On the public citation graph
A Bayesian Approach to Predict Solubility Parameters
0 signed · 168 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(issn)1099-0488openalex-snapshot
Journal of Polymer Science Part B: Polymer Physics
inferredcites →https://doi.org/10.1002/(issn)1521-3919openalex-snapshot
Macromolecular Theory and Simulations
inferredcites →https://doi.org/10.1002/actp.1995.010460101openalex-snapshot
Macromolecular chemistry and physics 1994
inferredcites →https://doi.org/10.1002/adfm.201301509openalex-snapshot
Solubility Based Identification of Green Solvents for Small Molecule Organic Solar Cells
inferredcites →https://doi.org/10.1002/adma.200903528openalex-snapshot
For the Bright Future—Bulk Heterojunction Polymer Solar Cells with Power Conversion Efficiency of 7.4%
inferredcites →https://doi.org/10.1002/aenm.201000054openalex-snapshot
A Systematic Approach to Solvent Selection Based on Cohesive Energy Densities in a Molecular Bulk Heterojunction System
inferredcites →https://doi.org/10.1002/aenm.201300752openalex-snapshot
Guiding the Selection of Processing Additives for Increasing the Efficiency of Bulk Heterojunction Polymeric Solar Cells
inferredcites →https://doi.org/10.1002/aenm.201602242openalex-snapshot
Small is Powerful: Recent Progress in Solution‐Processed Small Molecule Solar Cells
inferredcites →https://doi.org/10.1002/aenm.201703058openalex-snapshot
Miscibility–Function Relations in Organic Solar Cells: Significance of Optimal Miscibility in Relation to Percolation
inferredcites →https://doi.org/10.1002/app.38051openalex-snapshot
Generalizing solubility parameter theory to apply to one‐ and two‐dimensional solutes and to incorporate dipolar interactions
inferredcites →https://doi.org/10.1002/cem.2996openalex-snapshot
Modeling of Hansen's solubility parameters of aripiprazole, ziprasidone, and their impurities: A nonparametric comparison of models for prediction of drug absorption sites
inferredcites →https://doi.org/10.1002/cphc.201402734openalex-snapshot
Classification of Additives for Organic Photovoltaic Devices
inferredcites →https://doi.org/10.1002/jcc.20495openalex-snapshot
Semiempirical GGA‐type density functional constructed with a long‐range dispersion correction
inferredcites →https://doi.org/10.1002/jcc.540141106openalex-snapshot
Optimization and application of lithium parameters for PM3
inferredcites →https://doi.org/10.1002/macp.201100284openalex-snapshot
Determination of Solubility Parameters for Organic Semiconductor Formulations
inferredcites →https://doi.org/10.1002/mats.200800063openalex-snapshot
Application of QSPR to Binary Polymer/Solvent Mixtures: Prediction of Flory‐Huggins Parameters
inferredcites →https://doi.org/10.1002/polb.23153openalex-snapshot
Molecular solubility and hansen solubility parameters for the analysis of phase separation in bulk heterojunctions
inferredcites →https://doi.org/10.1006/jcph.1995.1039openalex-snapshot
Fast Parallel Algorithms for Short-Range Molecular Dynamics
inferredcites →https://doi.org/10.1007/978-1-4419-6247-8openalex-snapshot
Encyclopedic Dictionary of Polymers
inferredcites →https://doi.org/10.1007/s00894-012-1667-xopenalex-snapshot
Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters
inferredcites →https://doi.org/10.1007/s11095-014-1487-zopenalex-snapshot
