Greetings to you from the GM of Showa Denko Singapore. We have been doing marketing activities in the SEA region for a few years. Leading to our strong connection with these industries
- Research Institutes
Recently, there have been many changes in the world, resulting in supply shortages. For example, stronger environmental regulation in China, Spike of freight cost and so on.
“We do not have enough xx material for production!” “We can’t accept the shortage! Please do something!” “Can SSPL help sourcing this xx for us!?”
These are conversations that we always hear from customers recently.
Despite being a distributor, SSPL used to focus on Showa Denko Group products only. However, there is the most important value that we have found to have a better response to our customers. “Customer Value” is the most value that we are contributing in recently and from now on. Currently, we always start from what we can do and what value we can provide for customers.
About our sourcing
We have experience from Marketing and Sales with a lot of direct conversation with the purchasing team of customers.
“Only SDK group is quite limited” “High quality products, but sometimes it is just over the requirement” “No supply during maintenance period is too tough” “Do you have local-based stock? we want the material quickly”
Here are what the purchasing team concerns and we do hear you.
The customer wants us to supply other products than Showa Denko group’s products too. We also highly appreciated it as this means the customers have trust in us and our performance. And, it is also showing that only current service is definitely not enough, we need to provide more customer-oriented service and value.
And, this is why we started being an overall sourcing center for you. Our sourcing activities:
- Research supplier’s information in ASEAN
- Summarize price, specifications and quality from market survey
- Provide product sample for your first evaluation
These activities made the purchasing team become more convenient and efficient!
Here are some of our successful sourcing for customers.
- Raw materials for Ceramics from Myanmar, from supplier survey to sample evaluation
- Aluminium Trihydroxide (ATH) from Indonesia, offer with best price negotiation!
- Amino Acid from China
- Zeolite from Turkey
From supplier survey, sample evaluation to negotiation for best price!
There are uniqueness on our activities as being Showa Denko Group
・From cross-region connections with our global brancher, to local connections in the region
We do provide you all-around data, so you could have consideration without a miss.
・High Experience of our sales/marketing across a wide range of products.
It leads to the most wided know-how we could provide you to maximize the business.
・Local staff for your own language.
Accessing local customers and suppliers thoroughly, our staff speaking your language. Japanese, English, Bahasa Malaysia, Bahasa Indonesia, Thai, Vietnamese are available.
With all these providing, the Purchasing department will find doing business with us at ease. And, without a miss on the requirement/data trends
We are aiming to be “Sourcing Center for you”, providing a solution for your sourcing issue including other supporting activities for your convenience. Consulting is free, moreover free samples are also available.
Please do not hesitate to let us know your request.
Showa Denko K.K. (SDK) (TOKYO: 4004) has developed hard disk (HD) media for hard disk drives (HDDs) which support data recording with Microwave Assisted Switching-Microwave Assisted Magnetic Recording (MAS-MAMR) technology, which is a next-generation data-recording technology based on a new data recording principle suggested by Toshiba Corporate Research & Development Center and Toshiba Electronic Devices & Storage Corporation (Hereinafter collectively called Toshiba).
MAS-MAMR is a next generation data recording method that can realize further increase in data-storage capacity of HDDs. At present, Microwave Assisted Magnetic Recording (MAMR) is a leading edge data-recording technology, which has already been put into practical use. The newly developed MAS-MAMR technology realizes data-recording track on the surface of HD media drastically narrower than that of MAMR-technology-based HD media through utilization of the strong magnetic oscillation effect of Microwave Assisted Switching (MAS effect)*1, thereby increasing data-storage capacity of HDDs.
Aiming to put this new data-recording technology into practical use, SDK has been developing HD media supporting MAS-MAMR in collaboration with Toshiba and TDK Corporation (TDK) which is a manufacturer of read/write heads for HDDs. In this joint development program, SDK, Toshiba, and TDK have cooperatively proved for the first time in the world that HDD as a combination of read/write head equipped with dual spin-injection-layer, which has been developed by TDK, and HD media equipped with new-type magnetic layer, which has been developed by SDK, can substantially increase HDD’s data-storage capacity through manifestations of the MAS effect.
In this year, SDK has already started supplying Toshiba Electronic Devices & Storage Corporation with HD media supporting MAMR. These media are mainly installed in 18TB HDDs for near-line use in data centers. On the basis of the fruit of the technology development program mentioned above, and aiming to realize large-capacity near-line HDDs with storage capacity of more than 30TB, SDK will accelerate development of HD media supporting MAS-MAMR which Toshiba aims to put to practical use as the second generation MAMR.
The amount of data generated and communicated has been increasing rapidly due to progress in Digital Transformation (DX) including the spread of teleworking, 5th generation (5G) mobile communication services, and Internet of Things (IoT). As a result, it has become a more important task for HDD manufacturers to develop large-capacity near-line HDDs for use in data centers, which record and store a large amount of data. In order to respond to the demand for the increase in storage capacities of HDDs, SDK will accelerate two-way development of HD media supporting MAS-MAMR and HAMR (heat assisted magnetic recording) in accordance with its motto of “Best in Class,” thereby developing the best HD media in the world.
*1: MAS effect: MAS effect is an abbreviation of Microwave Assisted Switching effect. MAS effect is an effect of strong magnetic oscillation between Spin Torque Oscillator (STO) and magnetic recording media. This strong magnetic oscillation enables HDD manufacturer to record digital data on the surface of HD media with recording track narrower than those of HDDs equipped with conventional magnetic recording technologies.
