@article{33680,
  author       = {{Khajehpasha, Ehsan Rahmatizad and Finkler, Jonas A. and Kühne, Thomas and Ghasemi, Alireza}},
  issn         = {{2469-9950}},
  journal      = {{Physical Review B}},
  number       = {{14}},
  publisher    = {{American Physical Society (APS)}},
  title        = {{{CENT2: Improved charge equilibration via neural network technique}}},
  doi          = {{10.1103/physrevb.105.144106}},
  volume       = {{105}},
  year         = {{2022}},
}

@article{33686,
  author       = {{Elizabeth, Amala and Sahoo, Sudhir K. and Phirke, Himanshu and Kodalle, Tim and Kühne, Thomas and Audinot, Jean-Nicolas and Wirtz, Tom and Redinger, Alex and Kaufmann, Christian A. and Mirhosseini, Hossein and Mönig, Harry}},
  issn         = {{1944-8244}},
  journal      = {{ACS Applied Materials & Interfaces}},
  keywords     = {{General Materials Science}},
  number       = {{29}},
  pages        = {{34101--34112}},
  publisher    = {{American Chemical Society (ACS)}},
  title        = {{{Surface Passivation and Detrimental Heat-Induced Diffusion Effects in RbF-Treated Cu(In,Ga)Se<sub>2</sub> Solar Cell Absorbers}}},
  doi          = {{10.1021/acsami.2c08257}},
  volume       = {{14}},
  year         = {{2022}},
}

@article{33689,
  author       = {{Raghuwanshi, Mohit and Chugh, Manjusha and Sozzi, Giovanna and Kanevce, Ana and Kühne, Thomas and Mirhosseini, Hossein and Wuerz, Roland and Cojocaru‐Mirédin, Oana}},
  issn         = {{0935-9648}},
  journal      = {{Advanced Materials}},
  keywords     = {{Mechanical Engineering, Mechanics of Materials, General Materials Science}},
  number       = {{37}},
  publisher    = {{Wiley}},
  title        = {{{Fingerprints Indicating Superior Properties of Internal Interfaces in Cu(In,Ga)Se            <sub>2</sub>            Thin‐Film Solar Cells}}},
  doi          = {{10.1002/adma.202203954}},
  volume       = {{34}},
  year         = {{2022}},
}

@article{33690,
  author       = {{Ibaceta-Jaña, Josefa and Chugh, Manjusha and Novikov, Alexander S. and Mirhosseini, Hossein and Kühne, Thomas and Szyszka, Bernd and Wagner, Markus R. and Muydinov, Ruslan}},
  issn         = {{1932-7447}},
  journal      = {{The Journal of Physical Chemistry C}},
  keywords     = {{Surfaces, Coatings and Films, Physical and Theoretical Chemistry, General Energy, Electronic, Optical and Magnetic Materials}},
  number       = {{38}},
  pages        = {{16215--16226}},
  publisher    = {{American Chemical Society (ACS)}},
  title        = {{{Do Lead Halide Hybrid Perovskites Have Hydrogen Bonds?}}},
  doi          = {{10.1021/acs.jpcc.2c02984}},
  volume       = {{126}},
  year         = {{2022}},
}

@article{33683,
  author       = {{Lepre, Enrico and Heske, Julian Joachim and Nowakowski, Michal and Scoppola, Ernesto and Zizak, Ivo and Heil, Tobias and Kühne, Thomas and Antonietti, Markus and López-Salas, Nieves and Albero, Josep}},
  issn         = {{2211-2855}},
  journal      = {{Nano Energy}},
  keywords     = {{Electrical and Electronic Engineering, General Materials Science, Renewable Energy, Sustainability and the Environment}},
  publisher    = {{Elsevier BV}},
  title        = {{{Ni-based electrocatalysts for unconventional CO2 reduction reaction to formic acid}}},
  doi          = {{10.1016/j.nanoen.2022.107191}},
  volume       = {{97}},
  year         = {{2022}},
}

@misc{33688,
  author       = {{Balos, Vasileios and Kaliannan, Naveen Kumar and Elgabarty, Hossam and Wolf, Martin and Kühne, Thomas and Sajadi, Mohsen}},
  publisher    = {{LibreCat University}},
  title        = {{{Time resolved THz-Raman spectroscopy reveals that cations and anions distinctly modify intermolecular interactions of water}}},
  doi          = {{10.5281/ZENODO.6514905}},
  year         = {{2022}},
}

