We hereby sincerely invite you to visit our booth…
We Are Pleased to Announce #Lanya chemical Participation in the “Plast Eurasia Istanbul 2023 Fair”. We Invite You to Connect with the Industry’s Expertise and Explore the Latest Innovations in the Plastic Industry.
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CphI Barcelona 2023 opens its gates!
We are present at CPhI2023 in Barcelona, the world’s most important pharmaceutical event! Proud to be part of this community that brings together more than 47,000 professionals and 2,600 exhibitors from +150 countries. Meet us at Stand 80N26.
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Wire & Cable Compounding Solutions!
Lanya Chemical as we unveil our exceptional range of wire and cable additives. From the ever-reliable XLPE and PVC cables to innovative Electron Beam Curing Compounds, we’re powering the future of connectivity.
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Revolutionizing the Discovery of New Chemicals: T…
Introduction Artificial Intelligence (AI) has revolutionized numerous industries, and the field of chemistry is no exception. With its ability to process vast amounts of data, recognize patterns, and generate insights, AI is transforming the way scientists discover new chemicals. This article explores the impact of AI on chemical discovery, highlighting its benefits, challenges, and potential future developments. The Role of AI in Chemical Discovery Chemical discovery has traditionally relied on time-consuming and labor-intensive experimental methods. However, AI is revolutionizing this process by augmenting human capabilities and accelerating the discovery of new chemicals. By leveraging AI algorithms and machine learning techniques, scientists can analyze vast chemical datasets, simulate molecular structures, and predict properties with remarkable accuracy. Enhancing Efficiency with Machine Learning Machine learning algorithms play a pivotal role in the advancement of chemical discovery. They can be trained to recognize patterns in large chemical databases, identify relationships between molecular structures and properties, and generate predictive models. These models enable researchers to streamline the identification of promising candidates for drug development, materials science, and other chemical applications. Predicting Molecular Properties One of the significant advantages of AI in chemical discovery is its ability to predict molecular properties. By analyzing the structures and compositions of various compounds, AI algorithms can estimate properties such as toxicity, solubility, stability, and biological activity. This predictive capability enables scientists to prioritize and focus their efforts on the most promising chemical candidates, saving both time and resources. AI Techniques in Chemical Discovery AI encompasses various techniques that have been instrumental in advancing chemical discovery. Let’s explore some of these techniques and their applications: 1. Machine Learning Algorithms Machine learning algorithms, such as support vector machines (SVM), random forests, and neural networks, have found extensive use in chemical discovery. These algorithms can analyze large datasets, learn from patterns, and make predictions about the properties and behavior of chemical compounds. 2. Generative Models Generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), have the potential to revolutionize chemical discovery. These models can generate novel molecular structures with desired properties, helping scientists explore new chemical space and uncover previously unknown compounds. 3. Natural Language Processing (NLP) NLP techniques have proven valuable in extracting and analyzing chemical information from scientific literature and patents. By using NLP, researchers can gather vast amounts of knowledge, identify trends, and gain insights that can inform their chemical discovery efforts. 4. High-Throughput Screening High-throughput screening involves the automated testing of thousands or even millions of chemical compounds to identify those with desired properties. AI-driven automation and robotics enable scientists to perform these experiments efficiently, accelerating the discovery of new chemicals. 5. Quantum Chemistry Simulations Quantum chemistry simulations, combined with AI techniques, enable scientists to model and predict the behavior of chemical compounds at the atomic and molecular levels. These simulations provide valuable insights into the properties and interactions of compounds, aiding in the discovery of new chemicals with tailored characteristics. Benefits of AI in Chemical Discovery The integration of AI into chemical discovery processes offers several notable benefits: 1. Accelerated Discovery Timelines By leveraging AI’s processing power and predictive capabilities, researchers can significantly shorten the time required to discover new chemicals. AI algorithms can quickly analyze vast amounts of data, identify potential candidates, and guide experimental efforts, leading to faster discoveries. 2. Cost Savings AI-driven chemical discovery can help reduce costs associated with experimental testing. By using predictive models and simulations, scientists can prioritize their experiments, focusing on compounds with a higher likelihood of success. This targeted approach minimizes resources wasted on less promising candidates, resulting in cost savings
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Lanya Chemical Co.Ltd.Granted Silver medal As the…
We are proud to announce , Nanjing Lanya Chemical Co., Ltd., has been awarded the silver medal by EcoVadis for our sustainability work. We’re placed among the top 25% of companies assessed by EcoVadis. That is a big achievement for us and motivates us very much for the year 2023!
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Welcome Coating Show 2023
HELLO ECS 2023! Join us at Booth 462 in Hall 1 and let’s discuss solutions for adhesives & coatings tomorrow. We can’t wait to see you!
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PLASTINDIA 2023
LANYA CHEMICAL has a deep understanding of the plastic industry and is able to provide tailored solutions to meet the specific needs of its customers. Meet us in PlastIndia 2023 at HALL 5-FF, C-47!
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LYC-DF8210
Specifications: Package: 200Kg Drum or 1000Kg IBC. Application: Defoamer DF 8210 can be added the undiluted liquid directly or added after dilution. This product should be added in mixing-good location (e.g. fan pump, White water machine, white tank etc.). The dosage will change with the foam situation and typeof process fluids, usually 300~1000ppm. The performance can be the best if by adding continuously. Storage: Unopened it should be stored inCool and dry place. Recommend Shelf Life: 6 months.
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LYC-S660
Specifications: Package: 200Kg Drum or 1000Kg IBC . Application: Its common addition point is within the surface sizing system, at the inlet of thestarch transfer pump or directly added to the used gluing bin. The typical dosage is2~5% (dry starch), which is roughly equivalent to 0.5~2.0kg/ton paper ton. Basically,it needs aluminum sulfate to help with sizing. It should be noted that it cannot bedirectly added to the application of OBA, which can prevent the failure of OBA.For different paper machines, the dosage of surface sizing agent should be optimized inorder to obtain the best sizing effect. Storage: It is suitable for low temperatures as much as possible, but care must be taken toavoid freezing the product. Recommend Shelf Life: 6 months.
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PC-SA456
Specifications: Package: 25, 750, 800KG moisture-resistant bags. Application: Used in paper industry, one is to improve the retention rate of filling material, color paste, etc. To reduce the outflow of raw materials and environmental pollution tothe natural environment; Two is to improve the printing paper compressive strength(including dry compressive strength and wet compressive strength). Storage: stored in unopened package in a dry atmosphere at temperature no higher than40℃. Recommend Shelf Life: 24 months.
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