Computational Prediction of Drug Solubility in Fasted Simulated and Aspirated Human Intestinal Fluid
inferredcites →https://doi.org/10.1007/s11095-018-2343-3openalex-snapshot
Cocrystal Solubility Product Prediction Using an in combo Model and Simulations to Improve Design of Experiments
inferredcites →https://doi.org/10.1016/j.ejpb.2016.02.009openalex-snapshot
Application of Hansen Solubility Parameters to predict drug–nail interactions, which can assist the design of nail medicines
inferredcites →https://doi.org/10.1016/j.fluid.2011.06.030openalex-snapshot
Estimation of Hansen solubility parameters using multivariate nonlinear QSPR modeling with COSMO screening charge density moments
inferredcites →https://doi.org/10.1016/j.ijpharm.2011.01.030openalex-snapshot
Hansen solubility parameter as a tool to predict cocrystal formation
inferredcites →https://doi.org/10.1016/j.nanoen.2013.03.009openalex-snapshot
The role of miscibility in polymer:fullerene nanoparticulate organic photovoltaic devices
inferredcites →https://doi.org/10.1016/j.solmat.2012.01.005openalex-snapshot
Determination of the P3HT:PCBM solubility parameters via a binary solvent gradient method: Impact of solubility on the photovoltaic performance
inferredcites →https://doi.org/10.1016/s0169-409x(00)00129-0openalex-snapshot
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1
inferredcites →https://doi.org/10.1016/s0378-5173(01)00838-9openalex-snapshot
Determination of partial solubility parameters of five benzodiazepines in individual solvents
inferredcites →https://doi.org/10.1016/s0378-5173(96)04828-4openalex-snapshot
The use of solubility parameters in pharmaceutical dosage form design
inferredcites →https://doi.org/10.1016/s0378-5173(99)00374-9openalex-snapshot
The modified extended Hansen method to determine partial solubility parameters of drugs containing a single hydrogen bonding group and their sodium derivatives: benzoic acid/Na and ibuprofen/Na
inferredcites →https://doi.org/10.1016/s0939-6411(99)00055-7openalex-snapshot
Solubility parameter and oral absorption
inferredcites →https://doi.org/10.1021/acs.jcim.6b00332openalex-snapshot
MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes
inferredcites →https://doi.org/10.1021/acs.jmedchem.7b00696openalex-snapshot
A Simple Representation of Three-Dimensional Molecular Structure
inferredcites →https://doi.org/10.1021/acs.jpcb.6b00787openalex-snapshot
Combined Computational Approach Based on Density Functional Theory and Artificial Neural Networks for Predicting The Solubility Parameters of Fullerenes
inferredcites →https://doi.org/10.1021/acs.jpcc.7b03228openalex-snapshot
Introducing a New Potential Figure of Merit for Evaluating Microstructure Stability in Photovoltaic Polymer-Fullerene Blends
inferredcites →https://doi.org/10.1021/acsami.5b02202openalex-snapshot
Molecular-Scale Understanding of Cohesion and Fracture in P3HT:Fullerene Blends
inferredcites →https://doi.org/10.1021/acsami.7b00401openalex-snapshot
Suppression of Thermally Induced Fullerene Aggregation in Polyfullerene-Based Multiacceptor Organic Solar Cells
inferredcites →https://doi.org/10.1021/cen-v083n019.p031openalex-snapshot
JOURNAL OF CHEMICAL INFORMATION AND MODELING
inferredcites →https://doi.org/10.1021/ci800058vopenalex-snapshot
Solubility Challenge: Can You Predict Solubilities of 32 Molecules Using a Database of 100 Reliable Measurements?
