Volume 37(2) - Summer 2021

Lithium-ion batteries are secondary (rechargeable) batteries that are used for a wide range of applications, from mobile devices to electric vehicles, as they combine both high energy density and excellent power characteristics. In recent years, research has been conducted toward the realization of an all-solid-state lithium battery, in which the organic electrolyte is replaced with a solid lithium conductor. In many existing battery systems, including lithium-ion batteries, the electrolyte in which the supporting salt is dissolved is responsible for transporting carrier ions between the electrodes; in all-solid-state batteries, ion transport is performed by a solid electrolyte. At the same time, electrons flow through the external circuit, delivering power to the devices. The use of a solid electrolyte is believed to eliminate problems such as liquid leakage and electrical shorts, as well as explosions that can occur when an organic electrolyte is used, thus improving safety and reliability.

Discovering and producing an effective solid electrolyte is a significant challenge in developing solid-state lithium batteries. This means that a pure ionic conductor is required, in which only lithium ions diffuse at high speed, without electron conduction taking place. Various material systems, such as glass, glass ceramics, crystals, and polymers, have been developed as solid electrolytes. Thus far, sulfide-based materials are the only materials that exhibit ionic conductivity characteristics comparable to existing liquid electrolytes (≧10⁻² S cm⁻¹).

Many researchers have been developing and analyzing potential electrode materials and solid electrolytes, with a particular focus on crystalline materials. All-solid- state lithium batteries would give rise to the possibility of all battery components being made from crystalline materials; therefore, the importance of phase identification and crystal structure analyses by X-ray diffraction (XRD) measurements will increase.

In this technical note, we will introduce XRD measurements and explore how the data can be used in the search for materials related to all-solid-state batteries, along with examples of our own research.

Standardless FP X-ray fluorescence analysis is a quantification method using theoretical calculations including fundamental parameters. The analysis method has been widely used in the electronics and petrochemical industries, among others, since it can simply and quickly quantify sample compositions from spectral peak intensities without preparing calibration curves. In this report, the standardless FP analysis method was tested for metallic oxide compounds using cement and geological reference materials. The analysis results for Ni-based and Ni, Co, Mn-based cathode materials and SiO anode materials are shown.

Rapid Analysis of Carbon in Steel and High Performance Analysis of Stainless and High Temperature Alloys

The Rigaku KT-500 hand-held analyzer represents the next advancement in handheld laser induced breakdown spectroscopy (LIBS).

Building on the capability of the KT-100 Series analyzer, the KT-500 adds High Resolution Echelle Spectrometer (HiRES) technology for rapid analysis of carbon in steels along with high performance of stainless and high temperature alloys such as nickel and cobalt bases alloys.

The KT-500 is being offered for QA/QC applications and positive material identification (PMI) within petrochemical and power generation for customers who need carbon analysis of their steels along with stainless steel and high temperature alloys. These industries have found that relying on material test reports (MTR) alone is not enough when fabricating key components for these mission critical applications.

Differential scanning calorimetry (DSC) is a thermal analysis technique that measures the change in heat capacity of a sample, or endothermic/exothermic reactions, based on the difference in temperature between a sample and a reference material that are both heated/ cooled at a predetermined constant rate. This technique is widely used to study the thermal information of materials such as glass transition temperature, reaction temperature (e.g. crystallization, melting), and reaction energy. In contrast to conventional DSC, there is a thermal analysis technique called “temperature-modulated DSC,” which performs measurements with the addition of temperature-modulating components, such as sine wave and steps, to the constant-rate heating/cooling process. After the release of ISO (ISO-19935-2) “Plastics-Temperature-modulated DSC” in 2020, this measurement method will likely become widespread. Therefore, Rigaku has developed a control algorithm and the Dynamic DSC Analysis software that uses sine waves as a temperature modulating component.

One of the major technical challenges of this decade are energy efficient technologies, which is among others, comparable in its importance to Artificial Intelligence, 5G and IoT. Innovative silicon carbide (SiC) technology and components will contribute significantly towards the goal of a greener, energy efficient and sustainable economy. SiC also addresses major and dynamic growth markets such as renewable energy generation and conversion, edge computing, cloud computing and data centers and last but not least the imminent change to and corresponding growth of electric mobility solutions. SiC is therefore one of the most important semiconducting material in this decade.

