Fine-tuning GPT-3 for machine learning electronic and functional properties of organic molecules
We evaluate the effectiveness of fine-tuning GPT-3 for the prediction of electronic and
functional properties of organic molecules. Our findings show that fine-tuned GPT-3 can …
functional properties of organic molecules. Our findings show that fine-tuned GPT-3 can …
Multifidelity machine learning for molecular excitation energies
The accurate but fast calculation of molecular excited states is still a very challenging topic.
For many applications, detailed knowledge of the energy funnel in larger molecular …
For many applications, detailed knowledge of the energy funnel in larger molecular …
Resilience of Hund's rule in the chemical space of small organic molecules
A Majumdar, R Ramakrishnan - Physical Chemistry Chemical Physics, 2024 - pubs.rsc.org
We embark on a quest to identify small molecules in the chemical space that can potentially
violate Hund's rule. Utilizing twelve TDDFT approximations and the ADC (2) many-body …
violate Hund's rule. Utilizing twelve TDDFT approximations and the ADC (2) many-body …
Machine Learning for the Design of Novel OLED Materials
One of the central paradigms in materials science is that data-driven methods will decrease
the time needed to develop optimal solutions. In other words, the time required to go from …
the time needed to develop optimal solutions. In other words, the time required to go from …
Optimized machine learning techniques enable prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum …
Applications of organic dyes, ranging from basic research to industry, are functions of their
photophysical properties. Two important aspects—(1) knowledge of the photophysical …
photophysical properties. Two important aspects—(1) knowledge of the photophysical …
Structure prediction from spectra amidst dynamical heterogeneity in melanin
Melanin is a biopolymer pigment that plays a central role in skin photoprotection. Its
extensive chemical and dynamical heterogeneity imparts this property through a broad …
extensive chemical and dynamical heterogeneity imparts this property through a broad …
Harnessing quantum power: Revolutionizing materials design through advanced quantum computation
Z Guo, R Li, X He, J Guo, S Ju - Materials Genome Engineering …, 2024 - Wiley Online Library
The design of advanced materials for applications in areas of photovoltaics, energy storage,
and structural engineering has made significant strides. However, the rapid proliferation of …
and structural engineering has made significant strides. However, the rapid proliferation of …
UV–visible absorption spectra of solvated molecules by quantum chemical machine learning
Predicting UV–visible absorption spectra is essential to understand photochemical
processes and design energy materials. Quantum chemical methods can deliver accurate …
processes and design energy materials. Quantum chemical methods can deliver accurate …
[HTML][HTML] Chemical design by artificial intelligence
Empirical principles and structure–property relations derived from chemical intuition have for
centuries driven the design and synthesis of materials and molecules. In recent years …
centuries driven the design and synthesis of materials and molecules. In recent years …
[HTML][HTML] Machine learning based hybrid ensemble models for prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths …
Fluorescent organic dyes are extensively used in the design and discovery of new materials,
photovoltaic cells, light sensors, imaging applications, medicinal chemistry, drug design …
photovoltaic cells, light sensors, imaging applications, medicinal chemistry, drug design …