inferredcites →https://doi.org/10.1021/ie060370hopenalex-snapshot
Sigma-Profile Database for Using COSMO-Based Thermodynamic Methods
inferredcites →https://doi.org/10.1021/ja00051a040openalex-snapshot
UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations
inferredcites →https://doi.org/10.1021/jp070186popenalex-snapshot
DFTB+, a Sparse Matrix-Based Implementation of the DFTB Method
inferredcites →https://doi.org/10.1021/jz501559qopenalex-snapshot
Influence of Molecular Shape on Solid-State Packing in Disordered PC61BM and PC71BM Fullerenes
inferredcites →https://doi.org/10.1021/ma200855ropenalex-snapshot
Polymer Crystallization of Partially Miscible Polythiophene/Fullerene Mixtures Controls Morphology
inferredcites →https://doi.org/10.1021/ma400597jopenalex-snapshot
Determination of Solvent–Polymer and Polymer–Polymer Flory–Huggins Interaction Parameters for Poly(3-hexylthiophene) via Solvent Vapor Swelling
inferredcites →https://doi.org/10.1021/ma5021227openalex-snapshot
In Situ Characterization of Polymer–Fullerene Bilayer Stability
inferredcites →https://doi.org/10.1021/ma901350wopenalex-snapshot
Block Copolymers for Organic Optoelectronics
inferredcites →https://doi.org/10.1021/nn900493uopenalex-snapshot
Multicomponent Solubility Parameters for Single-Walled Carbon Nanotube−Solvent Mixtures
inferredcites →https://doi.org/10.1023/a:1015865025862openalex-snapshot
Significance of Partial and Total Cohesion Parameters of Pharmaceutical Solids Determined from Dissolution Calorimetric Measurements
inferredcites →https://doi.org/10.1038/ncomms14541openalex-snapshot
Abnormal strong burn-in degradation of highly efficient polymer solar cells caused by spinodal donor-acceptor demixing
inferredcites →https://doi.org/10.1038/s41578-018-0005-zopenalex-snapshot
Accelerating the discovery of materials for clean energy in the era of smart automation
inferredcites →https://doi.org/10.1039/1463-9084/1999openalex-snapshot
Physical Chemistry Chemical Physics
inferredcites →https://doi.org/10.1039/b508541aopenalex-snapshot
Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: Design and assessment of accuracy
inferredcites →https://doi.org/10.1039/c5cp00288eopenalex-snapshot
A review of methods for the calculation of solution free energies and the modelling of systems in solution
inferredcites →https://doi.org/10.1039/c7ta03505eopenalex-snapshot
Understanding the correlation and balance between the miscibility and optoelectronic properties of polymer–fullerene solar cells
inferredcites →https://doi.org/10.1039/p29930000799openalex-snapshot
COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient
inferredcites →https://doi.org/10.1080/08927020412331308539openalex-snapshot
Nanotube–polymer composites: insights from Flory–Huggins theory and mesoscale simulations
inferredcites →https://doi.org/10.1093/nar/gkv951openalex-snapshot
PubChem Substance and Compound databases
inferredcites →https://doi.org/10.1103/physreva.38.3098openalex-snapshot
Density-functional exchange-energy approximation with correct asymptotic behavior
inferredcites →https://doi.org/10.1103/physrevb.33.8822openalex-snapshot
Density-functional approximation for the correlation energy of the inhomogeneous electron gas
inferredcites →https://doi.org/10.1109/tpami.2013.159openalex-snapshot
Learning Nonlinear Functions Using Regularized Greedy Forest
inferredcites →https://doi.org/10.1111/(issn)1759-0884openalex-snapshot
Wiley Interdisciplinary Reviews: Computational Molecular Science
inferredcites →https://doi.org/10.1126/scirobotics.aat5559openalex-snapshot
ChemOS: Orchestrating autonomous experimentation
inferredcites →https://doi.org/10.1201/9781420006834.ch1openalex-snapshot
Solubility Parameters - An Introduction
inferredcites →https://doi.org/10.3929/ethz-b-000278021openalex-snapshot
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.5935/0103-5053.20130250openalex-snapshot
Determining Hildebrand Solubility Parameter by Ultraviolet Spectroscopy and Microcalorimetry
