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New Materials Development Consulting
Molecular modeling and artificial intelligence will give you the direction of successful new material development!
Work Process
The professional researchers in INSILICO will help the customers develop new materials in accordance with a step-by-step process.
With the molecular modeling and artificial intelligence, INSILICO’s exclusive research technologies, the prediction accuracy would be improved and the number of compounds that need to be tested would be practically reduced, so more efficient research and development could be supported.
Optimization modeling for crude oil additive
Client
SK Innovation
Summary
After selecting the molecular structure of major components of crude oil, the modeling of these mixtures, structural simulation getting to be changed when adding additives and solvent differences were analyzed.
Expected effect
Accurate investigation of the causes of the increase in solvent performance applied to the new process could provide essential information for future extraction-solvent development
Project period
2014
Analysis of optimal surface substitution structure for NCA development
Client
Samsung SDI
Summary
The energy of the surface structure of Ni-rich NCA active materials was calculated through the molecular modeling using computational simulation and the structural stability tendency appeared according to the presence of metal ions, such as Co, Al, etc., was examined.
Expected effect
By finding ECA parameter and cluster structures that can model LCA by using cluster expansion method, the results of Monte Carlo simulation will be analyzed, and LCA structure will be understood, which could be utilized to manufacture LCA of a new composition.
Project period
2013
Evaluation of metal composition effect of cathode material for Lithium Secondary Battery
Client
Samsung SDI
Summary
By using quantum computation, the change of OCV (open circuit voltage) was calculated for various metal oxides used as a cathode material of lithium ion battery; the modeling technique that could be reproduced by comparing with previous experimental values and calculated values was derived; based on these results, for other metal ion materials, and the reliable result was drawn and the confidence level was extended to the binary system; and why the ternary system structure has superior characteristics was interpreted based on several calculations.
Expected effect
A reliable protocol for predicting the capacity of OCV and Li ion for cathode materials of lithium ion batteries was established; a systematic research technique was established to explain the degree to which the objective characteristics change according to the composition and composition change; and the basic directions to develop excellent cathode materials with high efficiency and low cost was presented.
Project period
2005~2006
The machine learning method was developed for the classification / search / characteristic interpretation of compound
Client
SK Biopharmaceuticals
Summary
Utilizing the “Bayesian modeling” method among the classification learning methods, we constructed a model that could predict the “Activity” of the targets desired by the users; classified by each target the commercial libraries that could be purchased, based on this; and realized the user interface in the web environment so that experiment researcher might easily use the constructed target activity prediction model.
Expected effect
Since it is known that more than 3 trillion compounds are available globally and the utilization of artificial intelligence is more important in order to efficiently search for compounds capable of exhibiting the pharmacological activity in a specific target in a large amount of compound data, it is easily accessible in experimental research fields, such as establishing the logical model conditions for the pharmacological activity, selecting compounds that meet the conditions, etc.
Project period
2005
Prediction of tertiary structure of biopolymers and analysis of inhibitor binding
Client
SK Biopharmaceuticals
Summary
Based on the comparative genomics, we extracted the proteins whose structures were experimentally known well and which have the similar sequence structure with the sequence of the GPCR protein (dopamine receptor and melanin-enriched hormone receptor) whose structure was to be predicted, and based on this, 3 dimensional structure model was selected by using Homology method, molecular dynamics method, etc.
Expected effect
As GPCR is known as a protein involved in the signaling of cells in various diseases, the establishment of the 3-dimensional structure of protein can allow us to grasp the mechanism of the relevant disease at the molecular level and provide the crucial information for the development of agonists and antagonists required for the treatment of diseases.
Project period
2005
Surfactant design for dispersion of nanoparticles for MLCC
Client
Samsung Advanced Institute of Technology
Summary
By establishing systematic research techniques, we analyzed the structural characteristics of surfactants that maximize the dispersibility of Ni particles and enhance solvent affinity, at the molecular level; suggested the theoretical explanations, such as the changes in the dispersing ability of Ni particles according to various chemical groups constituting the hydrophilic group of the surfactant by using the molecular dynamics calculations, the structural changes of Terpineol-based solvents, the effect of the interaction with surfactant on the dispersion capacity depending on oxidation state of Ni particle surface, etc.; established the mechanism.
Expected effect
By analyzing the physicochemical properties of single molecules or molecular assemblies and predicting the properties of new compounds, the systematic and logical studies, high efficiency and low-cost researches, shortening of the payback period and so on are expected. We logically compared the compounds with the excellent properties with ones without them at the molecular level; grasped the limiting factors that may limit the purpose characteristics; and suggested the development of direction for new materials, based on these above.
Project period
2004
Analysis of mechanical properties based on the precursors of low-dielectric semiconductor materials
Client
Samsung Advanced Institute of Technology
Summary
In accordance with the full-scale use of copper for the semiconductor wiring materials, because it is not possible to achieve the goal of high density integration/high speed by replacing only aluminum, which is a wiring material, with copper in the copper wiring process so the usage of low dielectric materials must be simultaneously executed, the various required material properties of Low-k dielectric materials for semiconductors were predicted, whose mechanical properties were analyzed.
Expected effect
By early development of the low-dielectric materials required for manufacturing Cu Chip of a new concept, we will actively cope with the new changes in the semiconductor market; since the reduction of the RC signal delay which is expressed into the multiplication of the resistance value of wiring materials and the capacitance of insulator film is the essential matter for the high-speed operation of devices and the mutual cross-talk could be prevented thereby, the high integration / miniaturization thanks to the increased circuit density would be enabled, which may ultimately bring the achievement of the dramatic improvement in the cost reduction and chip performance.
Project period
2004
Photosensitive polymer design of Paste for field effect display
Client
Samsung SDI
Summary
The photosensitive resin polymer, whose mechanical properties was excellent and whose thermal decomposition was high, was developed during the short period of time for developing a photosensitive resin polymer suitable for CNT paste for FED and systemic research method by utilizing the molecular modeling technique and mixture experiment design method.
Expected effect
In addition to the development of high-resolution photosensitive resin polymers suitable for CNT paste and their creation, the FED team has proposed the development directions for the materials and their creating selection which are used as basic data for future research.
Project period
2004
Functional design for improving the dispersibility of carbon nanotubes
Client
Samsung SDI
Summary
The physicochemical properties of carbon nanotube paste at the molecular level were analyzed by using molecular design techniques, and based on this, the research directions of resin polymers for carbon nanotube paste are presented; the resin polymers with excellent properties that could be adopted in the machine, from the polymers which had been commercialized and being sold, were selected, and the effect of the pre-processing of carbon nanotubes on the mixing uniformity of carbon nanotube paste was grasped.
Expected effect
Through the establishment of guidelines for the construction of the polymer database, which had been melted and was sold, and the selection of polymer resins for the paste, they would be utilized for the future R&D, through which the basic data to be used for the process changes including carbon nanotube pre-processing is presented.
Project period
2003
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