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Determining the Impact of Alpha-Particle-Emitting Contamination From the Fukushima-Daiichi Disaster on Japanese Semiconductor Manufacturing Sites Robert C. Baumann, Fellow, IEEE
Abstract—We review the major radioactive isotopes formed in nuclear reactors and consider how these were released and dispersed in the days following the Fukushima-Daiichi accident. The risk of contamination from uranium and plutonium isotopes at semiconductor manufacturing sites in Japan is discussed, and the first report of alpha-counting measurements is presented demonstrating that no alpha-emitting contamination was found in either of the two manufacturing facilities. Index Terms—Alpha-particles, contamination, nuclear reactor, radiation, soft error rate.
I. INTRODUCTION
T
HE Fukushima Daiichi Nuclear Power Plant on the North Eastern Coast of Honshu was built and is operated by the Tokyo Electric Power Company (TEPCO) and consists of six light (boiling) water reactors generating a total of 4.7 GW [1]. The plant suffered major damage during the March 11, 2011, magnitude-9 “Higashi Nihon Daishinsai” (Eastern Japan Great Earthquake Disaster), which knocked out primary power systems. Arriving minutes after the earthquake, the tsunami flooded the diesel back-up generators disabling them. Remaining battery systems were exhausted hours later leading to a complete loss of electrical power. The resultant power loss shut off the water circulation system and gas venting equipment critical for keeping the fuel cool and keeping reactor containment pressures low. The water in the reactor cores became super heated, and the water levels in the spent fuel pools dropped with a growing concern that the fuel assemblies would be exposed to air and catch fire. During normal operation of a nuclear reactor, when the fissionable material in the fuel rods has been consumed, the fuel rods are considered “spent”. Spent fuel rods are removed from the reactor core and replaced with new ones. The spent fuel is stored in large pools of water for months or years before being recycled and disposed of off-site as nuclear waste. In the case of the Fukushima-Daiichi plant, these pools were located at the top of the reactor buildings. Under normal conditions a constant flow of water cools the fuel Manuscript received September 12, 2011; revised December 09, 2011; accepted January 27, 2012. Date of publication July 10, 2012; date of current version August 14, 2012. The author is with Texas Instruments, Dallas, TX 75243-1115 USA (e-mail:
[email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TNS.2012.2201749
in the reactor core and spent fuel pools by removing latent heat generated within the fuel by the fission process (in active reactor cores) and natural radioactive decay processes (in reactor cores and the spent fuel pools). Loss of water circulation allowed fuel temperatures to rise precipitously, ultimately leading to large amounts of hydrogen gas as water came in contact with the over-heated fuel rods. The hydrogen gas accumulated in units 1 and 3 and the increased pressure could not be released since the vents required power to operate and were closed prior to the loss of power. The pressure continued to build in the reactor cores until finally, something set off two hydrogen explosions breaching the building and core containment structures. Reactor 3, which had been recently converted to a mixed oxide (MOX) fuel with fissile uranium and plutonium, suffered a partial meltdown of the fuel assemblies. There is some evidence that the core of unit 2 may also have suffered a core melt-down and lost containment. Unit 4 was not in operation and was not fueled at the time of the earthquake; although, a fire did breakout and damage the exterior building structure. Reactors 5 and 6 were shut down successfully without damage to the buildings or containment [2], [3]. Later reports indicate that while the water levels in the spent fuel pools went down, all of the spent fuel assemblies remained submerged [4]. Ultimately, three reactor cores melted and containment was breached in two cases [5], releasing large quantities of radioactive contamination into the air, soil, and sea-water around Fukushima. The Japanese authorities rightfully focused on the release of the highly radioactive fission by-products that decay primarily by producing beta-particles and gamma photons as these pose serious health risks to the local population. Soft errors occur when single radiation events cause enough of a charge disturbance to reverse or flip the state of a memory cell, register, latch, or flip-flop. The error is “soft” because the circuit or device, itself, is not permanently damaged by the radiation; if new information is written to the bit, the device will store it correctly [6]. As will be shown, for semiconductor manufacturing and packaging processes, the primary risk from the Fukushima-Daiichi accident is not the gamma- and beta-particle-emitting isotopes, but the release, dispersal, and potential infiltration (into the clean-room) of alpha-particle-emitting contamination from the nuclear fuel. The fact that alpha-particles can dramatically increase and, in some instances, dominate the SER in semiconductor devices is well established in the literature [7]–[10]. We confirm that isotopes of uranium, plutonium, and other alpha-particle-emitting actinides were released by the Fukushima-Daiichi accident with an analysis of
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BAUMANN: DETERMINING THE IMPACT OF ALPHA-PARTICLE-EMITTING CONTAMINATION FROM THE FUKUSHIMA-DAIICHI DISASTER
Fig. 1. Location and distance of two manufacturing facilities from which samples were obtained with respect to the Fukushima Daiichi Nuclear Power Plant where radioactive contamination was released after the tsunami.