inferredcites →https://doi.org/10.7551/mitpress/3206.001.0001openalex-snapshot
Gaussian Processes for Machine Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4770184openalex-extracted
Molecular and Graph-Based Theory: A Reliable Solution for Estimating Three-Dimensional Hansen Solubility
inferred← citeshttps://doi.org/10.1002/9783527832767.ch21openalex-snapshot
Machine Learning for FB Electrolyte Screening
inferred← citeshttps://doi.org/10.1002/9783527833658.ch14openalex-snapshot
Morphological Characterization and Manipulation of Organic Solar Cells
inferred← citeshttps://doi.org/10.1002/adfm.202531987openalex-snapshot
Strategies for Loading and Releasing Peptide Therapeutics in Biodegradable Carriers
inferred← citeshttps://doi.org/10.1002/adma.201808256openalex-snapshot
Toward Design of Novel Materials for Organic Electronics
inferred← citeshttps://doi.org/10.1002/adma.202413695openalex-snapshot
Machine Learning in Polymer Research
inferred← citeshttps://doi.org/10.1002/adts.201800180openalex-snapshot
Materials‐Informatics‐Assisted High‐Yield Synthesis of 2D Nanomaterials through Exfoliation
inferred← citeshttps://doi.org/10.1002/adts.202000001openalex-snapshot
Predicting Solubility of Small Molecules in Macromolecular Compounds for Nanomedicine Application from Atomistic Simulations
inferred← citeshttps://doi.org/10.1002/adts.202000084openalex-snapshot
Efficient Syntheses of 2D Materials from Soft Layered Composites Guided by Yield Prediction Model: Potential of Experiment‐Oriented Materials Informatics
inferred← citeshttps://doi.org/10.1002/adts.202501865openalex-snapshot
Machine Learning Meets Molecular Dynamics: Accurate Prediction of Polymer Solubility Parameters
inferred← citeshttps://doi.org/10.1002/advs.202307152openalex-snapshot
Recent Progress in Dopant‐Free and Green Solvent‐Processable Organic Hole Transport Materials for Efficient and Stable Perovskite Solar Cells
inferred← citeshttps://doi.org/10.1002/aenm.201902463openalex-snapshot
Concurrent Optimization of Organic Donor–Acceptor Pairs through Machine Learning
inferred← citeshttps://doi.org/10.1002/aisy.202100261openalex-snapshot
Performance Prediction and Experimental Optimization Assisted by Machine Learning for Organic Photovoltaics
inferred← citeshttps://doi.org/10.1002/ange.202312231openalex-snapshot
Green Solvent Processable, Asymmetric Dopant‐Free Hole Transport Layer Material for Efficient and Stable n‐i‐p Perovskite Solar Cells and Modules
inferred← citeshttps://doi.org/10.1002/anie.202312231openalex-snapshot
Green Solvent Processable, Asymmetric Dopant‐Free Hole Transport Layer Material for Efficient and Stable n‐i‐p Perovskite Solar Cells and Modules
inferred← citeshttps://doi.org/10.1002/cphc.201900793openalex-snapshot
Building Blocks for High‐Efficiency Organic Photovoltaics: Interplay of Molecular, Crystal, and Electronic Properties in Post‐Fullerene ITIC Ensembles
inferred← citeshttps://doi.org/10.1002/jcc.26947openalex-snapshot
Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas‐phase structures of organic molecules
inferred← citeshttps://doi.org/10.1002/qute.202000003openalex-snapshot
Variational Quantum Generators: Generative Adversarial Quantum Machine Learning for Continuous Distributions
inferred← citeshttps://doi.org/10.1002/solr.202300490openalex-snapshot
Assessing Performance and Limitations of a Device‐Level Machine Learning Approach for Perovskite Solar Cells with an Application to Hole Transport Materials
inferred← citeshttps://doi.org/10.1007/s10118-022-2716-2openalex-snapshot
A Machine Learning Study of Polymer-Solvent Interactions
inferred← citeshttps://doi.org/10.1016/j.bmc.2022.116614openalex-snapshot
Structural modification aimed for improving solubility of lead compounds in early phase drug discovery
inferred← citeshttps://doi.org/10.1016/j.cemconres.2020.106173openalex-snapshot
Cheminformatics for accelerated design of chemical admixtures
inferred← citeshttps://doi.org/10.1016/j.ces.2021.117184openalex-snapshot
