Hongshuai Wang
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View article: Transfer learning discovery of molecular modulators for perovskite solar cells
Transfer learning discovery of molecular modulators for perovskite solar cells Open
The discovery of effective molecular modulators is essential for advancing perovskite solar cells (PSCs), but the research process is hindered by the vastness of chemical space and the time-consuming and expensive trial-and-error experimen…
View article: Virtual characterization via knowledge-enhanced representation learning: from organic conjugated molecules to devices
Virtual characterization via knowledge-enhanced representation learning: from organic conjugated molecules to devices Open
The rational design of organic functional devices relies on understanding structure-property-performance relationships through multi-scale characterization. However, traditional characterizations are costly and require multidisciplinary ex…
View article: Unifying Polymer Modeling and Design via a Conformation-Centric Generative Foundation Model
Unifying Polymer Modeling and Design via a Conformation-Centric Generative Foundation Model Open
Polymers, macromolecules formed from covalently bonded monomers, underpin countless technologies and are indispensable to modern life. While deep learning is advancing polymer science, existing methods typically represent the whole polymer…
View article: FAST AND FLEXIBLE 3D MOLECULE DESIGN FRAMEWORK FOR NOVEL ORGANIC OPTOELECTRONIC MATERIALS
FAST AND FLEXIBLE 3D MOLECULE DESIGN FRAMEWORK FOR NOVEL ORGANIC OPTOELECTRONIC MATERIALS Open
Organic optoelectronic materials (OOMs) are pivotal for advancing technologies such as organic photovoltaics and light-emitting diodes. Traditional methods for discovering new OOMs are inefficient and limited by chemical space exploration.…
View article: High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery Open
The escalating energy crisis has spurred extensive research into organic compounds for energy-efficient applications, taking advantage of their environmental friendliness, cost-effective synthesis, and adaptable molecular structures. Tradi…
View article: Study on Combustion and NOx Emission Characteristics of Low-Quality Coal with Wide Load Based on Fuel Modification
Study on Combustion and NOx Emission Characteristics of Low-Quality Coal with Wide Load Based on Fuel Modification Open
Enhancing the operational flexibility and environmental performance of coal-fired boilers under wide-load conditions presents a critical challenge in China’s low-carbon transition, particularly for low-quality coals (LQCs) with abundant re…
View article: Experimental Study on Peak Shaving with Self-Preheating Combustion Equipped with a Novel Compact Fluidized Modification Device
Experimental Study on Peak Shaving with Self-Preheating Combustion Equipped with a Novel Compact Fluidized Modification Device Open
Under the strategic objectives of carbon peaking and carbon neutrality, it is inevitable for large-scale integration of renewable energy into thermal power units. Nevertheless, improving the capacity of these units for flexible peak shavin…
View article: Virtual Characterization via Knowledge-Enhanced Representation Learning: from Organic Conjugated Molecules to Devices
Virtual Characterization via Knowledge-Enhanced Representation Learning: from Organic Conjugated Molecules to Devices Open
The rational design of organic functional devices relies on understanding structure–property–performance relationships through multi-scale characterization. However, traditional characterizations are costly and require multidisciplinary ex…
View article: PolyConf: Unlocking Polymer Conformation Generation through Hierarchical Generative Models
PolyConf: Unlocking Polymer Conformation Generation through Hierarchical Generative Models Open
Polymer conformation generation is a critical task that enables atomic-level studies of diverse polymer materials. While significant advances have been made in designing conformation generation methods for small molecules and proteins, the…
View article: Virtual Characterization via Knowledge-Enhanced Representation Learning: from Organic Conjugated Molecules to Devices
Virtual Characterization via Knowledge-Enhanced Representation Learning: from Organic Conjugated Molecules to Devices Open
Unlocking the potential of organic functional devices requires elucidating structure–property–performance relationships through comprehensive multiscale, multi property characterization. However, this process is limited by high costs and m…
View article: FAST AND FLEXIBLE 3D MOLECULE DESIGN FRAMEWORK FOR NOVEL ORGANIC OPTOELECTRONIC MATERIALS
FAST AND FLEXIBLE 3D MOLECULE DESIGN FRAMEWORK FOR NOVEL ORGANIC OPTOELECTRONIC MATERIALS Open
Organic optoelectronic materials (OOMs) are pivotal for advancing technologies such as organic photovoltaics and light-emitting diodes. Traditional methods for discovering new OOMs are inefficient and limited by chemical space exploration.…
View article: OCNet: A Domain Knowledge-Enhanced General Moleculer Representation Framework for Optoelectronic and Charge-transport Materials
OCNet: A Domain Knowledge-Enhanced General Moleculer Representation Framework for Optoelectronic and Charge-transport Materials Open
The characterization of material properties plays a crucial role in revealing the structure-property relationship and optimizing device performance. Organic optoelectronic and transporting materials, widely used in various fields, face cha…
View article: High-Accuracy Physical Property Prediction for Organics via Molecular Representation Learning: Bridging Data to Discovery
