Nanotechnology is playing an increasinglyimportant role in the development of sensors.Biosensors represent anespecially excitingoppor-tunity for high-impact applications benefitingfrom “nano” attributes. A biosensor is a devicethat combines a biological recognition element
with a physical or chemical transducer to detecta biological analyte. In general, a biosensor con-sists of three components: the biological recogni-tion element, the transducer, and signal proces-sing electronics. Nanomaterials can contributein either thebio-recognition element or the trans-ducer, or both, of a biosensor. The effective bio-recognition area, i.e. the area actually interacting
Research SectionIdentifying the emerging roles of nanoparti-cles in biosensors
Lu Huang*, Zhengchun Peng**, Ying Guo*** andAlan L. Porter****
This paper profiles R&Don the applicationofnanoparticles in biosensors andexplo-res potential application development pathways. The analysis uses a dataset ofnanotechnology publication records for the time period 2001 through 2008 (partyear) extracted from the Science Citation Index. It focuses on emergent researchactivities in the most recent years. Bibliometric analyses are employed to ascer-tain R&D trends and research networks for key biosensors. Growthmodels are fitto forecast the technological trend for nanoparticle-enhanced biosensor researchactivity. In addition, a combination of quantity (publication) and quality (citati-on) analysis for nanoparticle-enhanced biosensors helps position the leading coun-tries in this research field. Science overlaymapping shows different emphases ofnanoparticle-enhanced biosensor research between theUS andChina, the leadingcountries. Recent studies suggest that nano-enhanced biosensors show promisefor gains in stability, sensitivity, selectivity, and accuracy - for both direct and indi-rect detection. This paper demonstrates how bibliometric analyses can help anti-cipate emerging technology development and application potential.
* School of Management and Economics, Beijing Institute of Technology, 5 South ZhongguancunStreet, Haidian District, Beijing, 100081, P.R.China;School of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332-0345, USA,[email protected]
** School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0405, USAInstitute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332,USA , [email protected]
*** School of Management and Economics, Beijing Institute of Technology, 5 South ZhongguancunStreet, Haidian District, Beijing, 100081, P.R.ChinaSchool of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332-0345, USA,[email protected]
****Technology Policy and Assessment Center, School of Public Policy, Georgia Institute of Technology,Atlanta, GA 30332-0345, USA, Search Technology, Inc., [email protected]
Identifying the emerging roles of nanoparticles in biosensors
15
with the analyte, is one of the important para-meters that determines the sensitivity of a bio-sensor. Nanomaterials, especially nanoparticles,provideapromisingway to increase thebio-recog-nition area (Khanna,2008),because thehigh sur-face to volume ratio of nanoparticles provides alargenumberof sites available formolecular inter-actions (Kim et al., 2004).
In recent years, a wide variety of nanoparti-cles with different properties have found broadapplication in biosensors. Because of their smallphysical size, nanoparticles present unique che-mical, physical, and electronic properties that aredifferent from those of bulkmaterials (Luo et al.,2006), and improved and new biosensors aredesigned benefiting from these novel attributes.Functional nanoparticles bound to biologicalmolecules (e.g. peptides, proteins, nucleic acids)havebeendeveloped foruse inbiosensors todetectand amplify various (e.g. electronic, optical, andmagnetic) signals (Chen, 2004). Most recent stu-dies show that biosensors composedwithnanop-articles do take on rapid, sensitive, accurate, andstablemeasurements,which offers excitingnewopportunities for the development of biosensingcapabilities. Nowadays, nanoparticle-enhancedbiosensors show significant development.Researchers tend to integrate nanoparticles intothematerials used for biosensor construction inorder to improve the performance of the systemin both existing and potential sensing applicati-ons.