Estimation of Hansen solubility parameters with regularized regression for biomass conversion products: An application of adaptable group contribution
inferred← citeshttps://doi.org/10.1016/j.chemolab.2024.105168openalex-snapshot
Enhancing Hansen Solubility Predictions with Molecular and Graph-Based Approaches
inferred← citeshttps://doi.org/10.1016/j.chemolab.2025.105553openalex-snapshot
Advancing chemical manufacturing processes through data-driven approaches: A survey
inferred← citeshttps://doi.org/10.1016/j.cocis.2026.102044openalex-snapshot
Solubility prediction for ill-defined polymers: A critical comparison of Hansen parameters and COSMO-RS backfitting
inferred← citeshttps://doi.org/10.1016/j.commatsci.2026.114493openalex-snapshot
From prediction to understanding: A review of XAI applications and innovations in materials science
inferred← citeshttps://doi.org/10.1016/j.compchemeng.2023.108291openalex-snapshot
Application of interpretable group-embedded graph neural networks for pure compound properties
inferred← citeshttps://doi.org/10.1016/j.dche.2024.100207openalex-snapshot
Ensemble machine learning to accelerate industrial decarbonization: Prediction of Hansen solubility parameters for streamlined chemical solvent selection
inferred← citeshttps://doi.org/10.1016/j.giant.2023.100171openalex-snapshot
Integrating theory with machine learning for predicting polymer solution phase behavior
inferred← citeshttps://doi.org/10.1016/j.isci.2024.109200openalex-snapshot
Unveiling dominant recombination loss in perovskite solar cells with a XGBoost-based machine learning approach
inferred← citeshttps://doi.org/10.1016/j.jhazmat.2024.134012openalex-snapshot
Experimental analysis and prediction of radionuclide solubility using machine learning models: Effects of organic complexing agents
inferred← citeshttps://doi.org/10.1016/j.molliq.2020.112587openalex-snapshot
Gelation properties of various long chain amidoamines: Prediction of solvent gelation via machine learning using Hansen solubility parameters
inferred← citeshttps://doi.org/10.1016/j.molliq.2023.122669openalex-snapshot
Assessment of Hansen solubility parameters in deep eutectic solvents for solubility predictions
inferred← citeshttps://doi.org/10.1016/j.pmatsci.2025.101544openalex-snapshot
Machine learning in polymer science: A new lens for physical and chemical exploration
inferred← citeshttps://doi.org/10.1016/j.xcrp.2021.100346openalex-snapshot
Identification of the dominant recombination process for perovskite solar cells based on machine learning
inferred← citeshttps://doi.org/10.1021/acs.chemrev.4c00855openalex-snapshot
Physics-Based Solubility Prediction for Organic Molecules
inferred← citeshttps://doi.org/10.1021/acs.iecr.0c05923openalex-snapshot
Computer-Aided Design of New Physical Solvents for Hydrogen Sulfide Absorption
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00656openalex-snapshot
Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers
inferred← citeshttps://doi.org/10.1021/acs.jpcb.4c00581openalex-snapshot
Correlations of Surface Free Energy and Solubility Parameters with Dielectric Constant, Refractive Index, and Density for Liquids
inferred← citeshttps://doi.org/10.1021/acs.jpcc.0c01195openalex-snapshot
Learning from the Machine: Uncovering Sustainable Nanoparticle Design Rules
inferred← citeshttps://doi.org/10.1021/acs.langmuir.2c00677openalex-snapshot
Domination of H-Bond Interactions in the Solvent-Triggering Gelation Process
inferred← citeshttps://doi.org/10.1021/acs.macromol.0c00251openalex-snapshot
A Deep Learning Solvent-Selection Paradigm Powered by a Massive Solvent/Nonsolvent Database for Polymers
inferred← citeshttps://doi.org/10.1021/acs.macromol.2c02600openalex-snapshot
Multitask Machine Learning to Predict Polymer–Solvent Miscibility Using Flory–Huggins Interaction Parameters
inferred← citeshttps://doi.org/10.1021/acs.macromol.5c00178openalex-snapshot
Polymer Informatics Method for Fast and Accurate Prediction of the Glass Transition Temperature from Chemical Structure