air monitor data collected by the United States Environmental Protection Agency (EPA) and a review of TEPCO soil contamination data [11], [12]. We provide a theoretical calculation of the amount of surface contamination needed to cause a soft error problem and a consideration of the impediments to quantitatively determining the dispersion of these isotopes and the likelihood that such airborne contamination could make its way through the clean-room filters. The first report of alphaparticle counting measurements is presented from samples obtained from two manufacturing sites situated in the cities of Mihomura and Aizuwakamatsu, whose locations in relation to the Fukushima-Daiichi plant are shown in Fig. 1. II. BACKGROUND A. Dominant Processes in Nuclear Reactor Environments There are three primary mechanisms producing the unique mix of radioactive isotopes found in a nuclear reactor: natural radioactive decay, neutron capture reactions, and the thermal neutron-induced fission reaction. It is helpful to review these processes in terms of the types of nuclides that they produce when trying to establish whether or not specific isotopes were released into the environment by a specific incident such as the one that occurred at the Fukushima-Daiichi power plant. Radioactive decay is a random process by which unstable nuclei lose energy by emitting particles and/or electromagnetic radiation. This process occurs spontaneously without any external interaction with other particles or radiations. The decaying atom is called the parent, and the decay product is called the daughter. Typically the decay results in the emission of an energetic electron (either a beta-minus particle or the ejection of an inner core electron by an internal conversion event [13]) or the emission of an alpha-particle. The kinetic energy of the emitted beta-minus (an electron anti-neutrino is also emitted, but this generally does not have any potential effect on biological or electronic systems due to its extremely low interaction cross-section) is a smooth function of energy ranging from 0 to a few MeV with the maximum energy determined by the type of nucleus from which it was emitted. In contrast, a conversion electron, having been
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“knocked” from one of the core atomic orbitals, is emitted with one of a few discrete kinetic energy values (usually in the tens or hundreds of keV). Alpha particles (helium nuclei) are emitted from decaying nuclei with unique and discrete kinetic energies typically somewhere between 4 to 9 MeV. Additionally, after the radioactive decay event, a gamma-photon is emitted when the newly formed daughter nucleus “relaxes” to a lower energy state [14]. The resultant particle emission and the gamma photon emitted after the decay have energies that are unique and characteristic for a specific decay pathway. Isotopes of Uranium, Thorium, Plutonium, and other actinides typically undergo a succession of decays until the nucleus has reached a stable state (usually an isotope of lead). The radioactive decay of a large assembly of identical atoms (nuclides) will occur at a constant rate, and the quantity of the parent isotope can be determined as a function of time according to exponential decay as follows:
(1) Where is the initial time-zero concentration (assuming all the parents are created at the same time or within an interval much shorter than the half-life of the parent), is the concentration at any specific time , and is the decay constant . is unique for each nuclide and can be obtained using the half-life, , the time it takes for the initial parent concentration to decay to one-half its original amount as follows:
(2) (3) (4) is the activity, a measure of the rate of radioactive where decay in a material, defined as the number of disintegrations or decays per time interval. In SI units activity is typically reported in Becquerel (1 per second). The shorter the half-life of a specific isotope, the higher its activity. A related term, specific activity, quantifies activity in fluids and gases on a per-volume basis ( , , or l) and in solids, on a per-mass basis (Bq/kg of solid). For example, reports of specific activity released from the Fukushima-Daiichi accident included air sampling measurements calibrated to , soil samples reported in Bq/kg of dry soil, and Bq/l of seawater. Surface activity quantifies activity from a surface and is typically used to monitor deposition of radioactive contamination on the ground. It should be noted that activity only quantifies the strength of a source in terms of its radiation emission rate. Different types of ionizing radiation have very different effects in the materials and systems with which they interact, and one needs to consider exposure, absorbed dose, and dose equivalence [15]—we touch on this aspect later when we compare the ionization efficiency of electrons (beta-minus particles, conversion electrons, and electrons ionized from gamma photon interactions) and alpha-particles in silicon.
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Neutron capture, in contrast to natural radioactive decay, is a nuclear reaction requiring the presence of an external catalyst, as its name implies, a neutron. This reaction occurs when the nucleus of a target isotope captures a neutron (the nuclear reactor core is bathed in neutrons from fission and natural decay processes) transforming the original isotope into a heavier one as illustrated: (5) Where is the chemical symbol, is the nuclear mass number, is the atomic number, is the neutron number, is the incident neutron and represents the emission of a gamma photon. With a continued exposure to the high-flux neutron field in a fission reactor, successive additional neutron capture events create even heavier isotopes ( , , etc.), but as these require more than one reaction, their reaction cross-sections are multiplied, and, hence, the overall probability of formation (its rate of formation) is significantly smaller. The newly formed isotope spontaneously emits a gamma photon and undergoes subsequent radioactive decays as it seeks its stable form, typically an isotope of lead. Neutron capture reactions are responsible for the transmutation of uranium nuclides into heavier isotopes of plutonium, americium, curium, etc. that appear in small quantities in spent fuel. The reason that these reactions are important is that since many of these isotopes do not occur in nature, their presence in the environment serves as definitive proof that a detected activity was indeed released by a nuclear facility as opposed to being just natural background activity. The primary nuclear reaction during the operation of a nuclear power plant is nuclear fission (spontaneous fission, where the nucleus fissions without absorbing neutrons also occurs, but due to its negligible cross-section for most isotopes, this process can generally be ignored). Due to its relatively high natural abundance and large thermal neutron fission cross-section, the most common isotope used in nuclear fuel is . Upon absorbing a thermal neutron, the nucleus breaks apart into two smaller nuclear fragments, or fission fragments, and emits two or more prompt neutrons (neutrons emitted immediately at the time of the reaction). The emission of these additional neutrons sustains the nuclear reaction as they are subsequently moderated in the reactor and absorbed by other nuclei, in turn, inducing more fission reactions. The fission fragments produced by any given fission reaction are not unique. Indeed, there is a wide range of possible fragments produced as shown in Fig. 2. For any given fission reaction, the two fission fragments will almost always be of unequal mass and will vary in terms of their mass number. Three of the many possible thermal-neutron-induced fission reaction pathways are shown below: (6) (7) (8) The emission of neutrons that is a key to sustaining the fission process occurs because the number of neutrons relative to the
Fig. 2. Distribution of fission fragments (adapted from [16]) as a function of atomic number. These fragments are highly radioactive and depending on the isotope are biologically active (easily assimilated in living organisms).
