Hello, everyone. Welcome to today's live broadcast, Elemental Analysis of Sodium-Ion Battery Cathode Precursor Chemicals, PB, SMO, and SFP. I'm Shannon Stolz, Senior Editor of Special Projects for Spectroscopy, and I'll be your moderator for today's event. We are pleased to bring you this webcast presented by Spectroscopy and sponsored by Agilent Technologies. Agilent Technologies is a global leader in the life sciences, diagnostics, and applied chemical markets, delivering insights and innovation that help its customers bring great science to life. Agilent's full range of solutions includes instruments, software, services, and expertise that provide trusted answers to its customers' most challenging questions. We do have a few important announcements before we begin today. First, that this webcast is designed to be interactive, so we encourage you to ask questions throughout the event.
You can submit your questions by typing them in the Q&A box, and that can be found at the bottom of the video player. You can enlarge the slide window by clicking on the small icon in the bottom right corner of the media player, and the slides will be advancing automatically during the event. If you have any technical problems viewing or hearing this presentation, please click on the question mark Help widget in the top right of your presentation window. I would now like to introduce today's speaker. We are very pleased to be joined today by Dr. Daniel Clayton-Couch. Dr. Clayton-Couch graduated with a Bachelor of Science in Biochemistry from the University of Adelaide in 2018, with first-class honors. He started his industry PhD in early 2020, titled Identification, Characterization, and Exploitation of Bioactive Compounds from Plant Biomass.
The project heavily focused on manipulating and improving the biosynthesis of polyphenols, which have a wide variety of structures. The project collaborated with two industry partners, CSIRO and Agilent Technologies, involving analytical chemistry techniques such as Triple Quad LC/MS and LC/MS Q-TOF. While waiting to finalize his thesis, he was undertaking an industry placement at Agilent Technologies in the Atomic Spectroscopy Division. This was a part of his industry PhD program, working as an application scientist. So thank you so much for joining us today, and please get us started.
Thank you very much for the introduction. Hello, everyone, and thank you for joining me today. In this presentation, I want to share with you some of the work we've been doing on the elemental analysis of sodium-ion battery cathode materials by inductively coupled optical emission spectroscopy, otherwise known as ICP-OES, for the determination of contaminating elements. My name is Daniel Clayton-Couch, and I'm an application chemist here at Agilent Technologies in Melbourne, Australia. The aim for today is to provide an overview about how the Agilent ICP-OES instruments can be used to create safe and simplified methods that overcome the challenges presented by battery cathode materials during analysis. Okay, so here's an outline for today's presentation.
We'll begin with an overview of the rechargeable battery industry, looking at the current key player, lithium-ion batteries, and then move on to the emerging technology and main focus of today's presentation, sodium-ion batteries. Afterwards, we'll go into a brief outline of sodium-ion battery cathode materials and how that's led to the current attraction by industry in advancing this particular technology. Specifically, we'll be looking at a real-world example of the analysis and quantification of 30 elements in three different sodium-based cathode materials. I'll be touching on all phases of the method development for analyzing these challenging materials, as well as some of the difficulties that were encountered during the process, and conclude all of this by outlining which problems were addressed.
Finally, I'll go through some questions that you've asked me throughout this presentation, so make sure if you have any or think of any during the presentation, that you send them through. Okay, so let's begin with what the rechargeable battery supply chain looks like. The supply chain is just simply describing the entire process through which a product is made and delivered to a consumer. In our case, the steps involved in producing and using rechargeable batteries falls into four general categories. Firstly, we have the upstream, which is where mines extract raw materials for batteries. These raw materials typically contain elements such as lithium, cobalt, manganese, and nickel. Although many of these elements come from ore, a large percentage of them are also extracted underground from brines, as well as seawater.
