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Upscaling of the renewable hydrogen economy: a study on complex adaptive systems
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The renewable hydrogen economy is one of the potential solutions in the green transition by reducing the impact of carbon dioxide on society and planetary well-being, particularly in hard-to-abate sectors. This qualitative study examined the upscaling of the hydrogen economy through the lens of complex adaptive systems (CAS) to enhance stakeholder adaptability. The literature review identified central organising concepts that served as a framework for analysing empirical data. The central organising concept was adopted from the reflexive thematic analysis (RTA) method to support the analysis of empirical data. This paper proposes five distinct yet interconnected themes based on these central organising concepts. The findings aim to reveal the potential of a complex adaptive systems approach in the explorative context of the hydrogen economy and suggest directions for future research.Abstract
The renewable hydrogen economy is one of the potential solutions in the green transition by reducing the impact of carbon dioxide on society and planetary well-being, particularly in hard-to-abate sectors. This qualitative study examined the upscaling of the hydrogen economy through the lens of complex adaptive systems (CAS) to enhance stakeholder adaptability. The literature review identified central organising concepts that served as a framework for analysing empirical data. The central organising concept was adopted from the reflexive thematic analysis (RTA) method to support the analysis of empirical data. This paper proposes five distinct yet interconnected themes based on these central organising concepts. The findings aim to reveal the potential of a complex adaptive systems approach in the explorative context of the hydrogen economy and suggest directions for future research
Microstructure evolution and mechanical properties of the lightweight Fe-28Mn-8Al-1C steel under rolling at room and cryogenic temperatures
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A lightweight Fe–28Mn–8Al–1C steel was rolled at room temperature and the liquid nitrogen temperature. The effect of the deformation temperature on the microstructures and mechanical properties of the lightweight steel was systematically studied by optical microscopy (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), electron backscatter diffraction (EBSD), microhardness and tensile testing. The results showed that both cryogenic rolling(CR) and room temperature rolling(RTR) significantly refined the microstructure of the steel to the nanometer level, and CR achieved a finer grain size and a higher dislocation density. The plastic deformation mechanism of lightweight steel was dominated by dislocation slips during the process of rolling, but CR also led to the occurrence of deformation twinning. The lightweight steel formed a Copper {112}〈111〉 texture under low strain, which transformed into a Brass {110} 〈112〉 texture under high strain. The transformation process was accelerated by CR, and a more intense Brass {110} texture was obtained. Under the same level of reduction, increase in the intensity of the strength caused by CR was significantly greater than that of RTR. Due to the generation of deformation twins in the process of CR, the samples subjected to CR showed greater elongation, and the corresponding fracture morphology transferred from ductile fractures in the undeformed state to ductile-brittle mixed fractures after a 90% deformation.Abstract
A lightweight Fe–28Mn–8Al–1C steel was rolled at room temperature and the liquid nitrogen temperature. The effect of the deformation temperature on the microstructures and mechanical properties of the lightweight steel was systematically studied by optical microscopy (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), electron backscatter diffraction (EBSD), microhardness and tensile testing. The results showed that both cryogenic rolling(CR) and room temperature rolling(RTR) significantly refined the microstructure of the steel to the nanometer level, and CR achieved a finer grain size and a higher dislocation density. The plastic deformation mechanism of lightweight steel was dominated by dislocation slips during the process of rolling, but CR also led to the occurrence of deformation twinning. The lightweight steel formed a Copper {112}〈111〉 texture under low strain, which transformed into a Brass {110} 〈112〉 texture under high strain. The transformation process was accelerated by CR, and a more intense Brass {110} texture was obtained. Under the same level of reduction, increase in the intensity of the strength caused by CR was significantly greater than that of RTR. Due to the generation of deformation twins in the process of CR, the samples subjected to CR showed greater elongation, and the corresponding fracture morphology transferred from ductile fractures in the undeformed state to ductile-brittle mixed fractures after a 90% deformation
Multi-objective optimization of a novel hybrid battery thermal management system using response surface method
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This study evaluates the thermal performance of a Z-type battery thermal management system (BTMS) designed for nine lithium-ion batteries discharged at a high rate of 5C, using Computational Fluid Dynamics (CFD) sim- ulations. The investigation employs Response Surface Methodology (RSM) to optimize two critical thermal performance parameters: the maximum battery temperature (Tmax ) and the maximum temperature difference between cells (ΔTmax ). Various cooling strategies are explored to comprehensively assess the BTMS, including natural convection, forced convection, cooling fins, phase change material (PCM), and composite PCM. These methods are analyzed to determine their effectiveness in controlling the thermal behavior of the battery pack. The simulation results indicate that integrating different cooling techniques can significantly lower Tmax from 352.38 K to 309.14 K and reduce ΔTmax from 14.6 K to 3.31 K, depending on the method used. Under critical conditions, such as the failure of the active cooling system, the BTMS still maintained a Tmax of 310.64 K and a ΔTmax of 0.95 K, demonstrating its robustness and reliability. Further optimization identified the ideal config- uration for the system, including an inlet air speed of 1.2 m/s, an inlet temperature of 297.15 K, and a PCM thickness of 3.8 mm, achieving optimal thermal performance with a Tmax of 303.97 K and ΔTmax of 3.17 K. This study offers valuable insights into the design and optimization of effective BTMS for enhanced battery safety and longevity.Abstract