High-Accuracy Physical Property Prediction for Organics via Molecular Representation Learning: Bridging Data to Discovery Open
The ongoing energy crisis has underscored the urgent need for energy-efficient materials with high energy utilization efficiency, prompting a surge in research into organic compounds due to their environmental compatibility, cost-effective…
View article: End‐to‐End Crystal Structure Prediction from Powder X‐Ray Diffraction
End‐to‐End Crystal Structure Prediction from Powder X‐Ray Diffraction Open
Powder X‐ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse‐grained level. The mor…
View article: SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis Open
View article: A Prediction Method for Porosity in Autoclave-Cured Composites Based on a Physically-Grounded Cylindrical Void Growth Model
A Prediction Method for Porosity in Autoclave-Cured Composites Based on a Physically-Grounded Cylindrical Void Growth Model Open
View article: Data-Driven Parametrization of All-atom force fields for Organic Semiconductors
Data-Driven Parametrization of All-atom force fields for Organic Semiconductors Open
Organic semiconductors (OSCs) composed of π conjugated molecules have gained significant interest in the study of bulk properties such as molecular arrangement and electron mobility. However, the types of torsion in the traditional force f…
View article: Measuring and Monitoring Provincial Sustainable Development Goals in China
Measuring and Monitoring Provincial Sustainable Development Goals in China Open
View article: Towards a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts
Towards a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts Open
The study of structure-spectrum relationships is essential for spectral interpretation, impacting structural elucidation and material design. Predicting spectra from molecular structures is challenging due to their complex relationships. H…
View article: Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer Open
In scientific research and its application, scientific literature analysis is crucial as it allows researchers to build on the work of others. However, the fast growth of scientific knowledge has led to a massive increase in scholarly arti…
View article: A comprehensive transformer-based approach for high-accuracy gas adsorption predictions in metal-organic frameworks
A comprehensive transformer-based approach for high-accuracy gas adsorption predictions in metal-organic frameworks Open
View article: Statistics of cloud cover above the Ali Observatory, Tibet
Statistics of cloud cover above the Ali Observatory, Tibet Open
In this paper, the statistics of cloud cover at night from 2016 to 2018 above the Ali observatory has been summarized, using the meso-scale numerical model and the cameras (Canon and AllSky-340 Camera). Above the western Tibetan Plateau, i…
View article: End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction
End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction Open
Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse-grained level. The mor…
View article: Efficient screening framework for organic solar cells with deep learning and ensemble learning
Efficient screening framework for organic solar cells with deep learning and ensemble learning Open
Organic photovoltaics have attracted worldwide interest due to their unique advantages in developing low-cost, lightweight, and flexible power sources. Functional molecular design and synthesis have been put forward to accelerate the disco…
View article: Metal-organic frameworks meet Uni-MOF: a transformer-based gas adsorption detector
Metal-organic frameworks meet Uni-MOF: a transformer-based gas adsorption detector Open
Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks(MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulatio…
View article: Fast and accurate screening framework for organic solar cells based on molecular structure and deep learning
Fast and accurate screening framework for organic solar cells based on molecular structure and deep learning Open
Organic photovoltaics have attracted worldwide interest due to their unique advantages in developing low-cost, light-weight, and flexible power sources. Functional molecular design and synthesis have been put forward to accelerate the disc…
View article: Metal-organic frameworks meet Uni-MOF: a transformer-based gas adsorption detector
Metal-organic frameworks meet Uni-MOF: a transformer-based gas adsorption detector Open
Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks(MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulatio…
View article: Metal-organic frameworks meet Uni-MOF: a revolutionary gas adsorption detector
Metal-organic frameworks meet Uni-MOF: a revolutionary gas adsorption detector Open
Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks(MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulatio…
View article: Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction
Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction Open
Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery. However, most DL based QSAR models are restr…
View article: Manufacturing N,O-carboxymethyl chitosan-reduced graphene oxide under freeze-dying for performance improvement of Li-S battery
Manufacturing N,O-carboxymethyl chitosan-reduced graphene oxide under freeze-dying for performance improvement of Li-S battery Open
Lithium-sulfur (Li-S) batteries can provide far higher energy density than currently commercialized lithium ion batteries, but challenges remain before it they are used in practice. One of the challenges is the shuttle effect that originat…