@article{33692,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>An individual’s relation to time may be an important driver of pro-environmental behaviour. We studied whether young individual’s gender and time-orientation are associated with pro-environmental behaviour. In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time-orientation. In this consequential behavioural setting, we find that males who scored higher on <jats:italic>future-negative</jats:italic> orientation showed significantly more pro-environmental behaviour compared to females who scored higher on <jats:italic>future-negative</jats:italic> orientation and males who scored lower on <jats:italic>future-negative</jats:italic> orientation. Interestingly, our results are completely reversed when it comes to <jats:italic>past-positive</jats:italic> orientation. These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.</jats:p>}},
  author       = {{Hoffmann, Christin and Hoppe, Julia Amelie and Ziemann, Niklas}},
  issn         = {{1748-9326}},
  journal      = {{Environmental Research Letters}},
  keywords     = {{Public Health, Environmental and Occupational Health, General Environmental Science, Renewable Energy, Sustainability and the Environment}},
  number       = {{10}},
  publisher    = {{IOP Publishing}},
  title        = {{{Who has the future in mind? Gender, time perspectives, and pro-environmental behaviour}}},
  doi          = {{10.1088/1748-9326/ac9296}},
  volume       = {{17}},
  year         = {{2022}},
}

@techreport{33702,
  abstract     = {{<jats:p>Im Rahmen dieser Studie wird der Status Quo des KI-Einsatzes in der industriellen Arbeitswelt in der Region OstWestfalenLippe erfasst und beschrieben. Dadurch wird eine Grundlage geschaffen, um eine zielführende Unterstützung der Gestaltung von durch Künstliche Intelligenz (KI) gestützter Arbeitsprozesse in Unternehmen zu ermöglichen, indem beispielsweise bedarfsbezogene Maßnahmen entwickelt und durchgeführt sowie weiterer Forschungsbedarf aufgezeigt wird.  Die Befragung wurde im Jahr 2021 von dem Kompetenzzentrum Arbeitswelt.Plus sowie dem Spitzencluster it’s OWL initiiert. Dabei sind drei Zielgruppen – Unternehmensleitung, Personalabteilung (HR) sowie Arbeitnehmer*innen – adressiert worden. Insgesamt nahmen 317 Personen aus 89 verschiedenen Unternehmen bzw. Organisationen an der Befragung teil – zu 38 % Unternehmer*innen, zu 13 % Personaler*innen und zu 49 % Arbeitnehmer*innen. Die meisten der Teilnehmenden stammten aus der Elektroindustrie, dem Maschinenbau sowie dem Informations- und Kommunikationstechnologie (IKT)-Sektor.  Die Befragungsergebnisse zeigen, dass sich die meisten Unternehmen in der Anfangsphase der KI-Nutzung befinden. Zwischen einzelnen Unternehmensbereichen und verschiedenen Branchen zeigen sich gewisse Unterschiede in der Nutzungsphase. Die Befragten stehen aktuell vor der Nutzung von vor allem teilautonomen KI-Systemen, die ausführende und analytische menschliche Tätigkeitenbeispielsweise durch Informationsbereitstellungen unterstützen. Wesentliche Ziele der KI-Nutzung sind die Effizienzsteigerung, Qualitätsverbesserung, Entscheidungsoptimierung sowie Unterstützung der Arbeitnehmer*innen. Allerdings werden in allen Unternehmen die fehlende Expertise sowie insgesamt die Komplexität des Themenfelds als Hinderungsgründe identifiziert.  In allen Unternehmen und allen Unternehmensbereichen werden hohe Auswirkungen durch KI erwartet. Auf die Arbeitsgestaltung werden insgesamt eher positive Auswirkungen erwartet. Die Befragten schätzen die Bedeutung von KI, ihre Aufgeschlossenheit sowie ihr Vertrauen gegenüber KI als insgesamt hoch ein, ihr Verständnis von KI dagegen eher als gering. Tendenziell zeigt sich eine große Diskrepanz zwischen Selbst- und Fremdbild mit einer teils deutlich negativeren Wahrnehmung anderer. Die Befragten erwarten außerdem steigende Kompetenzanforderungen sowie einen hohen Weiterbildungsbedarf, insbesondere bezüglich des grundlegenden Verständnisses über KI. In den wenigsten Unternehmen existiert jedoch ein gezieltes Weiterbildungsangebot.  Die Erkenntnisse aus der Befragung fließen im Rahmen des Kompetenzzentrums Arbeitswelt.Plus in die gezielte Gestaltung und Einführung KI-gestützter Arbeitsformen sowie bedarfsgerechter Unterstützungsangebote ein. Die hohe Komplexität der KI-Einführung sowie die sowohl technischen als auch mitarbeiterbezogenen Herausforderungen verdeutlichen den Bedarf für eine soziotechnische Perspektive und ein systematisches Vorgehen bei der Gestaltung dieses vielschichtigen Themenfelds.</jats:p>}},
  author       = {{Papenkordt, Jörg and Gabriel, Stefan and Thommes, Kirsten and Dumitrescu, Roman}},
  publisher    = {{Kompetenzzentrum Arbeitswelt.Plus}},
  title        = {{{Künstliche Intelligenz in der industriellen Arbeitswelt - Studie zum Status Quo in der Region OstWestfalenLippe}}},
  doi          = {{10.55594/tmao3234}},
  year         = {{2022}},
}