We have the midstream, which is where processors and refiners purify the raw materials and use them to create cathode and anode active battery materials. Commodities traders also buy and sell raw materials to firms that produce the battery cells. Then we have the downstream, which is where battery manufacturers assemble the battery cells into modules, as well as packing and selling them to automakers, for example, who will place the finished batteries in electric vehicles. Some automakers have formed partnerships with battery manufacturers to produce their own batteries, for the vehicles that they sell. Finally, we have the end of life of the batteries. When they are no longer serving their original purpose, they can be reused or recycled. In the growing battery recycling industry, batteries are dismantled, shredded, and processed into a black mass powder.
This powder is then refined into commodity-grade graphite, cobalt hydroxide, and lithium carbonate for reuse. Recyclers need to test the purity of these recovered materials, as well as meet regulations on discharges and leaching into the environment to control the environment, and protect their workers. So at every stage of the value chain, I've outlined here, there is a requirement to understand which elements are actually present and in which concentrations they are present. So manufacturers need to monitor impurities in raw materials and ensure the quality of their final products through quality control testing. They also must control emissions from their factories into the environment and meet regulated limits on hazardous substances, such as heavy metals, to protect their workers. In this slide, I want to provide an overview of the key player in the rechargeable battery industry, the lithium-ion battery.
A significant proportion of the technology developed around lithium-ion batteries can be directly applied to the development of sodium-ion batteries, which is why these two industries will actually continue to grow together. For a brief history, the lithium-ion battery originated in the 1970s, when chemist M. Stanley Whittingham proposed using lithium cells. Early versions of this technology used expensive and toxic titanium sulfide metals. In the late 1970s and 1980s, scientists like John Goodenough and Ned A. Godshall developed lithium cobalt dioxide, which laid the foundation for the lithium-ion battery. In 1985, Akira Yoshino created a prototype with lithium ions and lithium cobalt dioxide, and by 1991, Japanese companies began mass producing these batteries for electronics. In 2019, Whittingham, Yoshino, and Goodenough received the Nobel Prize for their contributions to the lithium-ion battery industry.
So if we look a little closer at the lithium-ion battery industry, we can see battery demand for vehicles grew over 70%, while electric car sales increased by 80% in 2022 relative to 2021. In 2022, lithium demand exceeded supply, as in 2021, despite the 180% increase in production since 2017. In 2022, about 60% of lithium, 30% of cobalt, and 10% of nickel demand was for electric vehicle batteries. Just 5 years earlier, in 2017, these shares were around 15%, 10%, and 2% respectively, which gives you an idea of how much this industry is growing.
As has already been seen for lithium, mining and processing of these critical minerals will need to increase rapidly to support the energy transition, not only for EVs, but more broadly, to keep up with the pace of demand for clean energy technologies. In 2022, Lithium Nickel Manganese Cobalt Oxide remained the dominant battery chemistry, with a market share of 60%, followed by Lithium Iron Phosphate, with a share of just under 30%, and Nickel Cobalt Aluminum Oxide, with a share of about 8%. However, Lithium Iron Phosphate cathode chemistries have reached their highest share in the past decade. Tesla accounted for 15%, and the share of LFP batteries used by Tesla increased from 20% in 2021 to 30% in 2022.
LFP batteries contrast with other chemistries in their use of iron and phosphorus, rather than the use of nickel, manganese, and cobalt. But the downside of LFP batteries is that the energy density is lower than that of nickel manganese cobalt oxide. So despite their wide use and energy efficiency, lithium-ion batteries do come with notable safety concerns that must be carefully managed. The presence of flammable electrolytes within lithium-ion batteries makes them prone to pressurization and even explosions if subjected to structural damage. Because of this, and because of its widespread use in most commercial products, the safety standards and safety testing of lithium-ion batteries is much more stringent than other types of batteries.