Analyzing R&Ddevelopment trends and rela-tionships for nano-enhancedbiosensors canhelpbusiness decision-makers take best advantage ofemerging opportunities (Porter et al., 1991). Alt-hough nanoparticle-enhanced biosensors havebeen researched and affirmed to provide remar-kable functional improvements, fewstudies havetried to systematically characterize the roles ofnanoparticles in enhancing biosensor functiona-lity (Shipway,2008). Our researchquestionsaboutnano-enhanced biosensors R&D are:
What are the R&D trends?Which countries lead the nano-enhanced bio-sensors R&D?Which fields are engaged in this research?What are the emerging roles of nanoparticlesin biosensors?Which nanoparticles offer the greatest poten-tial for commercial applications?
Approach and data
We employ bibliometric analyses to ascertainR&D trends and research networks for nanopar-
ticle-enhanced biosensors. Bibliometric analysisis a set of tools for extracting information fromlarge databases looking for patterns and explai-ned reasons for apparently unstructured beha-vior (Daim,2005). Bibliometric analysis can playimportant roles in pursuing chemical businessopportunities fromthree aspects.The first is tech-nology forecasting. After getting historical datafromauthoritativedatabases,we canadjust thesebibliometric data using an S-curve as away to fitthe technological growth process (Daim, 2006),analyzing research trends and identifying emer-ging areas of technology. Secondly, bibliometricmethods can help determine the technology lifecycle position and gauge itsmaturity level.Mar-tino (2003) presents bibliometric analysis divi-ding the data in five categories. As he described,when the technological development is at thebasic research stage, the Science Citation Index(SCI) nicely represents that literature. When thetechnological development reaches the appliedresearch stage, the technological literature iswellrepresented by the Engineering Index (EI) litera-ture (for certain technologies). When develop-ment reaches the experimental developmentphase, patent documentation is a good reflecti-on. When the development reaches the applica-tion stage, Newspaper Abstracts depict activitypatterns. At last, bibliometrics can investigateinformation through the use of different indica-tors such as publications, cited references, occur-rences of words, phrases, citations, co-citations,authorship and related characteristics that mayextract hiddenpatterns fromstructureddata,pre-senting the whole picture of research networksand relationships (Watts et al., 2001).The datasets used in these bibliometric studiescome from global nanotechnology publicationsfor the timeperiod 2001 through 2008 (part year)extracted from different databases: SCI, Inspec,Compendex, and Factiva. This paper focuses onSCI data for intensive study to capture the emer-gent research activities, especially those promi-nent in the most recent 4 years. The SCI datasetof publicationsdrawsupon thedefinitionofnano-technology and thedata-cleaningmethods deve-loped by a Georgia Tech group. Our basic nanosearch locates abstract records containing“nano*”or anyof 7modular termsets,as discussedbyPor-ter et al. (2008). Within the resulting dataset (ofsome 500,000 publication abstracts), we thensearch for those specifically discussing “biosen-sors,” and “nanoparticles”. Besides these basicsearch terms, we add other terms like specificcategories of biosensor (such as glucose, choles-terol, enzyme, DNA, genome, hydrogen-peroxi-de, alcohol,nitrate,amino acid,protein chip,DNA
Lu Huang, Zhengchun Peng, Ying Guo, Alan L. Porter
array, immunoassay, sandwich assay, competiti-ve assay,etc.) and variants of nanoparticles (suchasAg,Au,Pt,Cds,Pbs,ZnO,SiO2,polystyrene,quan-tum dots, metal, semiconductor, polymer, etc.).Using this approach, 1,400 publication recordswere drawn from SCI to create a dataset for the2001-2008 (mid-year) time period. At the sametime, we also set up two other datasets drawnfrom the Inspec & Compendex databases with1,715 records, and from Factiva with 489 records.However, the searchmethod for these later data-sets is much simpler than that used for the SCIdataset, just using basic search terms of“biosen-sor” and “nanoparticles”.