@article{33701,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Künstliche Intelligenz bietet großes Potenzial im Engineering. Der Einsatz gestattet insbesondere für Wissensarbeiter eine effiziente Arbeitsteilung, in der beispielsweise fehleranfällige und repetitive Aktivitäten unterstützt werden. Eine erfolgreiche Einführung bedarf einer vorangehenden Analyse von nutzenstiftenden Einsatzpotenzialen, bei der alle Anwendenden frühzeitig einbezogen werden. Der folgende Beitrag verdeutlicht dieses Vorgehen anhand eines realen Beispiels im Sondermaschinenbau.</jats:p>}},
  author       = {{Kharatyan, Aschot and Humpert, Lynn and Anacker, Harald and Dumitrescu, Roman and Wäschle, Moritz and Albers, Albert and Horstmeyer, Sarah}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  keywords     = {{Management Science and Operations Research, Strategy and Management, General Engineering}},
  number       = {{6}},
  pages        = {{427--431}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Künstliche Intelligenz im Engineering}}},
  doi          = {{10.1515/zwf-2022-1074}},
  volume       = {{117}},
  year         = {{2022}},
}

@article{33705,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The ongoing digitalization of products offers product managers new potentials to plan future product generations based on data from the use phase instead of assumptions. However, product managers often face difficulties in identifying promising opportunities for analyzing use phase data. In this paper, we propose a method for planning the analysis of use phase data in product planning. It leads product managers from the identification of promising investigation needs to the derivation of specific use cases. The application of the method is shown using the example of a manufacturing company.</jats:p>}},
  author       = {{Meyer, Maurice and Wiederkehr, Ingrid and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{753--762}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Planning the Analysis of Use Phase Data in Product Planning}}},
  doi          = {{10.1017/pds.2022.77}},
  volume       = {{2}},
  year         = {{2022}},
}

@inproceedings{33708,
  abstract     = {{The megatrend digitalization turns mechatronic products into continuous collectors and generators of use phase data. By analyzing this data, manufacturers can uncover valuable insights about the products and the users. Especially in product planning, these insights could be used to plan promising future product generations. The systematic exploitation of data analytics results, however, represents a serious challenge, as research on the topic is still scarce. In this paper, we present 13 design principles for exploiting data analytics results in product planning. The results are based on a systematic literature review and a workshop with a research consortium. The evaluation of the design principles is demonstrated with a real case of a manufacturing company. The identified design principles represent a first contribution to a still scarcely explored research field.}},
  author       = {{Meyer, Maurice and Fichtler, Timm and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{ AMCIS 2022 Proceedings}},
  location     = {{Minneapolis}},
  title        = {{{How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning}}},
  year         = {{2022}},
}

@article{33707,
  author       = {{Meyer, Maurice and Panzner, Melina and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2212-8271}},
  journal      = {{Procedia CIRP}},
  keywords     = {{General Medicine}},
  pages        = {{1053--1058}},
  publisher    = {{Elsevier BV}},
  title        = {{{17 Use Cases for Analyzing Use Phase Data in Product Planning of Manufacturing Companies}}},
  doi          = {{10.1016/j.procir.2022.05.107}},
  volume       = {{107}},
  year         = {{2022}},
}

@misc{33709,
  author       = {{Wiecher, Carsten  and Mandel, Constantin  and Günther, Matthias  and Fischbach, Jannik  and Greenyer, Joel  and Greinert, Matthias  and Wolff, Carsten  and Dumitrescu, Roman and Mendez, Daniel  and Albers, Albert}},
  booktitle    = {{arXiv preprint}},
  title        = {{{Model-based Analysis and Specification of Functional Requirements and Tests for Complex Automotive Systems}}},
  year         = {{2022}},
}