This news originally published on www.sdk.co.jp
NEW! Technical Article No. 15
Purification and SEC/MS Analysis of Norovirus Virus-Like Particles
In the fields of new modality, such as gene therapy drugs, virus vector, new vaccine, and drug delivery etc., applied researches on “bionanoparticles” are rapidly expanding and receiving the greatest interest these days. Due to their complex structures and distinct sizes, production and quality evaluation of their biological processes require integrated and multifaceted analytical techniques, even more than that of conventional biopharmaceutical compounds.
Virus-like particles (VLPs) are typical bionanoparticles. Since they are not infectious nor proliferated, but they can reproduce their original sizes and forms, they effectively elicit immune responses when used for vaccine. R&D for its commercialization is in progress as it would be an excellent platform.
This article presents the effectiveness of Size Exclusion Chromatography (SEC) – Shodex SB-805 HQ – for the analysis of bionanoparticles. As a proof of concept, method development for a chromatographic purification of norovirus cell surface layer binding protein originated VLP (NVLP) is discussed. This article also includes the evaluation of an effective method development using an SEC column with different analytical devices and a summary of how to select a suitable column for the monitoring of purification procedures.
Click here to read the full PDF version.
Contact us today for your free, no-obligation technical consultation and demo offer.
Showa Denko K.K. (SDK) (TOKYO: 4004) has developed neural network models*1 to predict mechanical properties of 2000-series aluminum alloys*2 from their design conditions with high accuracy in collaboration with National Institute for Material Science (NIMS) and The University of Tokyo (UTokyo). The developed models enable us to accelerate the process to explore optimal compositions and heat-treatment conditions for aluminum alloys that can maintain strength at high temperatures and shorten development time for aluminum alloys to about half to one-third of that with conventional development method, which was not easy in the past.
Aluminum has various applications because it is lighter than iron and easy to work. However, it is usually used as an aluminum alloy containing copper, magnesium and other additive elements because pure aluminum has low strength. The development of aluminum alloys that can maintain sufficient strength for a particular use at high temperatures is desired because conventional aluminum alloys lose strength when their temperature rises to 100℃ or higher. However, the mechanical properties of aluminum alloys depend on many process factors, including many kinds of additive elements and heat-treatment conditions. Developing high-performance aluminum alloys usually takes time because designing aluminum alloys requires developers’ knowledge-rich experience and repetition of analysis and evaluation.
Aiming to solve these problems, SDK has been taking part in a project under Council for Science, Technology and Innovation (CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), “Materials Integration” for Revolutionary Design System of Structural Materials. In this Development, SDK, NIMS, and UTokyo have collaboratively developed a computer system using neural networks, an artificial intelligence (AI) algorithm, to accelerate the development of materials and explore globally for aluminum-alloy designing conditions that realize optimal mechanical properties.
In this development, we focused on 2000-series aluminum alloys, utilized design data of 410 records of aluminum alloys listed in public databases, including the Japan Aluminum Association, and developed neural network models that accurately predict the strength of aluminum alloys at various temperatures ranging from room temperature to high temperature. In addition, we optimized the architecture and parameters of the neural network with Bayesian inference*3 by applying the replica-exchange Monte Carlo Method*4. As a result, it became possible for us to evaluate aluminum alloy strength and its prediction uncertainty. Moreover, this neural network model can estimate the strengths of aluminum alloys under 10,000 different conditions within 2 seconds. Thus it became possible to evaluate aluminum alloys with various design factors comprehensively in a short time.
Furthermore, we successfully developed “an inverse design tool,” which suggests a set of aluminum-alloy design conditions that maximizes the probability of satisfying the desired strength at arbitrary temperature. Thus it enables us to design high-strength aluminum alloys at high temperatures above 200℃.
In its “Long-term Vision for Newly Integrated Company,” the Showa Denko Group has announced that it will continue committing itself to make the most of artificial intelligence and computational science, which is the core of its fundamental research activities. We will accelerate our material development programs by applying the results of this Development to our activities to develop various new materials, and provide our customers with solutions for their problems, thereby contributing to the prosperity of society.
Detail of the results of this Development will be presented at the virtual session of the 2021 Materials Research Society*5 Fall Meeting, which will be held from December 6 to 8 in the United States and broadcasted to the world via the Internet.
*1. Neural network model: Neural network model is a machine learning algorithm that imitates the human brain’s neural network. A typical neural network model has input, hidden, and output layers. The existence of a hidden layer enables a neural network model to learn and estimate relationships between the input and output of complicated events. Statistical machine learning with neural network models with many hidden layers is called “deep learning.”
*2. 2000-series aluminum alloys: 2000-series aluminum alloys contain copper and magnesium as additive elements, and have high mechanical strength. Duralumin and super duralumin are well-known 2000-series aluminum alloys. 2000-series aluminum alloys are used as materials for the bodies of aircrafts and industrial parts (screws, gears and rivets, etc.).
*3. Bayesian inference: Bayesian inference is a method of statistical inference that statistically infers causes from observed facts based on Bayes’ theorem. In this Development, we constructed neural network models that reproduce correlation between design conditions and mechanical properties of aluminum alloys with Bayesian inference.
*4. replica-exchange Monte Carlo Method: Replica-exchange Monte Carlo Method is one of the computational methods to simulate Bayesian inference with a computer. It is known to converge to a global minimum solution faster than other methods when solving multimodal problems with many local minimum solutions. This enables us to explore a wide range of parameter space efficiently to find the optimal solution.
*5. Materials Research Society: Materials Research Society is an academic society focusing on material science, established in the United Stated in 1973. It convenes general meetings twice a year, in spring and fall.
This news originally published on www.sdk.co.jp