Results
TTrreenndd aannaallyysseess
We begin by showing a trend line based onthe cumulative number of publications by eachof the three datasets (Figure 1). We are trying tofind out the development status of nanoparticle-enhanced biosensors. The sharp upward trend inarticles relating nanoparticles to biosensors showstheir increasingly important role. Examining thesethree growth curves, we find that 2004 is the key
point for both the SCI and Inspec & Compendexdata series. At about that time, the basic researchand the more applied research on nanoparticle-enhanced biosensors accelerated into a steeperrate of growth. In comparison, the publicationcounts of Factiva, reflecting broader business andgeneral public attention, started to increase moresteeply in 2007. This suggests that the popularbusiness application of nanoparticles in biosen-sors lags basic and applied research by aboutthree years.
What is likely to happen in the near future?The last data point for the INSP/Compendex seriesis estimated because our data reflect only abouthalf of the expected complete 2008 tally. Thatsaid, we still note that this point indicates a pos-sible slight decline in applied research on thetopic. On the other hand, the increasing rate ofpublications for SCI in the most recent two yearssuggests that a further expansion of applied R&Dcould be anticipated. So, those interested in tra-cking this emerging technology would want tomonitor developments quite closely in the comingyears to ascertain the development pattern.
In order to gain a richer perspective on thetechnology life cycle position and maturity levelfor nanoparticle-enhanced biosensors, we extra-
Figure 1 Cumulative publications of nanoparticles applications in biosensor by database1
1) Databases used: Science Citation Index, INSPEC&COMPENDEX, and Factiva, 2001-2008 (estimated). In order to get more accurate result for the comparison analysis for thesethree datasets, search terms for SCI in this chart are the same with the other two datasets with “nano*”,“biosensor” and “nanoparticle”.
Identifying the emerging roles of nanoparticles in biosensors
17
polate the R&D trends.2Figure 2 gives one result
of trend analyses of publications indexed by SCIthrough the year 2012. Bibliometric data can bemodeled using an S-curve as a way to fit the tech-nological growth process. Here, we choose a Gom-pertz Model to fit the data with a high R2 coeffi-cient of 0.99. It suggests that steep growth couldcontinue over the next few years. Similarly, trendanalyses for the INSPEC & Compendex datasetsalso follows an increasing trend over the next 4years (not shown here). According to the resultsof our trend extrapolation, we estimate that thereis still a long time, likely several years or longer,for basic and applied research on nanoparticle-enhanced biosensors to grow.
The evidence is strong that nanotechnologyhas recently become one of the most excitingforefront elements in biosensor R&D. In order toidentify the position of nanoparticle-enhancedbiosensors among all the nanomaterial-enhan-ced biosensors, this paper partitions the biblio-metric data. We separate the publication countsof nanoparticle-enhanced biosensors from thoseof any nanomaterial-enhanced biosensors. Wethen establish a ratio between these. The publi-cations of nanoparticle-enhanced biosensors areprimarily from the results of searching the terms,“nanoparticle” and “biosensors”. The publicati-ons of nanomaterial-enhanced biosensors comefrom the results of searching the term “nano*”with “biosensors”. Based on these bibliometricdata, we again seek to examine the trend and to
forecast the technological growth process ofnanoparticle-enhanced biosensors using suitab-le growth models. In Figure 3, a linear model isused to fit the ratio data from SCI for 2001 to 2008and gives another trend trajectory extended tothe year of 2012. Similarly, a linear model fits thedata from INSPEC/COMPENDEX quite well (notshown here). According to the results, we esti-mate that nanoparticle-enhanced biosensors havemore potential than other nanomaterial-enhan-ced biosensors in the next few years, because thevalue in the year 2012 is still smaller than the limitof “1.” However, to some extent we were concer-ned by the goodness of fit of the two trend ana-lyses, because the coefficients of determinationof these two models are not very high (0.78 and0.79, respectively).
Those coefficients just affirm the visual appea-rance – the fit of the line is not so strong in theearlier years; however, it is quite close in morerecent years.