number of protons is smaller for lighter elements than for heavy elements. In other words, heavier nuclei are “neutron rich” as compared with lighter ones. When a heavy nucleus splits into two much lighter fission fragments, the fragments are highly unstable due to the excess number of neutrons and these are shed immediately. The number of prompt neutrons emitted is a function of the type of fission fragments generated. The average number of neutrons produced by the thermal-neutron-induced fission of is 2.42 [17]. The light water reactors (boiling water reactors) of the type employed at the Fukushima-Daiichi plant use so-called low-enriched uranium as the nuclear fuel. The uranium is formed into cylindrical pellets of that are encased inside metal rods. The Uranium is “enriched” in terms of having a higher concentration of , usually between 3–5%, as opposed to the naturally-occurring concentration of 0.72%. The fission process is useful in that it creates a tremendous amount of heat since the total kinetic energy of the fragments is quite high ( per fragment pair) [18]. The heat produced by the fission process is absorbed by water that turns to steam, which, in turn, spins a turbine that generates electrical power. B. Potential Contamination From Nuclear Reactors A large fraction of the nuclear wastes produced by the fission process are the fission fragments. They are much lighter than the actinides in the nuclear fuel from which they are derived and highly radioactive (they have short half-lives, thus, high activity). They decay by emitting gamma photons and beta particles. Of primary biological concern are the isotopes of iodine, cesium, and strontium. While the iodine isotopes are relatively short-lived (the longest-lived iodine isotope from fission is with a half-life of 8 days), large quantities can be taken up by the thyroid gland where the high activity causes genetic damage, cell death, and cancer. Iodine radioisotopes released after the Chernobyl disaster were directly responsible for an epidemic of thyroid cancers in Ukrainian children [19]. and , with half-lives of 30.2, and 29.1 years respectively, pose the greatest health hazard as they are easily incorporated and
BAUMANN: DETERMINING THE IMPACT OF ALPHA-PARTICLE-EMITTING CONTAMINATION FROM THE FUKUSHIMA-DAIICHI DISASTER
have long enough half-lives to have an effect for hundreds of years. Cesium has a chemical activity similar to potassium and, thus, is readily incorporated throughout the body. Chemically similar to calcium, strontium gets incorporated and concentrated into the bone. Such internalized sources of gamma and beta radiation can cause cancer, genetic damage, and, in high enough doses, radiation sickness and death. A copious amount of radioactive cesium and iodine contamination was released into the atmosphere and ocean after the Fukushima-Daiichi accident. A total integrated activity (from March 11 to June) from of up to 60,000 was determined from soil samples obtained near Mihomura [20]. A similar activity of iodine isotopes was also released, but as these isotopes have half-lives of minutes or seconds, activity from this source quickly subsided. Prior to the incident and after June 2011, the levels of these and other isotopes were below detection limits. So the large surface activity was deposited from March to June, with a peak immediately after the incident. A large amount of contamination was also released into the sea and a portion of the surface contamination entered the fresh water supply around Fukushima, yet contamination levels in drinking water remained below detection limits [21]. Sea-water contamination is not a concern from the semiconductor manufacturing point-of-view, and contamination in fresh-water, if present, would be removed during normal clean-room processing (de-ionization and removal of metallic impurities). Even in the unlikely event that such fission fragments in air or water led to a surface distribution on silicon wafers or other semiconductor materials, the radiation they emit poses virtually no threat to the reliability of semiconductor devices, at least from the point of view of soft errors, due to their low stopping power. The stopping power or linear-energy transfer (LET) of alpha-particles and electrons (beta-particles are relativistic electrons and when gamma photons interact with matter they create electrons) is shown in Fig. 3. Typical high-density digital semiconductor devices today store a signal charge on the order of 1–10 fC within a single bit (or flip-flop) [24], [25]. To create a soft error or bit-flip, a radiation event must induce at least that much charge within a sensitive node. Alpha-particles can typically generate enough charge to corrupt a sensitive node since at their emission energies (4–9 MeV) they will typically generate between 4–25 fC with collection typically occurring over 1–2 . In contrast, the stopping power of electrons is two to three orders-of-magnitude lower. It is, therefore, unlikely that beta-particles can induce enough charge to create a soft error. Gamma photons produce electrons (typically at energies ) via the photoelectric effect, Compton scattering, or pair production [26]. These electrons will rarely, if ever, produce sufficient secondary ionization to cause a soft error due to their low stopping power. Additionally, since most gamma photons will traverse the device layers without interacting at all, the production of electrons within range of an active node will be a very rare event. Thus, from a semiconductor device point-of-view, the highly radioactive fission fragments that are so dangerous to biological systems are unlikely to cause any soft errors in semiconductor devices. Ionizing radiation can induce threshold voltage shifts that are proportional to the trapped interface and oxide charge generated
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Fig. 3. Stopping power in silicon for alpha particles calculated using SRIM [22] and for electrons using ESTAR [23]. The electron stopping power applies to beta-particles as well as electrons produced by gamma photons.
