The utilization of carbon dioxide (CO2) has garnered significant attention as a strategy to mitigate anthropogenic emissions. Within this field, the conversion processes of CO2 through photocatalytic systems have emerged as a particularly noteworthy area of research. This approach leverages solar energy for the reaction and is considered a promising and environmentally friendly alternative to traditional thermally driven catalytic systems. This article aims to summarize recent advancements in several key photo-conversion pathways, including the synthesis of methane, methanol, C2 hydrocarbons, dimethyl carbonate, and glycerol carbonate. Additionally, potential configurations for the development of processes aimed at producing various chemicals will be proposed. Current insights indicate that the photocatalytic conversion of CO2 could be effectively integrated with chemical absorption methods, provided that appropriate separation and process intensification strategies are developed. From an economic perspective, the photocatalytic reduction of CO2 minimizes the reliance on green hydrogen as a hydrogen source, thereby significantly improving overall economic viability. Environmentally, it is essential to enhance the reaction conversion and product selectivity of the photocatalytic conversion processes to maximize their decarbonization potential. Overall, this paper is particularly suited for readers who are new to this field and are interested in transitioning from experimental work to process development.

In this paper, we propose a model-based method to study conditional dependence between response accuracy and response time (RT) with the diffusion IRT model (Tuerlinckx and De Boeck in Psychometrika 70(4):629–650, 2005, https://doi.org/10.1007/s11336-000-0810-3; van der Maas et al. in Psychol Rev 118(2):339–356, 2011, https://doi.org/10.1080/20445911.2011.454498). We extend the earlier diffusion IRT model by introducing variability across persons and items in cognitive capacity (drift rate in the evidence accumulation process) and variability in the starting point of the decision processes. We show that the extended model can explain the behavioral patterns of conditional dependency found in the previous studies in psychometrics. Variability in cognitive capacity can predict positive and negative conditional dependency and their interaction with the item difficulty. Variability in starting point can account for the early changes in the response accuracy as a function of RT given the person and item effects. By the combination of the two variability components, the extended model can produce the curvilinear conditional accuracy functions that have been observed in psychometric data. We also provide a simulation study to validate the parameter recovery of the proposed model and present two empirical applications to show how to implement the model to study conditional dependency underlying data response accuracy and RTs.

The morpho-genetic evolution of the upper Aller valley (Weser basin, North Germany) was reconstructed using geological and géomorphologie data integrated within a numerical process model framework (FLUVER-2). The current relief was shaped by Pre-Elsterian fluvial processes, Elsterian and Saalian ice sheets, followed by Weichselian fluvial processes. Structural analysis based on subsurface data and morphological interpretations were used to reconstruct uplift/subsidence rates. A detailed analysis led to the hypothesis that we are dealing with either a NNW-SSE or a WSW-ENE oriented compression leading to uplift in the upper Aller valley. It is also hypothesised that the NNW-SSE compression might have caused strike-slip deformation leading to differential block movement and tilt. Two different uplift rate scenarios were reconstructed and used as a variable parameter in numerical modelling scenarios simulating the Late Quaternary longitudinal dynamics of the Aller. Each different scenario was run for 150.000 years and calibrated to the actual setting. The resulting model settings were consequently evaluated for their plausibility and validity. Subsequently, regional semi-3D simulations of valley development were made to test the two tectonic stress hypotheses. Differential tectonic uplift and regional tilt seems to have played an important role in shaping the current valley morphology in the upper Aller. Unfortunately, due to the uncertainties involved, we were unable to discriminate between the two postulated tectonic stress scenarios.

During the design of complex systems, a design process may be subjected to stochastic disruptions, interruptions, and changes, which can be described broadly as “design impulses.” These impulses can have a significant impact on the transient response and converged equilibrium for the design system. We distinguish this research by focusing on the interactions between local and architectural impulses in the form of designer mistakes and dissolution, division, and combination impulses, respectively, for a distributed design case study. We provide statistical support for the “parallel character hypothesis,” which asserts that parallel arrangements generally best mitigate dissolution and division impulses. We find that local impulses tend to slow convergence, but systems also subjected to dissolution or division impulses still favor parallel arrangements. We statistically uphold the conclusion that the strategy to mitigate combination impulses is unaffected by the presence of local impulses.

This paper presents a framework for the design of a hierarchical Simulator of a robotized sequential technological process. The framework employs concepts of discrerte event simulation modelling. The Simulator consists of two layers: the Simulator of a robot and technological process, and the interpreter and planner of robot tasks. A format specification of both layers is presented. The proposed simulation approach is expected to result in significant improvements in the robot task plan generation and in higher efficiency of a technological process.

Successful realization of large-scale product development programs is challenging because of complex product and process dependencies and complicated team interactions. Proficient teamwork is underpinned by knowledge of the manner in which tasks performed by different design participants fit together to create an effective whole. Based on an extensive industrial case study with a diesel engine company, this paper first argues that the overview and experience of senior designers play an important part in supporting teamwork by coordinating activities and facilitating proactive communication across large project teams. As experts move on and novices or contractors are hired, problems are likely to occur as tacit overview knowledge is lost. If informal, overview-driven processes break down, the risk of costly oversights will increase, and greater management overhead will be required to realize successful product designs. Existing process models provide a means to express the connectivity between tasks and components thus to compensate partially for the loss of tacit overview. This paper proposes the use of design confidence, a metric that reflects the designer's belief in the maturity of a particular design parameter at a given point in the process, to address the limitations of existing models. The applicability of confidence-based design models in providing overview, as well as their shortcomings, will be demonstrated through the example of a diesel engine design process. Confidence can be used to make overview knowledge explicit and convey additional information about the design artifact, thereby informing communication and negotiation between teams.