Research Articles
Bridging the Gap: A Researcher's Guide to Handling Discrepancies Between Computational and Experimental Results
This article provides a comprehensive framework for researchers and drug development professionals to systematically identify, analyze, and resolve discrepancies between computational models and experimental data.
Strategic Balance: Optimizing Cost and Accuracy in High-Throughput Screening Workflows
This article provides a comprehensive guide for researchers and drug development professionals on navigating the critical trade-off between computational/resource expenditure and data accuracy in High-Throughput Screening (HTS).
Beyond the Standard Functional: Advanced Strategies to Improve the Accuracy of DFT Predictions for Material Properties
Density Functional Theory (DFT) is a cornerstone of computational materials science, yet its predictive accuracy is often limited by approximations in the exchange-correlation functional.
Combating False Positives in High-Throughput Screening: A Strategic Guide for Drug Discovery
False positives present a formidable challenge in high-throughput screening (HTS), leading to significant resource waste and delays in drug discovery.
Validating Iodine Capture Predictions in MOFs: From Computational Screening to Experimental Confirmation
This article synthesizes recent advancements in validating predictive models for iodine capture using metal-organic frameworks (MOFs), crucial for nuclear waste management and environmental remediation.
From Simulation to Synthesis: A Practical Guide to Validating Computed Bimetallic Catalysts
This article provides a comprehensive roadmap for researchers and scientists navigating the integrated process of computational prediction and experimental validation of bimetallic catalysts.
High-Throughput Computational-Experimental Screening: Accelerating Drug and Material Discovery
This article provides a comprehensive overview of high-throughput computational-experimental screening protocols, a transformative approach accelerating discovery in biomedicine and materials science.
Validating High-Throughput Screening of MOFs for Gas Adsorption: From Computational Prediction to Laboratory Reality
This article provides a comprehensive framework for the validation of high-throughput computational screening (HTS) of metal-organic frameworks (MOFs) for gas adsorption, a critical process in carbon capture and hydrogen purification.
Bridging Accuracy and Efficiency: Integrating DFT and Machine Learning for Next-Generation Material Validation
This article explores the transformative integration of Density Functional Theory (DFT) and Machine Learning (ML) for validating material properties, a critical step in accelerating materials discovery and drug development.
From In Silico to In Vitro: A Comprehensive Protocol for Experimental Validation in Computational Screening
This article provides a detailed framework for researchers and drug development professionals to bridge the critical gap between computational predictions and experimental reality.