when radiation is absorbed in gate and isolation dielectrics. The charge is built-up over time, and the effect of the overall exposure is quantified as total ionizing dose (TID) in units of radiation absorbed dose . At high doses the threshold voltage shift can be large enough to induce substantial isolation leakage and functional failures [27]. Consider a worstcase thought-experiment where 100% of the reported total outdoor soil activity of 60,000 or 6 is deposited on a wafer surface (this obviously assumes that clean-room air filtration does nothing). The emission from a surface distribution of gamma and beta-emitters will be isotropic, so no more than half of the emissions will intersect the oxide area, thus the flux becomes 3 . Assume a large chip of 0.5 , with an isolation oxide that is 1 thick (the effect of TID on ultra-thin gate dielectrics a small fraction of its effect in the thicker isolation oxides in deep sub-micron technologies). For simplicity we also assume that all the photon energy is absorbed in the oxide (realistically the total absorption would be averaged over all angles given the LET of 1 MeV photons in a 1 oxide) and that all emissions are uniquely 1 MeV. Over a typical 10-year operational lifetime, the device area will receive 4.7 events (1.5 events/sec over a decade) amounting to a TID of:
(9)
(10) (11) where is the total energy absorbed (in J) within the target layer and is the mass, in kg, of the absorber. Despite the extremely conservative assumptions made, the TID over a decade of product life is less than ten rad . In comparison, commercial semiconductor technologies can tolerate dose exposures from thousands to hundreds of thousands of rad
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and still function properly [28]–[30], clearly demonstrating that the TID impact of fission fragments is negligible for chip manufacturing processes. From a sensitivity point-of-view, the primary contamination sources of concern for semiconductor technologies are, therefore, the alpha-particle-emitters. The contaminants in a nuclear power plant are defined by the type of fuel and where in the fuel cycle it is. As fission proceeds the fuel is “used up” (the becomes depleted [31]), fission fragments are generated, and new isotopes are generated by neutron capture and natural radioactive decay. The isotope mix for fuel that has been in a nuclear reactor about one year is shown in Table I. Note that due to the depletion of by fission, the original enhanced content of of 3.3% has been consumed to a content of 2.4%. These isotopes are all alpha-particle emitters (either directly or by daughter activity) and thus a potentially problematic source of radioactive contamination for semiconductor devices. The relative activity accounts for the quantity of an isotope and its non-equilibrium daughter contributions as a function of activity. In cases where the half-life of the parent is much longer than that of the daughter products, the additional contributions from the daughters is included, since, on average, the daughters will have decayed long before the next parent decay. The alpha factor accounts for this additional activity. After the Fukushima Daiichi disaster, it became clear that none of the spent storage pools were exposed, but at least two reactor cores lost containment, so the isotopes in Table I are expected to be the primary sources of alpha-emitting contamination. If some of these isotopes are able to breach clean-room air filters and get incorporated into a semiconductor process, even in relatively small amounts [34], they would dramatically increase the SER. III. RESULTS AND DISCUSSION A. Release of Contamination To ascertain the SER risk to silicon devices manufactured or packaged in Japan, we must first determine if the Fukushima Daiichi accident released any alpha-particle-emitting radioisotopes into the environment. The large release of gamma- and beta-emitters implies that there may have been a concurrent release of alpha-particle-emitting contamination, but is there definitive data that supports this assumption? The isotope activities from EPA air monitor data [35] were downloaded for the islands of Guam, Saipan, and for the states of Hawaii, California, Washington, and Alaska (Table II lists geographical distances from the Fukushima-Daiichi plant and dates represent the day the air was sampled). In order to generate a statistical background, the data from 1978 –2010 was averaged for these locations (Guam and Saipan did not have previous data, thus data from Honolulu were used as background. The background was compared with 2011 readings taken after the Fukushima Daiichi accident—the measurements at different locations were collected on different days and, thus, any correlation to geographical distance is weak, since the level of contamination was a strongly time-varying quantity. A 90% upper confidence interval was applied to all of detected uranium and plutonium isotope activity and plotted as a function of measurement location in Figs. 4(a) and 4(b) respectively. Airborne activity of
TABLE I ISOTOPE MIX IN NUCLEAR FUEL (
YEAR OLD)
uranium and plutonium isotopes above background levels was detected at all locations after the Fukushima-Daiichi accident, confirming that these were released and dispersed into the air stream by the accident. It should be noted that the summed activity from all these isotopes was at least 200 thousand times lower than the activity from naturally-occurring radon gas in outdoor air [36], [37] and, therefore, despite alarming claims from some media sources, the human health risk from this contamination is negligible at these locations. The key concern is that the alpha-emitting contamination could potentially cause SER problems in semiconductor devices if the activity from this contamination were above the normal background levels in the environments where devices are manufactured, specifically in Japan where highest activity levels had been deposited. Some soil sample measurements were made by TEPCO around the Fukushima-Daiichi plant, and while early data suggested that no significant uranium or plutonium contamination had been released, more detailed reports later confirmed the release of small quantities of plutonium, americium, and curium [38]. This more recent result supports the various EPA data indicating that alpha-emitting reactor products had, indeed, been released (curium and americium are specific to neutron capture reactions in a nuclear reactor and are not found in nature). Levels seem relatively low, but, unfortunately, there were no concurrent air-filter measurements taken for any of these actinides in surrounding areas, and, thus, airborne concentrations and dispersal patterns over the Japanese countryside are not well-defined.