inferred← citeshttps://doi.org/10.1021/acs.oprd.6c00057openalex-snapshot
Automation in Pharmaceutical Crystallization
inferred← citeshttps://doi.org/10.1021/acsami.0c21036openalex-snapshot
Predicting the Mixing Behavior of Aqueous Solutions Using a Machine Learning Framework
inferred← citeshttps://doi.org/10.1021/acsapm.5c04680openalex-snapshot
Hierarchical Virtual Screening for Plasticizer Discovery with Active Learning
inferred← citeshttps://doi.org/10.1021/acsmacrolett.1c00117openalex-snapshot
Deep Learning of Binary Solution Phase Behavior of Polystyrene
inferred← citeshttps://doi.org/10.1021/acsmaterialslett.5c00054openalex-snapshot
Polymer Solubility Prediction Using Large Language Models
inferred← citeshttps://doi.org/10.1021/acsnano.0c00384openalex-snapshot
From Absorption Spectra to Charge Transfer in Nanoaggregates of Oligomers with Machine Learning
inferred← citeshttps://doi.org/10.1021/acsnano.1c02104openalex-snapshot
Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy
inferred← citeshttps://doi.org/10.1021/acsomega.8b02601openalex-snapshot
Pencil and Paper Estimation of Hansen Solubility Parameters
inferred← citeshttps://doi.org/10.1021/acspolymersau.5c00177openalex-snapshot
Identifying Polymers that Bind or Reject Proteins with Machine Learning: Handling Categorical Features within a GPR Model
inferred← citeshttps://doi.org/10.1021/acssusresmgt.4c00122openalex-snapshot
Maximized Lanthanide Extraction Using Supercritical CO2 and Fluorinated Organophosphate Extractants
inferred← citeshttps://doi.org/10.1038/s41467-020-17995-8openalex-snapshot
Designing and understanding light-harvesting devices with machine learning
inferred← citeshttps://doi.org/10.1038/s41467-024-47070-5openalex-snapshot
An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations
inferred← citeshttps://doi.org/10.1038/s41524-019-0209-9openalex-snapshot
Machine learning enables polymer cloud-point engineering via inverse design
inferred← citeshttps://doi.org/10.1038/s41524-023-01040-5openalex-snapshot
Sizing up feature descriptors for macromolecular machine learning with polymeric biomaterials
inferred← citeshttps://doi.org/10.1038/s41560-022-01167-7openalex-snapshot
High-performing organic electronics using terpene green solvents from renewable feedstocks
inferred← citeshttps://doi.org/10.1038/s41598-025-87050-3openalex-snapshot
Application of Hansen solubility parameters in the eutectic mixtures: difference between empirical and semi-empirical models
inferred← citeshttps://doi.org/10.1038/s44286-025-00247-1openalex-snapshot
Solvent-based plastic recycling technologies
inferred← citeshttps://doi.org/10.1039/9781837677832-00001openalex-snapshot
Chlorinated Solvent Properties and Indexes
inferred← citeshttps://doi.org/10.1039/c9ta07361bopenalex-snapshot
Blade coated P3HT:non-fullerene acceptor solar cells: a high-throughput parameter study with a focus on up-scalability
inferred← citeshttps://doi.org/10.1039/d1gc03798fopenalex-snapshot
Prediction of solubility parameters of lignin and ionic liquids using multi-resolution simulation approaches
inferred← citeshttps://doi.org/10.1039/d2cp03735aopenalex-snapshot
Solvent selection for polymers enabled by generalized chemical fingerprinting and machine learning
inferred← citeshttps://doi.org/10.1039/d2dd00146bopenalex-snapshot
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS
inferred← citeshttps://doi.org/10.1039/d2ma00598kopenalex-snapshot
Large variability and complexity of isothermal solubility for a series of redox-active phenothiazines
inferred← citeshttps://doi.org/10.1039/d2me00023gopenalex-snapshot
Recent development in machine learning of polymer membranes for liquid separation
inferred← citeshttps://doi.org/10.1039/d2ta00743fopenalex-snapshot
Discovery of lead low-potential radical candidates for organic radical polymer batteries with machine-learning-assisted virtual screening
inferred← citeshttps://doi.org/10.1039/d3cp00177fopenalex-snapshot
Easy and fast prediction of green solvents for small molecule donor-based organic solar cells through machine learning