As an emerging field, there has been muchinterest in the leading countries in research onnanoparticle-enhanced biosensors. This papernot only compares the numbers of publications,but also focuses on the quality and influence ofcountries in this research field. Citations, as mea-sured by the number of times a paper has been
Figure 1 Cumulative publications of nanoparticles applications in biosensor by database3
2) We show this only for the SCI data; in the text we mention the other R&D trends based on INSPEC/Compendex. The Factiva data don’t pertain to R&D, so we don’t analyzethem in this way to model the technology maturation.
3) The limit of Gompertz Model here is equal to 1,200, and Coeff Det. is equal to 0.99, which is higher than other models, such as Fisher-Pry Model and Exponential Model.
Lu Huang, Zhengchun Peng, Ying Guo, Alan L. Porter
18
hiwi
Stempel
cited, are used here to gauge the level of quality,or impact, of the publications of a country. [Thisis an imperfect measure, of course, but it is wide-ly accepted as a reasonable indicator that otherresearchers find worthwhile research knowled-ge therein (Van, 1988).] The particular analyticalmethod used in this paper focuses on the coun-try location of the affiliation of the first authorof the publication. The first author’s country isused to assign citation numbers to that country.This focus on the first author is designed to pre-clude duplicating citation counts.
Another method to be pointed out is that weemploy a simple aging practice based on dividingthe citations in a given year by the number ofyears of opportunity to be cited. This is becausecitations are difficult to evaluate over time. Ear-lier papers have more occasions to receive citati-ons than do more recent papers (Youtie et al.,2008). As for our dataset of SCI, the most recentyear is the mid-year of 2008; thus in 2001, papershave 6.5 years of opportunity to attract citationsrelative to the end-point of our dataset. So thenumber of citations to papers published in thatyear is divided by 6.5. Similarly, in 2002, the num-ber of citations should be divided by 5.5; the num-ber 2006 citations is divided by 1.5; and so forth.So, “aged citations” gives us a metric to help gaugechange in nations’ research publications impact
over time. Again, this is not a precision measu-re, but it provides for viable comparison.
In order to make results more robust, we com-bine the tallies for two-year periods. To reflectthe earlier time period, we add 2001 and 2002together, and compare with the correspondingnumber for 2005 and 2006 combined. We use2005-06 to allow a few years for papers to accruecitations. Figure 4 shows the results. A trend lineconnects the results for (2001 + 2002) to those for(2005 + 2006). We first consider location alongthe X axis, which reflects publication counts, andfind that, in the early time period, the USA is theleader, although the publication counts are modestwith 14. However, by the later period, China hastaken over the lead in publishing on nanoparti-cles in biosensors with 158. The Y axis of Figure 4shows the citations received by those papers,adjusted by the years available since publicationin which to be cited. Looking at the starting andthe ending points of the lines, we find the US washighest in 2001-02 citation intensity and itremains the leader in the 2005-06 period.
The steeper the slope of the line connectingthese two points, the greater the quality orienta-tion of the country has been increasing. FromFigure 4, we can find that the US has the steepestslope, suggesting that its nanoparticle-enhancedresearch receives the greatest attention by
Figure 3 Linear model adjust to ratio of nanoparticle-enhanced biosensor SCI data4
2013
.4
.3
.2
.5
.6
.7
.8
.9
.
4) The value of the points in the chart represents the ratio of publication counts of nanoparticle-enhanced biosensors divided by publications counts of any nanomaterial-enhan-ced biosensors. The search terms of nanoparticle-enhanced biosensors are “biosensors” and “nanoparticle’; While search terms of nanomaterial-enhanced biosensors are “bio-sensors” and “nano*”.
Identifying the emerging roles of nanoparticles in biosensors
19
researchers. As noted, China is also a leading coun-try in research publication; here we see that Chi-nese publications also receive increasing citati-ons. Israel, Italy, and Japan have far fewer publi-cations and citations than does China (see theinsert of Figure 4). However, the steep slope oftheir lines relative to China suggests that theirpapers have relatively higher impact. Germany,Spain, and South Korea are also important play-ers in the research on nanoparticle-enhanced bio-sensors. So any competitive technical intelligence(“CTI”) endeavors would also want to monitortheir research initiatives.
