{"id":5575,"date":"2022-06-10T15:43:19","date_gmt":"2022-06-10T15:43:19","guid":{"rendered":"https:\/\/www.impactanalytical.com\/?p=5575"},"modified":"2022-08-25T16:30:54","modified_gmt":"2022-08-25T16:30:54","slug":"determination-by-icp-ms","status":"publish","type":"post","link":"https:\/\/www.impactanalytical.com\/whitepapers\/determination-by-icp-ms\/","title":{"rendered":"Determination by ICP-MS"},"content":{"rendered":"\n[et_pb_section fb_built=”1″ admin_label=”Header” _builder_version=”4.16.0″ background_color=”rgba(30,30,30,0.85)” background_enable_image=”off” background_position=”center_right” background_blend=”overlay” custom_padding=”||||true|false” locked=”off” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_row _builder_version=”4.16″ custom_padding=”7px||7px|||” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_column type=”4_4″ _builder_version=”4.16″ z_index=”11″ custom_padding=”||||false|false” custom_padding_tablet=”0px||||false|false” custom_padding_phone=”” custom_padding_last_edited=”on|tablet” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_text _builder_version=”4.17.3″ text_font=”||||||||” text_text_color=”#1E1E1E” text_font_size=”18px” text_line_height=”2em” header_font=”|600|||||||” header_text_align=”center” header_text_color=”#FFFFFF” header_font_size=”54px” header_line_height=”1.3em” header_6_font=”|600||on|||||” header_6_text_color=”#009dd5″ header_6_font_size=”20px” header_6_letter_spacing=”1px” text_orientation=”center” max_width=”700px” module_alignment=”center” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone” header_font_size_tablet=”44px” header_font_size_phone=”26px” header_font_size_last_edited=”on|phone” global_colors_info=”{}” theme_builder_area=”et_body_layout”]
-Knowledge Base-<\/span><\/h6>[\/et_pb_text][et_pb_text _builder_version=”4.17.3″ text_font=”||||||||” text_text_color=”#1E1E1E” text_font_size=”18px” text_line_height=”2em” header_font=”|600|||||||” header_text_align=”center” header_text_color=”#FFFFFF” header_font_size=”70px” header_line_height=”1.3em” text_orientation=”center” max_width=”700px” module_alignment=”center” hover_enabled=”0″ text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone” header_font_size_tablet=”58px” header_font_size_phone=”32px” header_font_size_last_edited=”on|phone” global_colors_info=”{}” theme_builder_area=”et_body_layout” sticky_enabled=”0″]

Determination by ICP-MS<\/h1>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|tablet” admin_label=”About” _builder_version=”4.16″ background_image=”https:\/\/www.impactanalytical.com\/wp-content\/uploads\/2021\/10\/molecules-bg.png” background_size=”initial” background_position=”top_right” custom_padding=”||||false|false” custom_padding_tablet=”||||false|false” custom_padding_phone=”” locked=”off” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_row _builder_version=”4.17.3″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_column type=”4_4″ _builder_version=”4.17.3″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_text _builder_version=”4.17.3″ _module_preset=”default” text_font_size=”16px” text_line_height=”1.8em” hover_enabled=”0″ global_colors_info=”{}” theme_builder_area=”et_body_layout” sticky_enabled=”0″]
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Determination of Nickel and Lead in Wax Samples by ICP-MS
<\/span>
By Barbara Pavan, Ph.D. and Lucia Gardey, Technical Co-op<\/span><\/p>\n