For example, the RoHS, Restriction of Hazardous Substances, and WEEE, Waste Electrical and Electronic Equipment directives, have put in place regulations that requires lithium-ion battery manufacturers to comply with, which regulate the use of hazardous substances. Among them are chromium, mercury, and cadmium. The WEEE directive also requires that manufacturers label their batteries with information on how to dispose of them properly. So although lithium-ion batteries use base metals such as iron, nickel, copper, and cobalt, their production and method of disposal can still pose a substantial hazard to the environment. While the metallic, metallic components of lithium-ion batteries are recyclable and even safe for both incineration and in landfills, repurposing them for reuse and reproduction in other products is a lengthy and expensive process, which in turn leads to manufacturers to forgo recycling and instead just mine new components.
The alternative technology to lithium-ion batteries currently is sodium-ion batteries. The foremost advantage of sodium-ion batteries comes from the natural abundance and lower cost of sodium compared with lithium. The abundance of sodium to lithium in the earth's crust is 23,600 ppm to 20 ppm, and the overall cost of extraction and purification of sodium is less than that of lithium. Moreover, sodium-containing metal oxide and polyanion cathode materials can be fabricated from naturally abundant transition metals such as iron, manganese, vanadium, and titanium without using cobalt, making sodium-ion batteries sustainable and affordable. Sodium-ion batteries are also safer because they are non-flammable and less susceptible to temperature fluctuations than lithium-ion batteries. The biggest downside is that sodium-ion batteries currently have a lower energy density than that of lithium-ion batteries.
This means that electric vehicles with a sodium battery that's the same size as a standard lithium-ion battery will not be able to travel as far on a single charge. And to make matters a bit more challenging, packing more voltage into the same space causes sodium-ion batteries to break down faster. Therefore, the more likely scenario is that lithium-ion batteries and sodium-ion batteries will not compete, not for the electric vehicle market share at least, but rather supplement each other. And sodium-ion batteries can help the automotive OEMs to alleviate the dawning lithium supply shortage. So substantial efforts of various researchers across the globe have resulted in distinct structured sodium-ion battery cathode materials. For instance, we have the layered transition metal oxides, the polyanionic compounds, Prussian blue, and its analogs.
The transition metal oxides, like iron and manganese, offer high theoretical capacity, but suffer from structural degradation and environmental instability. Strategies such as cation doping, surface coating, and structural design actually aim to improve their performance, though. Polyanionic compounds show promise due to stable structures and higher energy density, but their poor conductivity needs addressing. Conductive matrices enhance their electrochemical properties. Partially replacing elements in the host structure can also increase capacity. Prussian blue analogues provide good specific capacity, but face challenges due to vacancies and coordination water. Various strategies aim to stabilize their structure, reduce vacancies, and improve sodium transportation efficiency. Organic compounds exhibit stable redox characteristics, abundant reserves, and effective sodium transportation, but suffer from slow kinetics.
Overall, these cathode materials offer potential for sodium-ion batteries, and ongoing research is trying to address challenges and optimize their electrochemical performance for longer cycle life, higher voltage, and improved energy density. In the context of sodium-ion batteries, the choice of cathode material is crucial and is typically evaluated based on five parameters, as shown here in this figure. The scale-up viability is the ease of material synthesis and its environmental impact, which influence the potential for large-scale production. Solid-state techniques are preferred for polyanionic materials, while deleterious elements in other materials need to be substituted. The economic feasibility, so the cost of raw materials and post-treatment expenses affect the economic viability. The Prussian blue analogues are cost-efficient, while the layered transition metal oxides are less economical due to expensive elements, and the polyanionic materials fall somewhere in between those two.
The storage stability, so materials must remain stable in atmospheric conditions, with layered oxides being particularly vulnerable to moisture and carbon dioxide exposure. The energy density, so the specific capacity and redox potential determine electrochemical performance, with layered oxides offering high energy density, polyanionic materials having lower energy density, and Prussian blue analogues exhibiting lower capacity. Longevity, so polyanionic materials demonstrate the best cyclic stability, while the layered transition metal oxides have a shorter lifespan due to reversible phase transformations, and the Prussian blue analogues fall somewhere in between. So in the future, addressing challenges in sodium-ion battery cathode material technology, such as optimizing doping strategies, enhancing understanding of anionic redox processes, developing efficient complementary anodes, improving characterization techniques, are all essential for realizing the full potential of sodium-ion batteries.