“Nano” research is highly multidisciplinary(National Science and Technology Council, 1999;Eto, 2003; Loveridge et al., 2008; Roco, 2008; Por-ter and Youtie, under submission). That said, there
is considerable discourse as to which fields areimportantly involved and the extent to whichresearch knowledge is actively shared amongthem (Roco and Bainbridge, 2003; Meyer, 2006).We have found that visualizations of the researchfields involved help one gain perspective on theactivity.
We also examine the citations from a diffe-rent point of view. Most highly cited authors (top50) in our SCI dataset from 2001 through 2008are mapped via the help of VantagePoint soft-ware [see www.theVantagePoint.com] in Figure5. The size of the node reflects the number of cita-tions, and the strength of the links shown repre-sents the degree of association based on co-cita-tion (the extent to which papers reference bothof a pair of authors). It should be noticed that nolink between two nodes doesn’t mean zero co-citations, just fewer co-citations6. Proximity inthese Multi-Dimensional Scaling (MDS) mapsalso suggests relationship, but not as definitely
Figure 4 Number of aged citations of nanoparticles applications in biosensor in 2001 plus 2002 and 2005 plus 2006 relativto number of articles of nanoparticles applications in biosensor by first author.5
USA
China
Japan
Israel
Germany
Italy
South Korea
Spain
4020 60 80 1000 120 130 140 1500
50
100
150
200
250
300
350
Num
ber of Aged* Citations
Number of Articles Year donated by start and end points2001+20022005+2006
5) *Aged citations(AC) for countryi calculated as ACi=Cti/(Yn-Yt) where Cti=total number of citations for articles in target year for countryi; Yn=most recent year in dataset (2008,mid-year); and Yt=target year. For 2001, Yn-Yt=6.5; for 2002, Yn-Yt=5.5; for 2005, Yn-Yt=2.5; for 2006, Yn-Yt=1.5. Country designated by article first author. Database used: ScienceCitation Index.
6)The threshold of the MDS is set to 0.25 here. So, absence of a connecting link means that few (not necessarily zero) papers cite both researchers. The nature of this “co-citation”sampling means that not all prominent researchers will likely be located.
Lu Huang, Zhengchun Peng, Ying Guo, Alan L. Porter
Identifying the emerging roles of nanoparticles in biosensors
21
as do the path-erasing based links (lines). Loca-tion along the axes has no inherent meaning.
The clustering seen in Figure 5 suggests pos-sible concentrations in the cited literature. Weexamined in which journals the different highlyco-cited authors published most heavily. We thenassociate those journals with their SCI subjectcategories, noting four particularly prominentones:
CChheemmiissttrryy,, AAnnaallyyttiiccaall:: with Wang J (ArizonaState Univ) as the centrally-cited authorMMaatteerriiaallss SScciieennccee,, MMuullttiiddiisscciipplliinnaarryy:: a group atNorthwestern University, including Mirkin CA,Yonzon CR, Malinsky MD , and Haes AJEElleeccttrroocchheemmiissttrryy:: Bard AJ (University of Texas,Austin); Liu SQ (Nanjing University); Rusling JF(University of Connecticut); Lvov Y (LouisianaTech Univ)BBiiootteecchhnnoollooggyy:: Willner I and Xiao Y (The Heb-rew Univ of Jerusalem); Liu GD (Pacific North-west National Lab); Mirkin CA (NorthwesternUniversity); Nie SM and Bao G (Georgia Insti-tute of Technology).
