy Decomposition Analysis The discovery of linear scaling relations has fundamentally changed the field of heterogeneous catalysis. The scaling relations have been rationalized based on the d-band theory, specifically a separation of sp and d electron contributions to adsorption energies. Within the framework of energy decomposition analysis, a full understanding of such a separation would require one to further break down the adsorption energy into distinct energy components such as electrostatics, polarization, charge transfer, and van der Waals interactions, and to examine the sp and d contributions to each of them. As a step in this direction, we analyzed the interaction energy between CH <sub><i>x</i></sub> (<i>x</i> = 1-4) adsorbates and fcc(100) transition metal surfaces (M = Cu, Ag, Au, Rh, and Pt), with the surfaces represented both as slabs in plane-wave density functional theory (pw-DFT) calculations and as atomic clusters in atomic-orbital basis density functional theory (ao-DFT) calculations. Through an absolutely localized molecular orbital (ALMO) based energy decomposition analysis of the ao-DFT adsorption energy, each of the interaction energy components (electrostatics, polarization, van der Waals, and charge transfer) was found to follow its own scaling relations, with an intricate interplay among these energy components yielding the overall scaling relations for the total adsorption energies. Using the recently introduced ALMO-based polarization and charge-transfer analysis schemes, we further dissected polarization into metal surface and adsorbate contributions, and charge transfer into metal → adsorbate and adsorbate → metal contributions. The contributions from the sp and d electrons of the metal to these terms were further quantified, and the dominant role of the metal d electrons was reaffirmed. These results shed light on how CH <sub><i>x</i></sub> adsorbates interact with metal surfaces and further reveal the physical origin of the scaling relations. Scaling ; Decomposition ; Linear scale ; Statistical physics ; Psychology ; Computer science ; Mathematics ; Physics ; Chemistry ; Geography ; Cartography Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Advanced Physical and Chemical Molecular Interactions
Authors: Abbigayle E. Cuomo | John-Paul Webster | H. Ray Kelly | S N Sarkar | Yu Shee | Sanil Sreekumar | Haote Li | Frédéric G. Buono | Víctor S. Batista | Timothy R. Newhouse
Source: ChemRxiv (preprint, 2025-01-29)
Field: Chemistry — Organic Chemistry

EvolvedComplexity as a Total Synthesis Assessment Metric: Strychnine as a Case Study of Scoring Functions The selection of synthetic routes to a small molecule of interest is enabled by the use of various tools to assess the chemical complexity of a given intermediate. While prior approaches assess the intrinsic molecular complexity or the facility with which an intermediate can be synthesized, in this study we introduce an alternative approach that tracks the progress towards the target structure in a given synthesis. A simple metric, EvolvedComplexity, was developed that compares the chemical similarity of a pair of molecules on the basis of the Tanimoto distance between chemical fingerprints. This complementary approach to assessing progress in synthesis may prove to be a useful tool for planning synthetic routes and for developing novel chemistries. Strychnine ; Metric (unit) ; Computer science ; Mathematics ; Psychology ; Operations management ; Economics ; Neuroscience Chemical synthesis and alkaloids ; Innovative Microfluidic and Catalytic Techniques Innovation ; Asymmetric Synthesis and Catalysis
Authors: Chinmay A. Shukla | Roja P. Moghadam | Amber Keegan | Siddharth V. Patwardhan | Vivek V. Ranade
Source: Chemical Engineering Journal (article, 2025-06-17)
Field: Materials Science — Biomaterials