As the sodium-ion battery industry is still in its infancy, there are no set regulations regarding the analysis of cathode materials, anode materials, or electrolytes as of yet. Although China has been working on some industry or group standards for the sodium-ion industry, so the T/QGCML 306-2022 is one such standard and requires the use of inductively coupled plasma. However, there are no details available on the method. Contaminating elements that were outlined in this method include calcium, magnesium, silicon, zinc, and cadmium, the presence of which cannot exceed 0.1% of the total sample weight under investigation. Although it is a great first step, there are many other elements that should be analyzed in the cathode, anode, and electrolytes of sodium-ion batteries, as they may present deleterious effects to the battery performance and contamination of the environment into which they ultimately end up in.
Such elements as arsenic and lead that are not listed in this industry standard, should be quantified prior to manufacturing, or especially prior to the recycling of sodium-ion batteries. Further, in the lithium industry, EU RoHS specified maximum levels for hazardous substances, has set the limit to 0.1% for elements, besides for cadmium, which is set to 0.01%. The lithium-ion battery manufacturers don't need to test for those elements, but must comply with the RoHS. Therefore, the objective of this work was to provide a foundational method for the analysis of 30 elements in a range of cathode materials in sodium-ion batteries, and sort of pave the way for the in-depth analysis of these materials. In this work, we provide a safe and simplified method for the analysis in an otherwise complex industry.
As mentioned in earlier slides, there are a range of different sodium-ion battery cathode materials, each with their advantages and drawbacks. Therefore, in this work, we selected three different cathode materials, each with drastically different matrices, to test both the digestion and analytical method's robustness for the sodium-ion battery industry. One Prussian blue, a layered oxide, and a polyanionic compound were selected for analysis, namely, Sodium Manganese Oxide, Sodium Iron Phosphate, and Prussian blue, as shown here below. There is a great deal of difficulty when dealing with three different cathode materials, as each have high concentrations of varying elements, such as sodium, iron, manganese, and phosphorus. In addition, the concentrations of contaminants vary significantly depending on the cathode material under investigation.
Therefore, to develop one digestion and one analytical method for three different cathode materials has been done in this work, but it does come with its challenges, and that's what we'll get into now. First, I want to talk about Prussian blue and its analogues, which are promising materials for sodium-ion battery cathodes because of their high working potentials, high theoretical capacity, and lower toxicity. Prussian White is the fully reduced and sodiated form of Prussian blue, which could significantly improve the manufacturability of commercial batteries as it circumvents the requirement of a reactive sodium-loaded anode in cell assembly. Prussian blue, a precursor of Prussian blue analogues, or otherwise known as Prussian White, is one of the cathode materials which was investigated in this work.
One of the main concerns around the use of Prussian blue and its analogs is that when dissolved in strong acid at elevated temperatures, the cyanate within the structure may be released as free cyanide ions. These ions remain in solution. However, the formation of hydrogen cyanide may occur under specific conditions, including exposure to a strong acid under elevated temperatures in a reducing environment. A reducing environment would involve the presence of a reducing agent, such as metal powders, like zinc, hydrogen gas, or other reducing compounds. Therefore, when developing the digestion and analytical method for Prussian blue cathode material, this had to be kept in mind to maintain safety throughout the entire method. There are many technical challenges that an analyst might face when handling battery cathode, anode, or electrolyte samples. For the sake of this presentation, we'll just focus on cathode materials moving forward.