BAUMANN: DETERMINING THE IMPACT OF ALPHA-PARTICLE-EMITTING CONTAMINATION FROM THE FUKUSHIMA-DAIICHI DISASTER
Fig. 4. (a) Summary of EPA RadNet air filter data showing detected and background activities for uranium isotopes as a function of detector site.
Fig. 4. (b) Summary of EPA RadNet air filter data showing detected and background activities for plutonium isotopes as a function of detector site.
TABLE II DETAIL OF EPA AIR-MONITOR SAMPLE LOCATIONS SHOWING DISTANCE FROM FUKUSHIMA AND COLLECTION DATES (THE FIRST RELEASE OF RADIATION FROM THE FUKUSHIMA-DAIICHI PLANT OCCURRED ON MARCH 12, 2011)
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air column onto the ground by dry deposition. During precipitation events (mist, rain, etc.), as was the condition around the Fukushima-Daiichi site, additional, wet deposition, occurs as particles get entrapped in water droplets and fall to the ground with the rain. Wind and other mechanical agitations of soil surface can cause some of the deposited particles (smaller than 50 ) to become re-suspended in the air—allowing further dispersion of the contamination (resuspension was presumably minimized in the area since the soil surface was moist from rain). To understand how much of a released contaminant reaches a specific location over time is a complex problem that depends on many interdependent factors such as the concentration and duration of the original release, the way it was released (explosion, fire, slow leak, etc.), the height of release, wind direction, air temperature, air pressure, humidity, and the morphology of the surrounding terrain. Calculations of this type are often referred to as dispersion modeling with the Gaussian plume model [40] being one of the most conceptually simple. Diffusion and advection are used to model the spreading of an initial concentration of contamination. The concentration profiles assume a Gaussian or skewed Gaussian shape and vary based on the distance from the source, time-dependence of the source, and atmospheric conditions. In cases with wind, the maximal ground concentration is usually not at the emission point (ground zero) but, in fact, can be located many kilometers away. So a simple-minded assumption that the air and soil contamination around the Fukushima-Daiichi plant is a maximum and that areas farther away must have lower concentrations is a poor assumption. The wind direction at the Fukushima-Daiichi plant was primarily to the east for the majority of the time during which contamination was released, and, thus, much of it was sent over the Pacific. Another qualitative factor is the local terrain. For example, since Aizuwakamatsu is located just west of the 1812 m volcanic peak of Bandaizan, it is conceivable that dispersion of westward-born contamination was blocked and enhanced in surrounding areas by the presence of the mountain. Ultimately, with the dearth of air measurements of alpha-emitting contamination in the air around Japan, quantitative modeling is not possible. C. Infiltration of Particulate Contamination
B. Dispersion of Particulate Contamination As contamination is released into the atmosphere, it is immediately acted upon by various atmospheric processes as illustrated in Fig. 5. Radioactive particulates formed from uranium and plutonium isotopes are relatively heavy. After their release into a plume, the influence of gravity and atmospheric drag will cause a large portion of the larger particulates to fall out of the
Since we cannot ascertain with any fidelity the levels of alpha-particle-emitting contamination that reached the manufacturing sites, it is instructive to consider the level of surface contamination that would be problematic and some estimation for the amount of outdoor particulate contamination that might be able to infiltrate the clean-rooms. Clean-rooms have multiple stages of filtration culminating in a series of High-Efficiency Particulate Air (HEPA) and Ultra-Low Penetration Air (ULPA) filters capable of capturing virtually all particles bigger than 0.3 and 0.12 respectively. Other filters with specially designed media are often also used to capture particles as small as 0.01 [41]. Thus to some extent, the size of airborne particles determines their ability to infiltrate a clean-room environment. One study indicated that the smallest uranium/plutonium oxide particles from nuclear fuel were 2 [42] and indicated that particle sizes shrank with increasing
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Fig. 5. Diagram showing complex environmental factors that control the dispersion of contamination entering the atmosphere (adapted from [39]).
clean-room air filters in use during and after the disaster to determine the total airborne alpha-emitting activity around the manufacturing facilities (the caveat being that the clean-room filters were not operating until power was restored after the primary emissions from the Fukushima-Daiichi plant had occurred). D. Simplistic Calculation of Alpha Contamination
Fig. 6. Log-normal fit (gray line) and cumulative distribution (black line) of the mass density function of uranium oxide dust collected at a nuclear fuel manufacturing site as a function of the aerodynamic diameter data (black circles) reported in [46].