<\/strong><\/p>\n

Introduction<\/strong><\/span>
Paraffin waxes are a refined petroleum product consisting of a mixture of hydrocarbons with approximately twenty to forty carbon atoms. At room temperature, paraffin waxes are white \u2013 to \u2013 colorless soft solids, tasteless and odorless, with a melting point ranging from 52 \u00b0C to 73 \u00b0C (125 – 165 \u00b0F). Different grades and levels of refinement are available and are used in various applications. The most common use of paraffin wax is for the making of candles, when mixed with stearin to increase the melting point. Paraffin wax is also widely used as a coating in the paper and cloth industries, as a coating for candies and hard cheese, and as a chewing gum additive in the food industry. In the spa and beauty industries, paraffin wax is used in wax baths as well as a base for ointments in the pharmaceutical industry. The measurement of heavy metals in waxes such as paraffin is especially important when used in food, pharmaceutical, and candle-making applications. This is due to the likelihood of the material encountering the body through ingestion, dermal contact, or inhalation. The quantitation of heavy metals nickel and lead by inductively coupled plasma \u2013 mass spectrometry (ICP-MS) and the semi \u2013 quantitative determination of mercury, arsenic, cadmium, cobalt, and vanadium in paraffin wax samples used in the production of candles will be discussed.<\/p>\n

Experimental<\/strong><\/span>
The paraffin wax samples were fully dissolved, in order to obtain a successful elemental analysis. Complete dissolution was achieved through an acid digestion using a MARS Microwave \u201cMARS X Press\u201d, 5 mL of concentrated nitric acid and 2 mL of de-ionized water. Approximately 150 mg of the sample material and the above acid solution were permitted to react in open vessels before microwave digestion. The pre-digested solutions were then heated to 200 \u00b0C for thirty minutes in closed, pressurized microwave Teflon vessels in order to be fully dissolved. After digestion, all the sample solutions were clear without any solid residues, and were diluted to 50 ML with water, followed by a further 1:2 dilution for the analysis. The ICP-MS analysis was performed using an Agilent 7700x spectrometer. The sample induction system included a low-flow concentric nebulizer and temperature-controlled spray chamber. The instrument was equipped with a third generation Octopole Reaction System using helium as the collision gas, with a flow rate of 4.3 mL\/min [3]. Bismuth and germanium with a concentration of one part per million (ppm) were used as internal standards in order to improve accuracy. Calibration standards for nickel and lead were prepared at 10 and 100 parts per billion (ppb) from NIST traceable standards. Both the internal standard and the calibration standards were prepared with a 2% v\/v nitric acid matrix. The Detection Limit (DL) and Quantitation Limit (QL) were estimated based on the blank analysis and the slope of the calibration curves.<\/p>\n

Results and Discussion<\/strong><\/span>
During the analysis, the instrument was operated in helium collision mode (He-mode) for all analytes and samples. The use of a collision\/reaction cell filled with gas (helium in this case) is a well-known approach to effectively eliminate polyatomic and molecular interferences such as 40Ar35Cl+ interfering with 60Ni [1, 2]. As an inert gas, helium does not cause any new interference with the analytes. The internal standard solution was co-injected using a \u201cT\u201d junction which allowed for the constant addition of the internal standard elements to both calibration standards and samples alike without the need for spiking each solution. The use of an internal standard is a very effective way to minimize matrix interferences (arising, for example, from slight differences in the matrix makeup), and ultimately improving the accuracy of quantitative analyses [2]. The choice of the internal standard elements for this work was based upon the fact that they were not present in the sample and were very close in atomic mass and ionization potential to the elements of interest. The fluctuations of the internal standard elements were monitored during the analysis, and their variation was within 80-120% (Figure 1).<\/p>\n

\"Nickel<\/p>\n

Figure 1. Internal Standards (ISTD) recoveries during the analysis of paraffin wax samples.<\/p>\n

<\/em>
The calibration curves were found to be linear for both elements, with R2 values greater than 0.9999 (only the bottom three points in Figure 1 were used). In modern instruments, ICP-MS is well known for having very good linearity over a large range (up to nine orders of magnitude [2]). In this work, the calibration curves for nickel and lead were generated only using three points in the range of 0-100 ng\/mL (ppb). The linearity was previously evaluated over five point calibration curves, and the use of only three points was deemed equivalent and was chosen in order to reduce the time of analysis (Figure 2).\u00a0<\/p>\n

\"Nickel
Figure 2. Calibration curves for nickel and lead (top) 5-points and (bottom) 3-points<\/p>\n

<\/em>
The results after adjustment for sample weights and dilutions are reported in Table I. No nickel was detected in any of the samples, with a detection limit of 8 ng\/g (ppb). Lead was found only in some of the samples analyzed, with concentrations ranging from 0.6 to 26 ng\/g (ppb). The detection limit for lead was 0.1 ng\/g (ppb).\u00a0<\/p>\n

