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National Science Foundation (U.S.) (CA No. EEC-1041895)

Space conditioning, and cooling in particular, is a key factor in human productivity and well-being across the globe. During the 21st century, global cooling demand is expected to grow significantly due to the increase in wealth and population in sunny nations across the globe and the advance of global warming. The same locations that see high demand for cooling are also ideal for electricity generation via photovoltaics (PV). Despite the apparent synergy between cooling demand and PV generation, the potential of the cooling sector to sustain PV generation has not been assessed on a global scale. Here, we perform a global assessment of increased PV electricity adoption enabled by the residential cooling sector during the 21st century. Already today, utilizing PV production for cooling could facilitate an additional installed PV capacity of approximately 540 GW, more than the global PV capacity of today. Using established scenarios of population and income growth, as well as accounting for future global warming, we further project that the global residential cooling sector could sustain an added PV capacity between 20–200 GW each year for most of the 21st century, on par with the current global manufacturing capacity of 100 GW. Furthermore, we find that without storage, PV could directly power approximately 50% of cooling demand, and that this fraction is set to increase from 49% to 56% during the 21st century, as cooling demand grows in locations where PV and cooling have a higher synergy. With this geographic shift in demand, the potential of distributed storage also grows. We simulate that with a 1 m3 water-based latent thermal storage per household, the fraction of cooling demand met with PV would increase from 55% to 70% during the century. These results show that the synergy between cooling and PV is notable and could significantly accelerate the growth of the global PV industry., NSF (Grant 122374)

Measuring the impact of marketing is essential for improving its performance and justifying marketing decisions to top management. However, marketers often struggle with it, even though various methods are available to them in the literature. A good starting point for marketers is the most popular method, marketing mix modelling (MMM), that is a linear regression fitted in sales and marketing data. Yet, it often suffers from various downsides, such as lack of data, deficient model forms and biases. Researchers have consequently suggested improving it through better data, better models and model validation. However, researchers mainly discuss these areas as a way to improve model accuracy rather than to widen the scope of analysis. Improving modelling granularity would enable marketers to analyse performance on lower levels and broaden their discussion on improvements. Higher granularity could particularly support the retail industry, where marketing is a complex operation because of wide product ranges, geographical reaches and customer bases. Consequently, the goal of the thesis was to analyse how the typical MMM is limited, how model developers could adjust it to meet the needs of the retail marketing environment and what impacts such adjustments would have. We conducted the study through a combination of a literature review and a simulation. The literature review discovered that the typical MMM is limited in use in the retail environment, mainly due to its low granularity that hides the information about the structure of performance. Other flaws include, e.g., the lack of modelling in retail-specific effects, such as stock-up, and the lack of model validation. The most significant opportunity arises from increasing granularity in at least three dimensions: frequency, geography and product hierarchy. Other improvements, in turn, arise from improving accuracy through comprehensive modelling and model validation through simulation. The simulation studied the impact, Markkinoinnin vaikutuksen mittaaminen on välttämätöntä markkinoinnin tehostamiseksi ja markkinointipäätösten perustelemiseksi ylimmälle johdolle. Siitä huolimatta, useat yritykset epäonnistuvat siinä. Mittaamista varten on kuitenkin kehitetty menetelmiä, joista yleisin on ns. markkinointi mix mallinnus (MMM). Se kuitenkin kärsii useista ongelmista, kuten epätäydellisistä ja testaamattomista malleista. Parannusalueita on kuitenkin tunnistettu kolmella osa-alueella: parempi data, paremmat mallit ja mallin validointi. Näitä osa-alueita kuitenkin pääsääntöisesti lähestytään mallin tarkkuuden kehittämisen kannalta eikä analyysimahdollisuuksien laajentamisen kannalta. Analyysien laajuutta olisi mahdollista puolestaan parantaa paremmalla datan tarkkuudella eli granulariteetilla. Parempi granulariteetti voisi erityisesti tukea jälleenmyyntialaa, jossa markkinointi on hyvin monimuotoista ja haastavaa hallita, mm. laajan tuotevalikoiman takia. Työn tarkoituksena onkin tutkia, kuinka perinteinen markkinointi mix mallinnus on rajoittunut, kuinka sitä voidaan kehittää jälleenmyyntialalle sopivammaksi ja mitä vaikutuksia parannuksilla olisi. Tutkimus toteutettiin kirjallisuuskatsauksen ja simulaationtutkimuksen yhdistelmänä. Kirjallisuuskatsauksessa havaittiin, että mallinnus on rajoittunut käyttömahdollisuuksissaan jälleenmyyntialalla pääsääntöisesti sen huonon granulariteetin takia, joka piilottaa informaation tehokkuuden rakenteesta. Lisäksi mm. jälleenmyyntialalla ominaisten ilmiöiden, kuten hamstraamisen, mittaaminen on puutteellista ja mallit kärsivät useista epätarkkuuksien lähteistä ja validoinnin puutteesta. Malleja olisi erityisesti mahdollista parantaa lisäämällä granulariteettia ainakin kolmessa dimensiossa: frekvenssi, alueellisuus ja tuotehierarkia. Toinen tärkeä kehitysalue on mallin tarkkuuden parantaminen mm. kattavan mallintamisen ja mallin validoinnista simuloinnilla. Kirjallisuuskatsauksen lisäksi tehty simulaatio tutki granulariteetin vaikutuksia markkinoinni