distance from the source, implying that the larger, heavier particles deposited out of the air stream within a few kilometers of the emission source. In an EPA study of dust from fuel fabrication processes, particle sizes were found to range from 0.1 to 20 with a median value of about 1.3 [43]. The aerodynamic particle diameter (a common method for converting oddly shaped particles with different densities to equivalent spherical particles having a density of one and the same inertial properties as the original particles [44]) distribution of uranium oxide from this study is shown in Fig. 6 (black circles) with a bimodal log-normal fit (gray curve) and a cumulative distribution plot (black). The scarcity of particles below 0.1 is consistent with experimental evidence related to aerosols in which particles smaller than 0.1 tend to agglomerate into larger particles with diameters in excess of 0.1 [45]. Assuming similar particle size trends for the airborne contamination emitted by the Fukushima-Daiichi accident, the filtration in typical clean-room air-handlers will remove virtually all particles bigger than 0.3 from an air stream. An interesting experiment, unfortunately beyond the scope of this study, would have been to perform gamma spectroscopy on
One way to estimate of the magnitude of alpha-particle flux emitted from surface contamination is to assume a specific particle size, composition, and surface density. For simplicity the diameter of all particles is assumed to be 0.3 consistent with the typical filtering capabilities of HEPA. Larger particles are generated inside the clean-room by equipment and personnel, but these are not radioactive and, hence, not relevant for this calculation. Since the actinides are fairly reactive and readily form oxides in nature, the calculation assumes the isotopes will assume their most common oxide form. Studies of particulates and their distributions on wafer surfaces in sub-micron clean rooms reveal that diameter particles have a range of surface densities from to 0.06 [47], [48]. For 8” wafers (314 ) this is equivalent to a surface density range of 1 to 19 particles per wafer. The alpha-flux towards the active devices from a 0.3 radioactive particle was approximated according to:
(12) is the alpha-flux, is the number of daughters Where that also contribute to the alpha-flux, is the area on which the contamination resides, is the half-life of the parent isotope, is the density of the radioactive particle, is Avogadro’s constant, is the molar mass, is the radius of the particle (in our case 0.15 ), and is the stoichiometric fraction of the most common form (e.g., is one of the more commonly occurring forms of uranium and is composed of three atoms, one uranium for every two oxygen atoms and thus the ). The pre-factor of one-half discounts alpha-particles emitted in the hemisphere that does not intersect the active device plane since these will generate any soft errors.
BAUMANN: DETERMINING THE IMPACT OF ALPHA-PARTICLE-EMITTING CONTAMINATION FROM THE FUKUSHIMA-DAIICHI DISASTER
TABLE III DIAMETER ALPHA-FLUX FROM CONTAMINATION ASSUMING 0.3 PARTICLES WITH LOWER-BOUND AND UPPER-BOUND SURFACE DENSITIES OF 1 AND 19 PARTICLES PER WAFER RESPECTIVELY. GRAY ENTRIES REPRESENT FLUXES THAT ARE BELOW THE DETECTION LIMIT OF THE ALPHA COUNTING EQUIPMENT
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specific isotopes, so particles of all types will be present. Furthermore, since it is likely that many of the particles will be agglomerations of various different isotopes [49], and since the fraction of particles composed of specific isotopes is expected to be similar to their relative abundance in nuclear fuel, the rarer isotopes are less likely to be the predominant particulate. Thus, even with minimal surface contamination, the chance of a false negative is rather low. E. Alpha-Particle Counting
Table III was generated using (12) and a lower-bound of 1-particle-per-wafer and an upper-bound of 19 particles-per-wafer. For the purposes of detection by alpha-counting, the last two columns are more pertinent since the alpha-flux is calculated relative wafer area. In general, alpha-counting is relevant for lower-activity alpha-emitting isotopes that are uniformly distributed over the wafer area (a distribution of to particles of uranium isotope would be required to generate a flux of 0.002 ). Entries with gray shading in Table III represent fluxes that are below the detection limits of the alpha-counting equipment. For the maximal surface contamination of 19 particles-per-wafer, alpha-counting experiments easily detect all but three of the possible radioisotopes, , , and . These do not pose a significant SER risk due to their low activity. Since all other isotopes generate detectable alpha-flux there will be no false-negatives (obtaining a background-level alpha-counting result when in fact an actual non-zero surface contamination of alpha-emitters is present). At the other extreme, for wafers with the only a single particle of alpha-emitting contamination on their surfaces, two of the non-detectable radioisotopes ( and ) would generate a problematic alpha-flux in a single chip. Assuming a 0.5 chip, the single particle the SER would be 10–15 times larger than chips with no contamination (assuming that the packaging met the ULA standard). Obviously if we assume a smaller chip area the SER for that chip becomes even larger, while the fraction of chips affected decreases since there are more chips per wafer. It is unlikely that the natural dispersion processes and clean-room filtration would act selectively on the airborne contamination in terms of separating or accumulating