@article{33714,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Industry 4.0 promises many potentials in production. Examples are a data-driven optimization of production processes of individual machines, driverless transport systems, and assistance systems. Nevertheless, companies are still hesitant to invest in Industry 4.0 applications. Studies show that one of the main reasons for that is the unclear economic benefit. In this work, we present a systematic approach for the evaluation of Industry 4.0 applications in production. The main goal of the systematic is to create transparency over the evaluation process of an investment in an Industry 4.0 application in production. The evaluation of a concrete technical solution in an existing production system is supported. As a theoretical foundation, a characterization of investments in Industry 4.0 applications is given. From that, a procedure model is derived. It puts the activities to be carried out, the tools to be used and results in a temporal context. The application of the systematic is shown on the basis of an application example.</jats:p>}},
  author       = {{Joppen, Robert and Kühn, Arno and Förster, Magdalena and Dumitrescu, Roman}},
  issn         = {{1868-7865}},
  journal      = {{Journal of the Knowledge Economy}},
  keywords     = {{Economics and Econometrics}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Evaluation of Industry 4.0 Applications in Production}}},
  doi          = {{10.1007/s13132-022-00959-2}},
  year         = {{2022}},
}

@article{33713,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The development of technical systems requires close cooperation of stakeholders from different disciplines. This collaboration takes place in workshops. Driven by digitalization and by the current pandemic such workshops take place primarily online. Suitable collaboration tools and methods are crucial to success. At the beginning of such workshops, use and damage scenarios are identified. In this paper, we presented a method and tool for identifying and modeling use and damage scenarios, which we evaluated in 14 online workshops with a total of 118 participants over a period of almost 3 years.</jats:p>}},
  author       = {{Japs, Sergej and Schmidt, Sebastian and Kargl, Frank and Kaiser, Lydia and Kharatyan, Aschot and Dumitrescu, Roman}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{1599--1608}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Collaborative Modeling of Use Case &amp; Damage Scenarios in Online Workshops Using a 3D Environment}}},
  doi          = {{10.1017/pds.2022.162}},
  volume       = {{2}},
  year         = {{2022}},
}

@article{33715,
  author       = {{Japs, Sergej and Kargl, Frank and Anacker, Harald and Dumitrescu, Roman}},
  issn         = {{2212-8271}},
  journal      = {{Procedia CIRP}},
  keywords     = {{General Medicine}},
  pages        = {{293--298}},
  publisher    = {{Elsevier BV}},
  title        = {{{Why make it hard? - Usage of aggregated statistical data for risk assessment of damage scenarios in the context of ISO/SAE 21434}}},
  doi          = {{10.1016/j.procir.2022.05.252}},
  volume       = {{109}},
  year         = {{2022}},
}

@inproceedings{33712,
  author       = {{Mager, Thomas and Jürgenhake, Christoph and Dumitrescu, Roman}},
  booktitle    = {{2022 14th German Microwave Conference (GeMiC)}},
  location     = {{Ulm}},
  pages        = {{224--227}},
  publisher    = {{IEEE}},
  title        = {{{Efficient method for determining substrate parameters of additive manufactured spatial circuit carriers}}},
  year         = {{2022}},
}

@inproceedings{33711,
  author       = {{Gollner, Denis and Klausmann, Tobias and Rasor, Rik and Dumitrescu, Roman}},
  booktitle    = {{2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS)}},
  publisher    = {{IEEE}},
  title        = {{{Use Case Driven Digital Twin Generation}}},
  doi          = {{10.1109/icps51978.2022.9816907}},
  year         = {{2022}},
}

@article{33718,
  author       = {{Gabriel, Stefan and Bentler, Dominik and Grote, Eva-Maria and Junker, Caroline and Wendischhoff, David Meyer zu and Bansmann, Michael and Latos, Benedikt and Hobscheidt, Daniela and Kühn, Arno and Dumitrescu, Roman}},
  issn         = {{2212-8271}},
  journal      = {{Procedia CIRP}},
  keywords     = {{General Medicine}},
  pages        = {{431--436}},
  publisher    = {{Elsevier BV}},
  title        = {{{Requirements analysis for an intelligent workforce planning system: a socio-technical approach to design AI-based systems}}},
  doi          = {{10.1016/j.procir.2022.05.274}},
  volume       = {{109}},
  year         = {{2022}},
}

@article{33716,
  author       = {{Förster, Magdalena and Kürpick, Christian and Hobscheidt, Daniela and Kühn, Arno and Dumitrescu, Roman}},
  issn         = {{2212-8271}},
  journal      = {{Procedia CIRP}},
  keywords     = {{General Medicine}},
  pages        = {{322--327}},
  publisher    = {{Elsevier BV}},
  title        = {{{Cross-industry methods for strategic planning of the digital transformation of small and medium sized enterprises}}},
  doi          = {{10.1016/j.procir.2022.05.257}},
  volume       = {{109}},
  year         = {{2022}},
}