So typically, a high ratio of total dissolved solids may be present in a given battery cathode material digested sample. This makes it a challenging matrix to work with, as there will be high background signal and a range of spectral interferences. Another major problem could be that there are high concentrations of some elements and trace concentrations of other elements, as is the case in sodium-ion battery cathode materials, as there are high concentrations of elements like sodium, iron, manganese, and phosphorus, which adds another layer of difficulty when quantifying the low concentration elements present in the samples. Elements such as potassium and sodium are easily ionized, which results in ionization interference, which causes changes in emission intensity by shifting the ionization equilibrium. Typically, this results in greater intensity of atomic lines and reduced intensity of ionic lines.
Finally, a physical challenge when running higher sample volumes of sodium-ion battery or lithium-ion battery cathode materials is that the high concentrations of sodium or lithium may quickly degrade sample introduction system components, resulting in the analysts having to regularly clean or even replace this expensive hardware. So in this presentation, I'll address some of the ways in which these challenges were overcome. So let's take a look at the instrumentation and setup used in this work. The Agilent 5800 ICP-OES was used with the ICP Expert 7.6 software and SPS 4 autosampler, assisted with sample uptake, automating the sample introduction to the ICP-OES. The default sample introduction components were used in this work. That is a 1.8 mm internal diameter injector, one-piece torch, the Seaspray nebulizer, and the double-pass cyclonic spray chamber.
The instrument parameters used in this work were evaluated and optimized for calibration, linearity, and matrix effects. Axial viewing mode was used for most elements, and radial viewing mode was used only for sodium, iron, manganese, and phosphorus, which were in much higher concentrations. Instrument conditions were changed from the default parameters to ensure accurate data and reduce matrix effects. For example, the auxiliary flow was changed from 1 liter per minute to 1.2 liters per minute, and the plasma flow was increased to 13.5 liters per minute. All samples in this work were digested using the CEM BLADE Microwave Digestion System with the quartz microwave digestion vessels. These vessels are designed for digesting difficult materials, handling high temperatures and pressures with ease.
As you can see, the conditions for the digestion in our work had a maximum power of 1800 W at 180 degrees Celsius for just 10 minutes, with a 2-minute ramp time to reach that temperature. The CEM BLADE can reach the desired temperature in a much shorter time than standard microwave digesters, saving time for research and development-focused labs, as you can test multiple condition sets in the same run. The digestion mixture in this work consisted of 0.05 grams of sample. Depending on if it was a sample or a blank, that would be replaced with water, as well as 5 mL aqua regia and 5 mL water.
Following digestion, the contents of the vessels were emptied into a 50 mL centrifuge tube and diluted to 40 mL final volume, which made for an 800× dilution factor. It should be noted that the vessels were rinsed multiple times with deionized water to ensure complete sample recovery. This left the samples at a final Aqua Regia acid concentration of 16%. Following the digestion of new samples, the Agilent ICP Expert software offers an IntelliQuant screening feature, which actually provides a rapid semi-quantitative analysis, allowing the analyst to learn more about their samples. Specifically, it will give you semi-quantitative concentrations of elements present in your sample, and it allows you to quickly visualize this data in different ways. So here I'm showing a representative periodic table heat map, which is one of the data viewing options. The feature indicates higher concentrations by color.
So in this particular sample of Prussian blue cathode material, you can see sodium, iron, lanthanum, zirconium, calcium, and aluminum are in relatively high concentrations, which is certainly something to keep in mind, as these elements may interfere with the analysis of other elements, leading to inaccurate results. Additionally, this rapid screening allows for the guided design of calibration curve concentrations, rather than just taking a guess at which concentrations will be present in your sample. This saves the chemist time and resources as you can actually design your calibration curves to fit predetermined sample concentrations. The Agilent VistaChip III third generation detector enables such technologies as IntelliQuant screening due to its fast processing speed, full wavelength coverage in every capture, hermetic seal, and one slit used for the entire spectrum.