Given the lack of concrete alpha-particle activity and dispersion data from the Fukushima-Daiichi plant at the time of the accident and without a detailed model of air infiltration into the clean room over time after the accident, it is impossible to create a quantitative assessment of contamination levels in the manufacturing sites. We, therefore, focused our effort on trying to directly quantify the actual level of contamination, if any, found on silicon wafers themselves. To this end, a number of silicon wafers were obtained from a manufacturing site at Mihomura, approximately 160 km south by south-west of the Fukushima Daiichi plant, and from a manufacturing site at Aizuwakamatsu, about 100 km west of the nuclear power plant. In all, a set of eight 200 mm wafers exposed to the clean-room air for several weeks after the earthquake (during the ensuing recovery and clean-up), was obtained from each of the two facilities. While air filters and positive pressure in the clean-room would likely eliminate the risk of any contamination prior to the earthquake, these wafers could have been exposed to contamination infiltration after the power failure shut-off the air filtration system and/or later during the extensive clean-up activities. In both cases these were fully-processed wafers undergoing electrical test when the earthquake occurred. The long accumulated exposure time of several weeks on the 2500 of the total exposed wafer surface area ensures that uranium, plutonium, or other radioactive airborne contamination would have adequate opportunity to be deposited (under normal test conditions these wafers would be exposed to clean-room air for several minutes, thus the multiple week exposure represents a significant over-exposure as compared with the actual production process). The wafers were not cleaned in any way but were placed in air-tight cassettes that remained sealed until they were opened in the clean room with the alpha-counting characterization equipment in Dallas, Texas. A control group of eight 200 mm wafers was also obtained from each of the two manufacturing sites. These wafers were in the same areas but were in air-tight cassette boxes at the time of the Earthquake and subsequent clean-up activities so they were expected to have levels of alpha-emission below the detection limits. The alpha-counting characterization was done on an Alpha Sciences Model 4950 gas proportional counter able to run eight 200 mm wafers at a time. The unit detects radiation by measuring the amount of counting gas ionized between two electrodes by the passage of an alpha-particle emitted from samples placed within 2 mm of the detector’s thin Mylar® window. The anode of the detector is comprised of a fine grid of wires to ensure that the electric field close to the grid is large enough to cause gas multiplication, thereby, enhancing the original signal charge. As its name implies, the output pulse is proportional to
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the number of ions emitted from the samples and reaching the counting chamber. The energy output of the detector was set to discriminate events below 1 MeV (the discriminator was calibrated by the manufacturer), greatly reducing the number of unwanted beta-particle detections. Ultra-pure P-10 counting (90% argon 10% methane) gas was used and a count time of 168 hours (1 week) was utilized for each of the four samples and the intervening background runs. Testing, analysis, and reporting were done according to the recently released JEDEC JESD221 test standard [50]. The limit-of-detection (LOD) is:
TABLE IV ALPHA COUNTING RESULTS
(13) where is the number of gross counts obtained from the sample, is the number of background counts, and and are the sample and background count times respectively. is the sample area, and is the detector efficiency (a geometrical consideration). The coefficient is a factor based on the desired confidence interval to be used. For the 90% confidence interval that we use for this analysis, standard deviations. The LOD represents the lowest activity that can be detected by the experiment. The lower the LOD, the more sensitive the test is to alpha-particle emissivity from the wafers. The fact that it is based on the standard deviation makes sense in that if one measured a zero-emission sample, if the measurement were deterministic, then one would uniquely find the gross count and background counts to be the same (and thus the raw alpha emissivity would be uniquely zero). Since the measurements are statistical in nature, with the same zero-emission samples, one would expect the gross count to be higher, the same as, or lower than the background count. While a negative raw emissivity maybe counter-intuitive, this will occur anytime that the gross count is less than the background count and is not unusual for zero-emission samples. It is an expected result (provided they are within one or two standard deviations of the background), occurring roughly 50% of the time when testing low emission samples. Seven 168-hour alpha-counting runs were performed over a period of two months. Gross background of the trays and of the chamber alone with no trays was similar at and counts per 168 hours. Our historical gross background count for 168 hours for this detector with trays had been counts over the last 9 years of service. Thus the current system demonstrated a sizable background contamination issue from both tray and chamber (this detector sat unused in the clean-room for nearly two years and the higher-than-normal background may be the result of accumulated radon activity). Before sending the detector back to the vendor for cleaning, however, it was apparent that the background was decreased by the presence of the wafer samples (the wafers effectively shielding of the tray surface). It was decided to use runs with the unexposed wafers as the background for the measurements (processed wafers have been measured numerous times and have always been below the detection limits of this equipment). The results are summarized in Table IV. The calculated alpha emissivity of Mihomura samples was 1.2 standard deviations above zero while that