Modelling and optimisation of bio-inspired synthesis of porous silica particles: estimation of kinetics and application to continuous reactors The bio-inspired silica (BIS) synthesis is a greener process that operates at ambient and mild pH conditions and produces high-value products with applications in wide areas such as energy, environment, and medicine. In this work, batch and continuous experiments of BIS synthesis were conducted. The experimental data and reaction engineering approach were used to estimate key reaction kinetics relevant to BIS formation over a range of pH. The BIS synthesis was performed in a continuous mode using CSTR and bubble column reactors, resulting in yields comparable to small-scale batch experiments. Using the experimental results and the models, the effects of residence time and feed concentrations were investigated, and optimum conditions were identified. These outcomes will be useful for the scale-up of BIS synthesis, reactor design, and optimization of sustainable manufacturing of high-value silicas. • Developed a pH-dependent kinetic model for the bio-inspired synthesis of silica (BIS) • Demonstrated continuous synthesis of BIS • Developed a reaction engineering model for optimization BIS process • Potential for tailoring properties of particles via BIS Kinetics ; Porosity ; Chemical engineering ; Materials science ; Process engineering ; Chemistry ; Biological system ; Engineering ; Composite material ; Physics Diatoms and Algae Research ; Mesoporous Materials and Catalysis ; Algal biology and biofuel production
Authors: Adrianna Fałowska | Martyna Ząbkowska | Karol Sambora | Karolina Kula | Agnieszka Łapczuk-Krygier | Radomir Jasiński
Source: Current Chemistry Letters (article, 2025-12-04)
Field: Chemistry — Organic Chemistry

Application of DFT models for the prediction of geometries and energies of the transition states in [4+2]-π -electron cycloadditions The usefulness of various quantum chemical algorithms (semiempirical, HF, DFT) for predicting the energy and geometry of transition states of polar pseudocyclic processes was analyzed using the example of a model cycloaddition process between (Z)-C,N-diphenylnitrone and (E)-2-phenyl-1-nitroethene. These studies clearly recommend the ωB97XD functional in 6-311+G(d) basis set as the relatively most precise tool for studying the mechanisms of polar pseudocyclic processes. Quantum chemical ; Basis set ; Polar ; Transition state ; Set (abstract data type) ; Process (computing) ; Quantum ; Cycloaddition Organic Chemistry Cycloaddition Reactions ; Advanced Chemical Physics Studies ; Cyclization and Aryne Chemistry
Authors: Yong Ju Lee | Chang Woo Jeong | Mi‐Jung Choi | T.Y. Lee | Hyoung Jin Kim
Source: Journal of Chemometrics (article, 2025-07-29)
Field: Chemistry — Analytical Chemistry

Infrared Spectroscopy and Machine Learning for Classification of Red Stamp Inks on Questioned Documents ABSTRACT This study demonstrates that integrating infrared spectroscopy with machine learning enables highly accurate, nondestructive classification of red‐stamp ink manufacturers. We evaluated five classifiers—partial least squares discriminant analysis (PLS‐DA), k‐nearest neighbor (k‐NN), support vector machine (SVM), random forest (RF), and a feed‐forward neural network (FNN)—across multiple spectral regions. The FNN trained on second‐derivative spectra in the 1700–900 cm −1 region achieved perfect test metrics (F1 = 1.000; AUC = 1.000), while PLS‐DA and RF also performed robustly (F1 ≥ 0.933). Variable importance in projection (VIP) analysis identified the 1650–1100 cm −1 subrange as most informative, streamlining feature selection and model training. Applied to three unknown samples, the optimized FNN produced high‐confidence manufacturer predictions consistent with expected origins. These results confirm that targeted spectral selection combined with derivative preprocessing markedly enhances nondestructive ink classification for forensic applications. Spectroscopy ; Infrared spectroscopy ; Chemometrics ; Infrared ; Computer science ; Artificial intelligence ; Materials science ; Polymer science ; Analytical Chemistry (journal) ; Information retrieval ; Chemistry ; Machine learning ; Optics ; Chromatography ; Physics ; Organic chemistry Spectroscopy and Chemometric Analyses ; Cultural Heritage Materials Analysis ; Remote-Sensing Image Classification
Authors: Ikechukwu A. Nnanwube | Fidelis Obidi Ochili | Okechukwu D. Onukwuli | Monday Omotioma
Source: Discover Applied Sciences (article, 2025-06-04)
Field: Materials Science — Materials Chemistry