This unique combination of our superior detector and comprehensive wavelength database allows IntelliQuant to deliver real-time sample insights based on each individual's spectrum that is measured. In addition to helping build calibration curves and figure out which elements are in your sample initially as a method development tool, IntelliQuant can be used as an extra in-run quality control step. Leaving the IntelliQuant feature turned on during your run comes at a 20-second time penalty, however, provides confidence and assurance that there are no elements in high concentrations outside of the ones that you are quantifying regularly.
The semi-quantitative capability of IntelliQuant and r unning this feature every time as a proactive quality control measure can provide you with the confidence that your samples are exactly what they're meant to be, and there are no surprise elements present that may affect the quality of the product manufactured from your sodium, sodium ion battery cathode materials. IntelliQuant also helps identify any potential interferences and determines the optimal analysis wavelength using a star ranking based on potential interferences and other factors. The figure here shows the 267.716 wavelength for chromium is ranked with one star. Hovering the mouse on the red question mark, a message indicates the potential spectral interference of phosphorus 267.711. Chromium 205.560, however, is ranked with five stars and a green tick. This informs us the most suitable wavelength we can use for chromium.
The star ranking system is very helpful with the selection of quantitation wavelengths. So to run the samples for IntelliQuant, there is no need for prior knowledge of the samples or expertise in spectroscopy. With minimal setup of the instrument required, the operator can spend less time to create a customized quantitative method for the sample analysis using features such as the star ranking system mentioned here. So often, customers who suspect a problem with their data will go through standard procedures, such as re-preparing samples, running samples on different instruments, or performing a variety of other time-consuming troubleshooting before identifying the issue. And customers who don't suspect a problem will often simply report incorrect results. So these are some of the reasons why the smart star ranking system and IntelliQuant can be of enormous value to a range of different customers with varying levels of expertise.
So the ICP Expert software also includes automated background correction, so that the variable background structures arising from different sample matrices can be easily corrected for. Fitted background correction automatically models the background signal under the analyte peak, providing accurate correction of both simple and complex background structures. No method development or manual placement of background peak markers is required for fitted background correction, which is a great feature, as off-peak background correction can be extremely inaccurate, as it's hard to know where to measure the background, leading to inaccurate data. Along with fitted background correction, another powerful background correction algorithm in the ICP Expert software, known as FACT, can provide accurate data when one element has a strong interference from another at a very close wavelength. FACT allows the analyst to select a specific interferent and analyte, removing the interferent emission intensity and ensuring accurate data.
Fitted background correction was used for most analyte wavelengths in this study, with a few exceptions. For example, gallium 417.204, where FACT correction was used instead. FACT was used for this gallium wavelength as high concentrations of iron were interfering with the data, as you can see in this figure. Calibration standards were prepared using Agilent single element standard calibration solutions, as well as the Agilent QC 27 standard calibration mixture. The calibration standards were matrix-matched using 16% aqua regia and the same concentrate-- this is the same concentration of acid that was present in the final digested and diluted samples. The calibration range used for each element is shown here in this table. Linear calibration curves were achieved for all elements, as shown by the great calibration coefficients are greater than 0.9995.
Shown above me here on the right are some examples of calibration curves of arsenic, cadmium, cobalt, and phosphorus, all with great correlation coefficients and relative standard errors below 5%, which is what we always aim for. These particular standard curves ranged all the way from 0.05 ppm, all the way to 50 ppm or 500 ppm, as is the case for phosphorus, covering a wide range of concentrations into which our samples could fall. As there are currently no set detection limit regulations regarding the concentrations of contaminating elements in sodium ion cathode materials, we followed the industry standard developed in China to specify method detection limits, MDLs, and limits of quantification, LOQs, for some of the elements analyzed in this work.
The MDLs were measured in the digested sodium ion battery cathode material samples, Prussian blue, sodium iron phosphate, and sodium manganese oxide, to have a more representative result of what real-life samples would actually look like. The MDLs and LOQs reported in this table were calculated based on the analysis of 10 solutions measured over three separate occasions. The MDLs were calculated by multiplying the standard deviation of the 10 blank replicates by 3, while the LOQs were calculated by multiplying the standard deviation of the blank replicates by 10. As shown in this table, the 5800 ICP-OES quantitative MDLs and LOQ values were excellent and will likely fall far below required detection limits set in place by official regulations.
