Digitalization in Thermodynamics

Digitalization is about data and how they are used. This has always been a key topic in applied thermodynamics. In the present work, the influence of the current wave of digitalization on thermodynamics is analyzed. Thermodynamic modeling and simulation is changing as large amounts of data of different nature and quality become easily available. The power and complexity of thermodynamic models and simulation techniques is rapidly increasing, and new routes become viable to link them to the data. Machine learning opens new perspectives, when it is suitably combined with classical thermodynamic theory. Illustrated by examples, different aspects of digitalization in thermodynamics are discussed: strengths and weaknesses as well as opportunities and threats

Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledge

Process synthesis in chemical engineering is a complex planning problem due to vast search spaces, continuous parameters and the need for generalization. Deep reinforcement learning agents, trained without prior knowledge, have shown to outperform humans in various complex planning problems in recent years. Existing work on reinforcement learning for flowsheet synthesis shows promising concepts, but focuses on narrow problems in a single chemical system, limiting its practicality. We present a general deep reinforcement learning approach for flowsheet synthesis. We demonstrate the adaptability of a single agent to the general task of separating binary azeotropic mixtures. Without prior knowledge, it learns to craft near-optimal flowsheets for multiple chemical systems, considering different feed compositions and conceptual approaches. On average, the agent can separate more than 99% of the involved materials into pure components, while autonomously learning fundamental process engineering paradigms. This highlights the agent's planning flexibility, an encouraging step toward true generality.Comment: 36 pages, 7 figures, 4 tables. G\"ottl and Pirnay contributed equally as joint first authors. Burger and Grimm contributed equally as joint last author

Benchmarking five numerical simulation techniques for computing resonance wavelengths and quality factors in photonic crystal membrane line defect cavities

We present numerical studies of two photonic crystal membrane microcavities, a short line-defect cavity with relatively low quality ($Q$) factor and a longer cavity with high $Q$. We use five state-of-the-art numerical simulation techniques to compute the cavity $Q$ factor and the resonance wavelength $\lambda$ for the fundamental cavity mode in both structures. For each method, the relevant computational parameters are systematically varied to estimate the computational uncertainty. We show that some methods are more suitable than others for treating these challenging geometries.Comment: Revised and final version for publication. 28 pages, 10 figures, 7 table

Can We Predict Skeletal Lesion on Bone Scan Based on Quantitative PSMA PET/CT Features?

Objective: The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS). Methods: In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times. Results: A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation. Conclusions: These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection

Genetic deletion of the adaptor protein p66Shc increases susceptibility to short-term ischaemic myocardial injury via intracellular salvage pathways

Genetic deletion of p66Shc, as shown in the present study, leads to increased myocardial infarction in response to short-term ischaemia and reperfusion. Therefore, heart-specific activation of p66Shc protein may represent a promising novel strategy to prevent ischaemic and reperfusion myocardial injury. In particular, pharmacological modulation of apoptosis via myocardial salvage pathways involving p66Shc might be a promising approach to limit short-term ischaemic injury, for instance in patients with acute coronary syndrome (ACS) from the time of symptom onset to percutaneous coronary intervention. However, the present study also adds complexity to the use of this pathway as a therapeutic target. Indeed, given the different effects of activation and silencing of p66Shc in different cells, tissues and organs, tissue selective inhibition would be required. Indeed, while short-term activation might be protective in the context of an ACS, long-term inhibition may prevent endothelial dysfunction, atherosclerosis, and diabetic vascular disease. Obviously, this complexity also raises safety concerns for the potential use of p66Shc in acute myocardial infarction that need to be clarified by additional researc