Investigating expired Esofag-D as an eco-friendly corrosion inhibitor for aluminium-6061 in sulfuric acid: experimental, theoretical, and optimization approaches The inhibitive effect of expired esofag-d on aluminium-6061 corrosion in 1 M H2SO4 solution was investigated via experimental and theoretical methods, supplemented by optimization using response surface methodology (RSM). Fourier transform infrared (FTIR) spectroscopy and gas chromatography-mass spectrometry (GC–MS) were deployed to characterise the inhibitor. The inhibition efficiency (IE) of esofag-d increased with the rise in esofag’s concentration and decreased as temperature increased. The FTIR analysis results showed the existence of heteroatoms in the drug. GC–MS results indicated that the drug contains diethyl phthalate, pentadecane, tridecane, octadecane, nonadecane, tetradecanoic acid, sulfurous acid, 2-propyl tridecyl ester, n-hexadecanoic acid, dodecanoic acid, among other compounds that contain heteroatoms. The adsorption study performed shows that the Langmuir model gave the finest description of the experimental data. Potentiodynamic polarization results revealed that esofag-d is a mixed-type inhibitor. Nyquist plot from the electrochemical impedance spectroscopy study gave depressed semi-circles and corrosion inhibition efficiency of 95.92%. DFT parameters further confirm the inhibitive ability of the inhibitor. RSM was used to model the combined effect of the variables on the corrosion process. RSM modelling gave an optimum IE of 92.03%, which was further improved by artificial neural network (ANN) modelling. The results obtained show that esofag-d is a good inhibitor for aluminium-6061. Hence, this study has established the viability of expired pharmaceuticals such as expired esofag-d in the corrosion inhibition of Al-6061. Sulfuric acid ; Aluminium ; Environmentally friendly ; Corrosion inhibitor ; Corrosion ; Metallurgy ; Chemistry ; Materials science ; Biology Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Pieter Samyn | Patrick Cosemans
Source: Polymers (article, 2025-12-12)
Field: Materials Science — Polymers and Plastics

Substituting Fossil-Based into Bio-Based Isocyanates for Resin and Dispersion Polyurethane Coatings: Evaluation of Thermal, Mechanical, and Chemical Performance This study investigates the substitution of fossil-based isocyanates with bio-based alternatives in polyurethane resin (PU) coatings and polyurethane dispersion (PUD) coatings, focusing on mechanical and thermal performance. The coatings were formulated using bio-based pentamethylene diisocyanate (PDI) and a range of fossil-based hexamethylene diisocyanate (HDI) trimers, combined with either a polyester polyol or a polyacrylate polyol. Differential-scanning calorimetry analysis revealed that PDI-based coatings exhibit higher reactivity during crosslinking, resulting in higher glass transition temperatures. Thermogravimetric analysis showed lower thermal stability compared to HDI-based polyurethanes, indicating increased rigidity but reduced thermal resilience. Mechanical testing of the coatings on wood showed superior microhardness, scratch resistance, and wear resistance for PDI-based coatings, particularly when combined with polyester polyols. Microscopic surface evaluation and roughness analysis confirmed smoother morphologies and lower crack densities in PDI-polyester coatings. Gloss and water contact angle measurements further demonstrated improved surface uniformity and hydrophobicity for PDI-based coatings. The FTIR spectroscopy validated the chemical integrity and more intense hydrogen bonding for PDI-based coatings. The post-wear spectra indicated chemical oxidation and surface rearrangements in PDI-based systems and mechanical degradation with chain scission for HDI-based coatings. Overall, the study highlights that bio-based PDI trimers can effectively replace fossil-based HDI trimers in PU and PUD coatings without compromising mechanical performance, especially when paired with polyester polyols. These findings support the development of more sustainable polyurethane coatings with enhanced durability and environmental compatibility. Polyurethane ; Hexamethylene diisocyanate ; Thermogravimetric analysis ; Contact angle ; Polyester ; Thermal stability ; Glass transition ; Fourier transform infrared spectroscopy ; Dynamic mechanical analysis Polymer composites and self-healing ; Lignin and Wood Chemistry ; Carbon dioxide utilization in catalysis