Due to the current undersupply of SiC substrates, the obtained prices for typical 150 mm n-type SiC wafers are quite high and in the range of $800–$1200 per wafer, depending on the material quality and the purchased quantity. Beside wafer prices, the material quality is a very important factor to choose the right material supplier. A stable baseline, instead of handpicking small numbers of best case wafers, for supplying high quality SiC substrates is needed to manufacture reliable SiC power devices, which is especially requested for automotive application. Therefore, a strong need for non-destructive and reliable SiC substrate characterization occurs, which supports R&D purposes, e.g. defect optimization or scale up to 200 mm substrate diameter, and of course in-line capability in terms of quality assurance within production environment.

Total Reflection X-ray Fluorescence (TXRF) analysis is a non-destructive and surface-sensitive analysis method using X-rays, in which incident X-rays are irradiated on a sample at an extremely low grazing angle (about 0.1°) and the fluorescent X-rays from the sample generated by the incident X-rays are measured with extremely low background because of the total reflection characteristics of the incident X-rays. TXRF analysis does not require special sample preparation for flat samples. Because of this, TXRF analysis has been widely used for the evaluation of contamination on wafers in semiconductor manufacturing processes(3) as well as in industrial and environmental analysis. Contamination control in semiconductor manufacturing processes becomes more rigorous every year.

Recently, Artificial Intelligence (AI) technologies have developed rapidly along with progress in computer hardware, software and software libraries to deal with big data. One main benefit of AI is that it automatically extracts and analyzes unique and notable characteristics from a huge amount of data. In the field of image processing, particularly, image recognition—for example, handwritten character recognition—has been actively researched and many results—such as super-resolution techniques that convert low-resolution images to high-resolution ones—have been achieved. Although there are many cases where AI is used for image processing, it seems that there are few cases where AI technologies are applied to one-dimensional spectrum analysis instead of to a two-dimensional image. Therefore, in this paper, we applied the machine learning method to the data processing of TXRF analysis and introduce the results, especially on the quantification of contaminations on wafers from the spectrum obtained by short-time measurements.

In the second installment of the powder X-ray diffraction (PXRD) basic course, how to select instrument configurations to obtain high-quality data was described. This third installment provides information on how to prepare samples and determine the best measurement conditions to obtain high-quality data. Regarding sample preparations, the type of sample holders, the effect of grain size of the sample, and the impact of the eccentricity and asperity of the sample surface must be taken into consideration.

In most PXRD measurements, a glass sample holder is usually filled with sample. However, other appropriate sample holders should sometimes be selected based on the chemical properties, composition, and shape of the sample, which will allow you to obtain high-quality data with high resolution and low background. Also, the impact of preferred orientation can sometimes be suppressed. Appropriate optics should also be used for the selected sample holder. The following chapters and sections will describe the details of sample preparation and measurement conditions, along with a few tricks and traps.

Weight saving is an important challenge for various industries, including transportation (automotive, aeronautical, or bullet-train manufacturing), electronic devices, and intelligent robotics. Finding lighter-weight materials is, therefore, a popular research subject because of its potential impact on peoples’ daily life. This is especially true in the modern automotive industry, where better fuel economy and reduction of CO₂ emissions are now even more important requirements in technology development as the global number of cars owned is expected to keep growing.

A significant trend when making parts is to replace steel with a light metal or a high-strength resin. Magnesium is regarded as a prospective next-generation high-performance material. In fact, the Nonferrous Metals Division of the Japan Ministry of Economy, Trade and Industry has published a report titled “Nonferrous Metal Industrial Strategy 2016”, which proposes a marketing plan for these light metals, including magnesium.

This article demonstrates examples of multifaceted non-destructive analyses on raw and surface-treated AZ31B, a representative magnesium alloy, using laboratory X-ray analyzers, which are useful nondestructive analysis tools.

Recognizing the potential of MicroED, Rigaku and JEOL announced a collaboration in 2020 to develop a new product designed in a fashion that will make it easy for any crystallographer to use. The resulting product is the XtaLAB Synergy-ED, Figure 1, a new and fully integrated electron diffractometer, that creates a seamless workflow from data collection to structure determination of three-dimensional molecular structures. The XtaLAB Synergy-ED combines core technologies from the two companies: Rigaku’s high-speed, highsensitivity detector (HyPix-ED), and instrument control and single crystal analysis software platform (CrysAlis^Pro ED), and JEOL’s expertise in generation and control of stable electron beams. There are many materials that only form nanosized crystals. Before the development of the MicroED technique, synthetic chemists were forced to rely on other techniques, such as NMR, to postulate 3D structure. Unfortunately, for complicated molecules such as natural products, the NMR results can be difficult to interpret. MicroED has thus become a revolutionary technique for the advancement of structural science.