Science mapping is emerging as a specialtyin its own right (Chen, 2003; Boyack et al., 2005).We have been developing a “science overlay map-ping” approach to locate particular research setson a base science map (Leydesdorff and Rafols,forthcoming; Rafols and Meyer, forthcoming).This approach uses the Subject Categories thatWeb of Science assigns to journals. For a set ofpublications indexed by Web of Science (in thiscase, by SCI, which is part of Web of Science), welocate that research by the journals in which itappears. Figures 6 and 7 do that for subsets ofthe “nanoparticles and biosensors” researchpapers, which are based on SCI dataset for 2005through part-year 2008 in order to focus on theemergent characters of recent 4 years. The basemap reflects the 175 Subject Categories shown bythe background intersecting arcs among them.The Subject Categories are then grouped into“macro-disciplines” using a form of factor analy-sis (Principal Components Analysis) based on thedegree of co-citation of the Subject Categories ina large sample of articles indexed by Web of Sci-ence (Porter and Rafols, forthcoming). Thosemacro-disciplines become the labels in the figu-re. The “nanoparticles in biosensors” researchconcentrations appear as nodes on this map.
These science overlay maps particularly helpus answer two questions: which research fieldsare engaged? And how similar is the approach ofdifferent players? In this case, we choose to focuson national comparisons. We only show two of
the leading countries active in this research arena– the US and China. Some observations include:
Nanoparticles in Biosensors research involvesa very extensive range of research fieldsThat research is centered in Materials Sciencesand ChemistryThe research also involves a number of Biome-dical Sciences
The Chinese and American research patternsare largely similar – both engage the same broadswath of research fields. But Chinese and Ameri-can research emphases are not identical (Table 1shows significant variations, particularly in che-mical specialties).
Table 1 tabulates the leading Subject Catego-ries represented by Chinese and American publi-cations in this area for 2005-08. On the left, onesees the number of publications associated witheach Subject Category. At the top is the numberof publications by China and by the USA. The per-centages are taken of the national totals. So, forexample, 57% of China’s articles indexed by SCIfor this search set (nanoparticles and biosensors)are associated with Analytical Chemistry jour-nals and another 40% are linked to Electroche-mistry [We note that the column percentagestotal over 100%; that is because Web of Scienceassociates some journals (~39%) with more thanone Subject Category.]. So, the Chinese research,in comparison to the American, emphasizes Che-mistry more heavily. Conversely, notice that Ame-rican articles are considerably more apt to entailPhysics sub-areas than are the Chinese. Discer-ning such differences (and pursuing their impli-cations) can be vital to proactive business manage-ment.
Reviewing recent studies, we find that manykinds of nanoparticles have been widely used inbiosensors. Here, we group nanoparticles intofour families - metal nanoparticles, semiconductornanoparticles, magnetic nanoparticles, and allother types (including polymer nanoparticles,silica nanoparticles, and so on). All these nanop-articles can be used in biosensors, as long as theparticle surface is modified with specific functio-nal groups. Since different families of nanopar-ticles, and sometimes nanoparticles of the samefamily, can play different roles in biosensor sys-tems, we attempt to identify the most represen-tative properties taken on by different nanopar-ticles, either in a group or individually. In Figure
Figure 7 Locating China “Nanoparticles in Biosensors” research over a base map of science
Lu Huang, Zhengchun Peng, Ying Guo, Alan L. Porter
24
8, we summarize the detailed ties from the mostfrequently researched nanoparticles to their uni-que properties, and to their possible enhance-ment of biosensing. Figure 8 reveals the extre-mely promising prospects of specific nanoparti-cles in designing new and improved biosensorsby using their unique chemical and physical pro-perties.
Our search results show that biosensors com-posed with nanoparticles do purport to provideadvantages in their sensitivity, stability, accura-cy, selectivity, and so on. For instance, improvedaccuracy and stability of biosensors were demons-trated by using nanoparticles as the solid sup-port and carrier of biological components, suchas proteins and DNA (Lynch et al., 2007). Thisimprovement benefits from the small physicalsize of nanoparticles, which minimizes the con-formational and activity change of the biologi-cal components. In addition, biosensors withimproved detection limits and selectivity havebeen developed by making use of the exceptio-nal catalytic effect of Pt and Au nanoparticles(Luo et al., 2006). Furthermore, biosensors capa-ble of highly sensitive and stable detection ofmultiple cancer markers were enabled by the high
fluorescent quantum yield and enhanced photo-stability of semiconductor nanoparticles such asCdS and CdSe quantum dots (Medintz et al., 2005).We mention that many polymer nanoparticles(e.g. polystyrene) offer not only direct bioconju-gation processes, but also promising biocompa-tibility. Therefore, we expect the polymer fami-ly of nanoparticles to play increasing roles in bio-sensing applications.