To verify the analytical method, that is the sample digestion and ICP-OES analysis, all samples and a method blank were spiked with 250 ppb of all elements analyzed in this work. Each spike was prepared in triplicate, and each digest was also analyzed in triplicate. Recoveries for all reported analytes fell within ±10% of the expected value, as shown in this table. The excellent recoveries reported in this work are due to the Agilent technology and ICP Expert software that enables the VistaChip III CCD detector, IntelliQuant and IntelliQuant Screening, as well as FACT and Fitted Background Correction features. These results further validate the suitability of this digestion method for the preparation of different sodium-ion battery cathode materials and confirms the accuracy of the 5800 ICP-OES method.
The quantitative data for the three sodium-ion battery cathode material sample digests obtained using the 5800 showed that varying elemental compositions were present in all samples, as expected. The composition of the samples, which varied in levels of sodium, iron, manganese, and phosphorus, represented a diverse range of matrices for which this digestion and analytical method are suitable for. Finally, to assess the stability of the 5800 ICP-OES, 450 sample solutions were measured over 10 hours without recalibration. The QC solution was measured directly after calibration and then after every 10 samples. As you can see in this figure here, it shows the stability of the elements to be within ±10% over the entire course of the run. The QC solution contained 100 ppb of each element in 16% aqua regia.
The results demonstrate the excellent robustness, stability, and precision of the 5800 ICP-OES for the routine quantitative analysis of contaminating elements in sodium-ion battery cathode materials, such as heavy metals like arsenic, cadmium, and lead. What are the benefits from excellent long-term stability performance? Well, it leads to a reduced need to recalibrate, and this improves sample throughput while also reducing running costs. These operational benefits are the result of the novel design of the echelle polychromator in the 5800 and 5900 ICP-OES. The design of the echelle polychromator, compared to most polychromators on the market, include reducing the interior volume to enable the purge gas to rapidly reach equilibrium. Additionally, having a high thermal mass as well as thermostating the optics immunizes the system from fluctuations in environmental conditions during long analysis runs. How did we address the problems initially outlined in this presentation?
Well, understanding the preliminary sample composition using the IntelliQuant feature allowed for accurate preparation of calibration ranges from the start of method development. This addresses the initial problem of not knowing the concentrations or which of the elements are actually present in your sample and guides method development throughout the entire process. Interferences, particularly from EIE effects in the sodium-ion battery cathode material samples containing high concentrations of elements such as sodium, manganese, iron, and phosphorus, were avoided by the SVDV feature of the Agilent 5800 ICP-OES. Further spectral interferences from the complex background structures found in sodium-ion battery cathode materials were corrected for using fitted background correction, as well as the FACT algorithm, two features that are built into the ICP Expert software.
Lastly, all of this was achieved in a simple and safe way, meaning that the Agilent ICP-OES 5800 instrument does not require an expert with years of experience to operate effectively. Overall, the Agilent 5800 and 5900 ICP-OES instruments are easy to use and can handle complex matrices faced in both the lithium and sodium-ion battery industries. An atomic spectroscopy lineup, we start with the lowest cost and entry-level instrument, the AA, all the way up to the 8900 triple quad ICP-MS/MS. For the analysis of contaminating elements in sodium-ion battery cathode samples, different methods can be selected based on several parameters, including the cathode matrix, required method sensitivities, specificity requirements, or available resources for the analysis. In the work presented thus far, we ran the same samples on the 5800 ICP-OES.