inferred← citeshttps://doi.org/10.1039/d3dd00119aopenalex-snapshot
Using natural language processing (NLP)-inspired molecular embedding approach to predict Hansen solubility parameters
inferred← citeshttps://doi.org/10.1039/d4ra01433bopenalex-snapshot
Flash precipitation of random copolymers in a micro-mixer for controlling the size and surface charge of nanoparticles
inferred← citeshttps://doi.org/10.1039/d4sm00590bopenalex-snapshot
Predicting polymer solubility from phase diagrams to compatibility: a perspective on challenges and opportunities
inferred← citeshttps://doi.org/10.1039/d5gc03161copenalex-snapshot
Green solvents in membrane separation: progress, challenges, and future perspectives for sustainable industrial applications
inferred← citeshttps://doi.org/10.1039/d5ra07380dopenalex-snapshot
Overcoming colorectal cancer and cancer stem cell resistance with photodynamic therapy: new frontiers in oncology
inferred← citeshttps://doi.org/10.1063/5.0014828openalex-snapshot
Classification of biomass reactions and predictions of reaction energies through machine learning
inferred← citeshttps://doi.org/10.1073/pnas.2404676121openalex-snapshot
Stochastic machine learning via sigma profiles to build a digital chemical space
inferred← citeshttps://doi.org/10.1088/2632-2153/ad020dopenalex-snapshot
Deep Bayesian experimental design for quantum many-body systems
inferred← citeshttps://doi.org/10.1515/revce-2023-0021openalex-snapshot
A perspective on data-driven screening and discovery of polymer membranes for gas separation, from the molecular structure to the industrial performance
inferred← citeshttps://doi.org/10.1557/mrc.2019.90openalex-snapshot
Embedding domain knowledge for machine learning of complex material systems
inferred← citeshttps://doi.org/10.2118/212790-msopenalex-snapshot
A Review-Dissolution and Mineralization Storage of CO2 Geological Storage in Saline Aquifers
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-hmml5openalex-snapshot
Predicting solvents with the help of Artificial Intelligence
inferred← citeshttps://doi.org/10.30574/wjarr.2021.12.3.0680openalex-snapshot
Theoretical consideration of solubility by Hildebrand solubility approach
inferred← citeshttps://doi.org/10.33612/diss.160806040openalex-snapshot
Lessons learned from device modeling of organic & perovskite solar cells
inferred← citeshttps://doi.org/10.3389/fchem.2019.00809openalex-snapshot
Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns
inferred← citeshttps://doi.org/10.3390/axioms10030178openalex-snapshot
A Method for Visualizing Posterior Probit Model Uncertainty in the Early Prediction of Fraud for Sustainability Development
inferred← citeshttps://doi.org/10.3390/en17092011openalex-snapshot
Estimation of Fuel Properties for the Heavy Fraction of Biomass Pyrolysis Oil Consisting of Proposed Structures for Pyrolytic Lignin and Humins
inferred← citeshttps://doi.org/10.3390/molecules26216362openalex-snapshot
Applying Active Learning to the Screening of Molecular Oxygen Evolution Catalysts
inferred← citeshttps://doi.org/10.3390/polym13060937openalex-snapshot
Removing Acrylic Conformal Coating with Safer Solvents for Re-Manufacturing Electronics
inferred← citeshttps://doi.org/10.3390/pr10010066openalex-snapshot
Chemical Recycling of Mixed Plastics in Electronic Waste Using Solvent-Based Processing
inferred← citeshttps://doi.org/10.4028/p-v9fyriopenalex-snapshot
Enhancing Hansen Solubility Predictions: A Combined Approach Using Integrated Datasets and Optimized Machine Learning Techniques
inferred← citeshttps://doi.org/10.70675/07975f61z019bz4c08zaae4z2fcda6cc9032openalex-snapshot
On the use of Machine Learning modeling tools in chemical process and product engineering
inferred← citeshttps://doi.org/10.7567/1347-4065/ab4f39openalex-snapshot
A high throughput molecular screening for organic electronics via machine learning: present status and perspective
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.