An important trend in current research is usingcomposite nanoparticles with combined proper-ties of polymer, semiconductor, and metal nanop-articles for multifunctional applications. Com-posite nanoparticles are mainly in the form ofcore-shell structures. Heavily researched onesinclude silver-polystyrene particles (Wu et al.,2003) and magnetite-dextran particles (Pank-hurst et al., 2003).
In terms of percentage of the aforementionedfour kinds (metal, semiconductor, magnetic, poly-mer) of nanoparticles, metal nanoparticles domi-nate (Figure 9). Before 2002, only metal and mag-netic nanoparticles were investigated for biosen-sor enhancement. Although semiconductor andpolymer nanoparticles were employed to enhan-ce the functions of biosensor systems later, these
Lu Huang, Zhengchun Peng, Ying Guo, Alan L. Porter
26
three kinds of nanoparticles are still relativelyminor components of this research domain. Toprobe a level deeper, we identified that metalnanoparticles constitute a big family, includingPt, Ag, Au, Pd, Cu nanoparticles and so on. Thiscould be a major reason for its high profile innanoparticle-enhanced biosensors. Turning tothe publications counts of typical metal nanop-articles applied in biosensors (Figure 10), we con-clude that gold (Au) nanoparticles are the mostfrequently used. The gold nanoparticles publica-tions count has kept increasing from 2001 to 2008.However, the other two metal nanoparticles, pla-tinum and silver, are only becoming popular inrecent years. Noticeably, platinum nanoparticlesappear to be an emerging nanoparticle which isincreasingly popular since 2007 in constructingbiosensors. Due to high surface free energy, goldnanoparticles can adsorb biomolecules stronglyand play an important role in the immobilizati-on of biomolecules for biosensor construction (Caiet al., 2001). In addition, the combination of thecatalytic properties of gold nanoparticles withthe specificity of biomolecular interactions canresult in the construction of highly sensitive andselective sensor systems (Xian et al., 2005). Fur-thermore, gold nanoparticles have been shownintegrated with carbon nanotubes to form nano-
hybrids to modify biosensors with improved indi-rect detection of enzymes (Cui et al., 2008).
As for the prominent research fields of nanop-article-enhanced biosensors, we selected five kindsof biosensors based on the biological componentsused for bio-recognition in the sensing scheme.In order to capture the character of this research,we focus on their publications numbers in ourSCI dataset during most recent 4 years (2005through 2008 part year). Figure 11 shows that thepublications counts of these 5 nanoparticle-enhan-ced biosensors are increasing over the years. Enzy-me-based biosensors are at the top followed byimmunosensors, chemical substance-based bio-sensors, genome sensors, and organism and cell-based biosensors.
We present these data to suggest to techno-logy analysts and managers the potential to gene-rate valuable CTI. Again, we reiterate that enga-gement of technical experts is essential to iden-tify the nuances and implications of such empi-rical information.
Discussion
This paper has examined R&D on nanoparti-cle-enhanced biosensors and employed biblio-metric analyses as a means to help forecast R&D
Figure 10 Cumulative publications of 3 typical metal nanoparticles applied inbiosensors. Databases used: Science Citation Index, 2001-2008 (estimated).
0
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Identifying the emerging roles of nanoparticles in biosensors
27
trends and identify the emerging nanoparticleroles in biosensors. According to the results ofthe trend growth models, the R&D activities appe-ar likely to increase over the next few years.Moreover, nanoparticles show greater potentialto improve the performance of biosensors thando other nanomaterials.