\"Nickel<\/p>\n

The semi-quantitative results for vanadium, cobalt, arsenic, cadmium and mercury are summarized in Table II. These elements, together with lead and nickel, are part of the Class 1 and Class 2A elemental impurities according to the ICH Q3D guideline [4]. The Class 1 elements (arsenic, cadmium, mercury, and lead) are well known human toxicants, while the Class 2A elements (cobalt, vanadium, and nickel) are route-dependent human toxicants and have a relatively high probability of occurrence in a finished good through it production process. These elements (excluding cobalt) are also included in the new USP <232> chapter [5].<\/p>\n

The semi-quantitative analysis was performed in He-mode to minimize polyatomic interferences. It was carried out by having the mass spectrometer scan the entire mass range and acquire responses from all elements and isotopes. The concentration of each element was then estimated based on the known relative responses for all isotopes [6]. This analysis does not have the same accuracy and precision of a quantitative method, but it can be used successfully to rapidly screen the composition of unknown samples, even during the quantitative analysis of specific elements.<\/p>\n

\"Nickel<\/p>\n

Conclusions<\/strong><\/span>
This work demonstrates the versatility and good sensitivity of ICP-MS in the quantitation of heavy metals, also giving the possibility of monitoring other metals. The sample preparation for elemental impurities analysis is a critical step, and the use of microwave digestion allowed for a rapid and complete dissolution of all the samples. Furthermore, the use of closed vessels was essential to avoid losses of volatile elements such as arsenic and mercury.<\/p>\n

The greatest advantage of ICP-MS over other elemental analysis techniques such as graphite furnace atomic absorption (GF-AAS), or flame-atomic absorption (F-AAS) is that all of the elements can be acquired with one single injection and in a short period of time (less than four minutes per injection). The total analysis time for the work presented in this paper was in fact only 56 minutes. Finally, a similar analytical method can be successfully applied to a wide set of petroleum refined products with only minor modifications in the digestion and analysis procedures.<\/p>\n<\/div>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16.0″ _module_preset=”default” background_color=”#009dd5″ background_enable_pattern_style=”on” background_pattern_style=”tufted” background_pattern_color=”rgba(0,0,0,0.06)” custom_padding=”0px||0px||true|false” global_module=”4668″ saved_tabs=”all” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_row _builder_version=”4.16.0″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_column type=”4_4″ _builder_version=”4.16.0″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”et_body_layout”][et_pb_cta title=”Ready to Get Started?” button_url=”@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjI3MiJ9fQ==@” button_text=”Request a Quote” _builder_version=”4.16.0″ _dynamic_attributes=”button_url” _module_preset=”default” header_font=”|700|||||||” header_font_size=”36px” body_font_size=”16px” background_enable_color=”off” custom_button=”on” button_text_size=”14px” button_border_radius=”0px” button_letter_spacing=”1px” button_font=”|600||on|||||” button_icon=”=||divi||400″ button_on_hover=”off” global_colors_info=”{}” button_bg_color__hover_enabled=”on|hover” button_bg_color__hover=”#009dd5″ button_bg_enable_color__hover=”on” theme_builder_area=”et_body_layout”]

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-Knowledge Base-Determination by ICP-MS Determination of Nickel and Lead in Wax Samples by ICP-MSBy Barbara Pavan, Ph.D. and Lucia Gardey, Technical Co-op IntroductionParaffin waxes are a refined petroleum product consisting of a mixture of hydrocarbons with approximately twenty to forty carbon atoms. At room temperature, paraffin waxes are white \u2013 to \u2013 colorless soft solids, […]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[11],"tags":[],"_links":{"self":[{"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/posts\/5575"}],"collection":[{"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/comments?post=5575"}],"version-history":[{"count":3,"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/posts\/5575\/revisions"}],"predecessor-version":[{"id":6024,"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/posts\/5575\/revisions\/6024"}],"wp:attachment":[{"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/media?parent=5575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/categories?post=5575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.impactanalytical.com\/wp-json\/wp\/v2\/tags?post=5575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}