of the Aizuwakamatsu samples was 1.6 standard deviations below zero. Even with the control wafers in place blocking a portion of the tray background, the LOD was not as low as it had been in the past (an LOD of has been reported for similar equipment [51] and over a 9-year history our measurements indicated an LOD of at 90% confidence). The “exposed” wafer samples exhibited activity that was less than or equal to an LOD of 0.00025 using a 90% confidence interval. Thus, at most, the exposed wafer’s alpha emission was eight times lower than the ULA specification, indicative that no significant alpha-emitting contamination was incorporated on the wafers. A second set of alpha-counting measurements on the same samples is planned as confirmation once the alpha-counter is verified to be operating at the expected background levels. With the expected LOD of approximately 0.00015 , a null result would indicate the wafers had alpha-particle emission at least 13 times lower than ULA materials. IV. CONCLUSION We have given some general arguments explaining why it is unlikely that high concentrations of alpha-emitting contaminants ventured far from the Fukushima-Daiichi site. An analysis of EPA air filter measurements revealed that extremely low, but detectable, levels of alpha-emitting contaminants did, indeed, escape and were borne thousands of kilometers eastward by wind action. We also reviewed later TEPCO reports confirming that low-levels of alpha contamination related to the accident were released. Due to the complexity of modeling atmospheric dispersion of contamination and to the paucity of reliable measurements taken immediately after the disaster, it is
BAUMANN: DETERMINING THE IMPACT OF ALPHA-PARTICLE-EMITTING CONTAMINATION FROM THE FUKUSHIMA-DAIICHI DISASTER
impossible to make a quantitative estimate of local concentrations of alpha-emitters in the air in the hours and days after their release. Based on reports of “typical” uranium-oxide particulate sizes and clean-room filter specifications, we have shown that all but the smallest fraction of these particles would be captured before entering the clean-rooms. We have made estimates of the maximal alpha-particle activity based on an assumption of particle size, composition, and type of isotope that could have infiltrated the clean-room. Finally, we summarize the first alpha-counting measurements of wafers from two Japanese manufacturing sites exposed to the atmosphere during and after the Fukushima-Daiichi accident and demonstrate that these are free of any detectable alpha activity down to a detection limit of . This limit of detection was 8 times LOWER than the current ULA standard specified to minimize alpha-particle-induced SER. These results imply that, at least at these two sites, no significant level of alpha-emitting contamination infiltrated the manufacturing process and that the impact to the soft error reliability performance of devices manufactured at these sites is negligible. ACKNOWLEDGMENT The author would like to thank the Texas Instruments, Japan management, finance, and engineering staff, particularly M. Shingo, S. Nakayama, Y. Koizumi, H. Wada, and J. Karube for having secured and sent wafers for this evaluation despite the daunting task of getting production back online after the earthquake. Thanks also to P. Clancy at Air Liquide for doing the alpha-counting study, and to M. Chisholm, T. Jesper, and V. Zhu for helping to connect this author with the right people in Japan. REFERENCES [1] “Fukushima Daiichi Nuclear Power Plant” Wikipedia [Online]. Available: http://en.wikipedia.org/wiki/Fukushima_Daiichi_Nuclear _Power_Plant [2] “Status of the Nuclear Reactors at the Fukushima Daiichi Power Plant,” New York Times (Online)-Asia Pacific, 2011. [3] J. Buongiorno, R. Ballinger, M. Driscoll, B. Forget, C. Forsberg, M. Golay, M. Kazimi, N. Todreas, and J. Yanch, “Technical lessons learned from the Fukushima-Daiichi accident and possible corrective actions for the nuclear industry: An initial evaluation,” MIT-Nucl. Sci. Publ. Tech. Rep.-025, pp. 5–5, May 2011. [4] Ibid, rev. 1 2011. [5] J. Boyd, “Shutdown of Fukushima reactors is ahead of schedule,” IEEE Spectrum, vol. 48, no. 11, pp. 16–17, Nov. 2011. [6] R. Baumann, “Radiation-Induced soft errors in advanced semiconductor technologies,” IEEE Trans. Device Mater. Rel., vol. 5, no. 3, pp. 305–316, Sep. 2005. [7] T. May and M. Woods, “A new physical mechanism for soft error in dynamic memories,” in IEEE Proc. 16th Int. Reliability Physics Symp. (IRPS), Apr. 1978, pp. 33–40. [8] R. Baumann, “Soft errors in advanced semiconductor devices-part I: The three radiation sources,” IEEE Trans. Device Mater. Rel., vol. 1, no. 1, pp. 17–22, Mar. 2001. [9] J. Wilkinson and S. Hareland, “A cautionary tale of soft errors induced by SRAM packaging materials,” IEEE Trans. Device Mater. Rel., vol. 5, no. 3, pp. 428–433, 2005. [10] M. Gedion, F. Wrobel, F. Saigne, and R. D. Schrimpf, “Uranium and thorium contribution to soft error rate in advanced technologies,” IEEE Trans. Nucl. Sci., vol. 58, no. 3, pt. 2, pp. 1098–1103, Jun. 2011. [11] “EPA RadNet Air Filter and Air Cartridge Results,” [Online]. Available: http://iaspub.epa.gov/enviro/erams_query_v2.simple_query
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[48] G. Strasser, H. P. Bader, and M. E. Bader, “Reduction of particle contamination by controlled venting and pumping of vacuum loadlocks,” J. Vac. Sci. Technol. A, vol. 8, no. 6, pp. 4092–4097, Nov. 1990. [49] J. Jernström, “Development of Analytical Techniques for Studies on Dispersion of Actinides in the Environment and Characterization of Environmental Radioactive Particles,” in Faculty of Sci. U. Helsinki, Nov. 10th, 2006, pp. 11–11. [50] Alpha Radiation Measurement in Electronic Materials, JEDEC Test Standard No. 221, May 2011. [51] M. Gordon, D. Heidel, K. Rodbell, B. Dwyer-McNally, and W. Warburton, “An evaluation of an ultralow background alpha-particle detector,” IEEE Trans. Nucl. Sci., vol. 56, no. 6, pt. 1, pp. 3381–3386, Dec. 2009.