In addition, a combination of quantity (publi-cation) and quality (citation) analysis for nanop-article-enhanced biosensors helps position theleading countries in this research field. Scienceoverlay mapping helps us see the different empha-ses of nanoparticle-enhanced biosensors researchbetween the US and China. We noted the poten-tial complementarity in Chinese chemistry andUS physics emphases in this R&D. R&D mana-gers might well want to extend such analyses toprofile the research emphases of particular organi-zations. By identifying particular specializationsand research strengths, they can identify poten-tial technology development partners. Suchresearch outreach is becoming increasingly essen-tial as “Open Innovation” becomes increasinglyimportant (Chesbrough, 2006; Huston and Sak-
kab, 2006). This is especially so in today’s diffi-cult economy.
Nanoparticle-enhanced biosensors present ahighly cross-disciplinary research arena. This sug-gests value in exploring the relationships furt-her. Is research concentrated in particular Sub-ject Categories being fully utilized by researchersin other domains? What is the cooperativeresearch network? For instance, are there confe-rences to bring together the biomedicalresearchers with the chemists, the materials scien-tists, and the physicists, to share cutting edgeknowledge that could come to bear on nano-enhancement of various biosensors? For the tech-nology manager, what can you do to facilitatecross-field and cross-institutional researchknowledge transfer? Our perspective, based onthese bibliometric analyses, is that this field isripe for stimulated research knowledge exchange.The variety of nanoparticles, multiple functions,and diverse applications suggest that R&D mana-gers should actively reach out and exploit cross-area results.
Figure 11 Cumulative publications of nanoparticle-enhanced biosensors in recent 4 years Databases used: Science Citation Index, 2005-2008 part year
2005 2006 2007 2008
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Immunosensor
Genome sensor
Cell-based biosensor
Enzyme-based sensor
Chemical substance-based biosensor
Lu Huang, Zhengchun Peng, Ying Guo, Alan L. Porter
28
biosensors to improve the performance of exis-ting and potential sensing applications. We ana-lyzed the increasing focus on specific functionsof nanoparticles and their ties to promising enhan-cement in biosensors. These specific functionsinclude catalytic, plasma-optical, quantum, elect-ro/chemiluminescent, and superparamagneticeffects. One type of nanoparticle can play diffe-rent roles in different biosensor systems, and itcan also play more than one role in the same bio-sensor system. Different types of nanoparticle-enhanced biosensors analyzed include enzyme-based biosensors, immunosensors, chemical sub-stance-based biosensors, genome sensors, andcell-based biosensors. We identified gold nanop-articles as especially promising for biosensorenhancement and probed their applications invarious biosensors using specific or combinedfunctions they possess. A future course of inves-tigation would involve developing enhancedmethods for discerning special functions of dif-ferent types of nanoparticles in biosensor sys-tems. Our observation that “nano in biosensors”research has become increasingly specific – interms of particular materials and particularfunctional gains – is a key indicator that this tech-nology is “emerging” (Watts and Porter, 1997).When research shifts from the general to the spe-cific, this is a key benchmark of maturation.
In closing, we note an important caution.Before basing business decisions on such researchprofiling and forecasting, one would want toobtain expert opinions by researchers and busi-ness people conversant with the topic (Two seniorresearchers and several others have reviewed andenhanced our analyses). Experts can help buildupon these results to suggest additional linkagesto related research domains to explore. Expertscan also help refine the searches and refocus theinquiry to better understand patterns in specificaspects of this emerging technology.
Acknowledgements
This research was undertaken at Georgia Tech,supported by the National Science Foundation(Award Nos. 0531194 and 0830207); Beijing Insti-tute of Technology, supported by the NationalScience Foundation of China (Award No.70639001). Many of the findings in this paperwere presented in the 18th International Confe-rence on Management of Technology (IAMOT).The authors also appreciate the valuable sugges-tions from Prof. Lawrence Bottomley in Chemis-try and Prof. Prof. Oliver Brand in Electrical Engi-neering (both at Georgia Tech).
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