Control of detrimental metal impurities is crucial to silicon solar cell performance. Traditional silicon solar cell emitters are diffused in an infinite-source regime and are known to cause strong point defect segregation towards the emitter and thus enhance bulk minority carrier diffusion length. With the advent of ion-implantation and chemical vapor deposition (CVD) glasses, finite-source diffused emitters are attracting interest. This contribution aims to increase their adoption by elucidating the dominant gettering mechanisms present in finite-source diffused emitters. Our findings indicate that infinite-source diffusion is critical for effective segregation gettering, but that high enough surface phosphorus concentration can activate segregation gettering via finite-source diffusion as well. In the case of ion-implanted emitters, the traditional segregation gettering may be considerably enhanced by impurity precipitation in the implanted layer., United States. Department of Energy. Office of Basic Energy Sciences (Contract No. DE-AC02-06CH11357), National Science Foundation (U.S.) (CA No. EEC-1041895), Finnish Cultural Foundation, Fulbright-Technology Industries of Finland Grant, University of California, San Diego. Start Up Funds

An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe[subscript i]]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetically limited and bulk ([Fe[subscript i]]) predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time., National Science Foundation (U.S.), United States. Dept. of Energy (NSF CA No. EEC-1041895), Tekes (Agency) (project ‘‘PASSI’’ (project No. 2196/31/ 2011)), Academy of Finland (project ‘‘Low- Cost Photovoltaics.’’), German Federal Ministry for the Environment, Nature Conservation and Nuclear (research cluster ‘‘SolarWinS’’ (contract No. 0325270A-H)), Alexander von Humboldt-Stiftung (Feodor Lynen Postdoctoral Fellowship), Massachusetts Institute of Technology. Department of Mechanical Engineering (Peabody Visiting Professorship), Harvard University (Real Colegio Complutense, RCC Fellowship), Finnish Cultural Foundation (grant No. 00150504)

A pivotal phase in the manufacturing of crystalline silicon solar cells is the formation of the charge collecting pn-junction. Typically, the junction is created via dopant in-diffusion, but lately creating it through implantation has also raised interest. Implantation offers several potential benefits compared to diffusion, such as fewer processing steps and better process control. However, the differences between diffused and implanted junctions with respect to gettering, that is, the control of harmful metal impurities are not yet fully understood. This work studies the precipitation and diffusion of iron in intentionally iron-contaminated phosphorus-implanted silicon solar cells under varying time-temperature profiles. In this study, it is shown that unlike in the case of diffused cells, not only the total amount of precipitated iron, but also the precipitate size distribution of iron can be important when minimizing the harmful effects of iron on the performance of implanted solar cells. A slow cooling from the implant activation temperature to a moderate gettering anneal temperature can result in few, but large iron precipitates at the implanted surface, which improves the bulk minority carrier diffusion length but reduces the open circuit voltage of the solar cell. However, by first forcing bulk precipitation by quenching the wafers to room temperature before the gettering anneal, a large number of small precipitates is formed, resulting in a high open circuit voltage. The iron precipitate size distributions are analyzed in detail via a heterogeneous iron precipitation model and the simulation results are validated with synchrotronbased micro-X-ray fluo-rescence measurements. It is shown that the precipitate size distribution after the gettering anneal can be predicted, if the gettering efficiency of the gettering anneal in question is known. Thus, the next step towards predictive impurity-to-efficiency modeling of implanted cells is predicting the gettering, Keskeinen vaihe piiaurinkokennojen valmistuksessa on varauksen keräävän liitoksen valmistus. Perinteisesti liitos valmistetaan diffusoimalla seosatomeita piikiekkoon, mutta viime aikoina liitoksen luominen istuttamalla on myös herättänyt mielenkiintoa. Verrattuna perinteiseen diffuusioon, istutus on paremmin hallittavissa ja sen avulla voidaan vähentää prosessivaiheiden määrää. Vahingollisten metalliepäpuhtauksien getterointi, eli niiden haittavaikutuksen minimointi kennoprosessin aikana ei ole kuitenkaan niin laajasti ymmärretty istutetuissa kuin diffusoiduissa kennoissa. Tämä työ tutkii rautaepäpuhtauksien erkautumista ja diffuusioita tarkoituksella kontaminoiduissa piiaurinkokennoissa erilaisten lämpökäsittelyiden aikana. Työn tulokset osoittavat, että toisin kuin diffusoiduissa kennoissa, istutetuissa kennoissa erkautuneen raudan kokonaismäärän lisäksi myös erkaumien kokojakaumalla on merkitystä, mikäli raudan negatiiviset vaikutukset halutaan minimoida. Hidas jäähdytys istutuksen aktivointilämpötilasta getterointilämpötilaan voi johtaa harvoihin, mutta isoihin rautaerkaumiin istutetulla pinnalla, mikä lisää vähemmistövarauksenkuljettajan diffuusiopituutta bulkissa, mutta saattaa vähentää kennon avoimen piirin jännitettä. Toisaalta mikäli kennot jäähdytetään nopeasti aktivaatiolämpötilasta huoneen lämpötilaan, syntyy useita, pieniä erkaumia, jotka eivät vahingoita avoimen piirin jännitettä, mutta saattavat rajoittaa diffuusiopituutta bulkissa. Rautaerkaumien kokojakaumia tutkitaan heterogeenisellä erkaumamallilla ja simuloidut kokojakaumat vahvistetaan vertaamalla niitä synkrotroniavusteisella mikro-röntgenfluoresenssi mittauksilla. Työssä näytetään, että kokojakauma getterointiprosessin jälkeen pystytään ennustamaan, mikäli getterointiprosessin aikana bulkista vähentynyt rautakonsentraatio tiedetään etukäteen. Seuraava tutkimusaskel on ennustavan mallin kehittäminen, joka pystyisi ennustamaan rautakonsentraation vähentymisen pelkkien istutusparametrien avulla.