This instrument is suitable for the analysis of contaminating elements in sodium-ion battery cathode materials, as has been outlined, providing excellent affordability and sensitivity. Additionally, the ICP-OES complements affordability and sensitivity quite nicely. Being a mid-range, affordable instrument with high sensitivity, it is highly recommended for laboratories looking for an affordable way to determine contaminating elemental concentrations in a range of different lithium-ion or sodium-ion battery cathode materials. In summary, the Agilent 5800 ICP-OES was used for the accurate analysis of multiple elements, including deleterious impurities, in a range of sodium-ion battery cathode materials. The single method developed in this work for three different matrices was able to successfully quantitate 30 elements, further reiterating the simplicity of using Agilent instruments. The samples were prepared using an Aqua Regia-based microwave digestion procedure, with only 0.05 g sample required to be digested.
Such a low amount of sample at an 800 x dilution factor shows the excellent robustness and sensitivity of the Agilent 5800 ICP-OES. The accuracy of the sample preparation and method was confirmed by spiking the method blank and all samples at a concentration of 250 ppb. Recoveries were within 10, 10% in all cases, verifying the accuracy of the method for the accurate measurement of multiple elements in sodium-ion battery cathode materials, irrespective of the sample matrix. The instrument was stable over 10 hours of running complex sodium-ion battery material matrices, as shown in the previous slide. This work demonstrates the suitability of the 5800 ICP-OES for the sodium-ion battery manufacturing industry, specifically to identify and quantify the presence of contaminating elements in varied sodium-ion battery cathode materials.
This slide provides some useful links and resources where you can find some of the accessories, parts, and consumables that were used throughout this application note. You can also find webinars, examples of other application notes, and useful information to help improve your own analytical methods. And on that note, I want to say thank you for joining me today during this presentation. I hope you enjoyed it and found it useful in some way to help develop your own methods in your own labs. I think we have time now to answer some questions. So if you have any, please feel free to send them through, and let's run through them now.
Great, thank you so much for that informative presentation. Before we do get started on the question and answer session, I would like to quickly remind our audience how to submit questions. You can submit your questions by typing them in the Q&A box, which can be found directly below the video player. So to start off, how do you deal with the signal suppression due to the interferences present in these cathode material matrices?
Signal suppression can be unavoidable in cathode material matrices due to the presence of elements such as sodium, manganese, iron, and phosphorus, as is the case in the work presented here. Therefore, a great way of dealing with this signal suppression is through diluting the sample as much as possible without over-diluting, such as to lose signal for the detection of the less abundant contaminating elements. Due to the sensitivity of the 5800 ICP-OES in this work, the sample was able to be diluted 800x , which reduced signal suppression caused by the high concentrations of those elements mentioned earlier.
What is the best way to overcome non-spectral, but rather ionization-related interferences?
Ionization interference is a phenomenon which manifests through a change in emission intensity, causing the ionization equilibrium to shift, particularly when easily ionizable elements such as sodium, potassium, or rubidium are present in high concentrations. So internal standardization, standard addition, and matrix matching calibrations are three great examples of techniques that can be used to deal with ionization-related interferences.
Great, thank you. So moving on to our next question: If we're a laboratory running hundreds of samples every day, how often should we look at cleaning our sample introduction components to maintain a good percentage RSD?
Background correction has been made relatively straightforward with the IntelliQuant feature that automatically detects spectral overlap and displays the results using the star rating system. This means in most cases, fitted background correction will be suitable. Although, it is also important to manually check your wavelengths, and if there are any very close wavelengths of elements that are highly concentrated in your sample, either select an alternative wavelength or, if that's not possible, apply FACT spectral deconvolution to ensure your results remain accurate.
Thank you. With that, it does look like it's already time to wrap up. I want to thank the audience for attending and participating in today's event, and I would also like to thank our sponsor, Agilent Technologies, for making today's educational webcast possible. We would like to ask everyone in the audience to participate in a brief survey, and the survey will appear on your screen after today's presentation has ended. You'll also receive an email alerting you when this webcast will be available for replay, and we invite you to forward that announcement to your colleagues who may have missed today's live event. We hope to see you all next time. Thank you and take care.