This study evaluates the thermal performance of a Z-type battery thermal management system (BTMS) designed for nine lithium-ion batteries discharged at a high rate of 5C, using Computational Fluid Dynamics (CFD) sim- ulations. The investigation employs Response Surface Methodology (RSM) to optimize two critical thermal performance parameters: the maximum battery temperature (Tmax ) and the maximum temperature difference between cells (ΔTmax ). Various cooling strategies are explored to comprehensively assess the BTMS, including natural convection, forced convection, cooling fins, phase change material (PCM), and composite PCM. These methods are analyzed to determine their effectiveness in controlling the thermal behavior of the battery pack. The simulation results indicate that integrating different cooling techniques can significantly lower Tmax from 352.38 K to 309.14 K and reduce ΔTmax from 14.6 K to 3.31 K, depending on the method used. Under critical conditions, such as the failure of the active cooling system, the BTMS still maintained a Tmax of 310.64 K and a ΔTmax of 0.95 K, demonstrating its robustness and reliability. Further optimization identified the ideal config- uration for the system, including an inlet air speed of 1.2 m/s, an inlet temperature of 297.15 K, and a PCM thickness of 3.8 mm, achieving optimal thermal performance with a Tmax of 303.97 K and ΔTmax of 3.17 K. This study offers valuable insights into the design and optimization of effective BTMS for enhanced battery safety and longevity
Mesoporous nanocomposite polydopamine-coated graphene oxide/maghemite for high-efficient adsorption of diclofenac sodium in batch mode: synthesis, characterization, RSM modeling and optimization
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To address significant health issues and ecological damage associated with drug pollutions in wastewater, a novel mesoporous nanocomposite, polydopamine-coated graphene oxide/maghemite (PDA-GO/ɣ-Fe2O3), was synthesized and utilized for removing diclofenac sodium (DCF) from aqueous solution in batch mode. This study proposed an efficient method for synthesizing PDA-GO/ɣ-Fe2O3 nanocomposites, emphasizing the eco-friendly attributes of the modified GO (PDA-GO) and maghemite nanoparticles (ɣ-Fe2O3). The adsorbent structure was characterized using XRD, BET analysis, FTIR, FE-SEM, and EDX. BET measurements showed that the adsorbent’s mean pore diameter was approximately 7.5 nm, confirming its mesoporous structure. The EDX spectrum displayed peaks corresponding to oxygen, carbon, iron, and nitrogen in the composition of the PDA-GO/ɣ-Fe2O3 nanocomposite. FTIR analysis showed the presence of various functional groups, including hydroxyl, carboxylate, and carbonyl groups, on the surface of the PDA-GO/ɣ-Fe2O3 composite. The R2 values obtained from the quadratic models using RSM-CCD for the composite adsorbent were 0.988 and 0.998 for removal efficiency and adsorption capacity, respectively. The optimal operating parameters to reach the maximum adsorption capacity of 151.9 mg/g and removal efficiency of 93.12% were determined at an initial DCF concentration of 32.5 mg/L, a temperature of 25 °C, a contact time of 40 min, and a pH of 3, using the CCD-RSM methodology. The kinetics of adsorption were well described by the Fickian diffusion model. By performing four repeated cycles of DCF adsorption/desorption using NaOH solution as an eluent at pH 8, reductions in removal efficiency of 2 and 10% were observed during first three cycles and fourth cycle, respectively.Abstract
To address significant health issues and ecological damage associated with drug pollutions in wastewater, a novel mesoporous nanocomposite, polydopamine-coated graphene oxide/maghemite (PDA-GO/ɣ-Fe2O3), was synthesized and utilized for removing diclofenac sodium (DCF) from aqueous solution in batch mode. This study proposed an efficient method for synthesizing PDA-GO/ɣ-Fe2O3 nanocomposites, emphasizing the eco-friendly attributes of the modified GO (PDA-GO) and maghemite nanoparticles (ɣ-Fe2O3). The adsorbent structure was characterized using XRD, BET analysis, FTIR, FE-SEM, and EDX. BET measurements showed that the adsorbent’s mean pore diameter was approximately 7.5 nm, confirming its mesoporous structure. The EDX spectrum displayed peaks corresponding to oxygen, carbon, iron, and nitrogen in the composition of the PDA-GO/ɣ-Fe2O3 nanocomposite. FTIR analysis showed the presence of various functional groups, including hydroxyl, carboxylate, and carbonyl groups, on the surface of the PDA-GO/ɣ-Fe2O3 composite. The R2 values obtained from the quadratic models using RSM-CCD for the composite adsorbent were 0.988 and 0.998 for removal efficiency and adsorption capacity, respectively. The optimal operating parameters to reach the maximum adsorption capacity of 151.9 mg/g and removal efficiency of 93.12% were determined at an initial DCF concentration of 32.5 mg/L, a temperature of 25 °C, a contact time of 40 min, and a pH of 3, using the CCD-RSM methodology. The kinetics of adsorption were well described by the Fickian diffusion model. By performing four repeated cycles of DCF adsorption/desorption using NaOH solution as an eluent at pH 8, reductions in removal efficiency of 2 and 10% were observed during first three cycles and fourth cycle, respectively
Gate teleportation-assisted routing for quantum algorithms
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The limited qubit connectivity of quantum processors poses a significant challenge in deploying practical algorithms and logical gates, necessitating efficient qubit mapping and routing strategies. When implementing a gate that requires additional connectivity beyond the native connectivity, the qubit state must be moved to a nearby connected qubit to execute the desired gate locally. This is typically achieved using a series of SWAP gates creating a SWAP path. However, routing methods relying on SWAP gates often lead to increased circuit depth and gate count, motivating the need for alternative approaches. This work explores the potential of teleported gates to improve qubit routing efficiency, focusing on implementation within specific hardware topologies and benchmark quantum algorithms. We propose a routing method that is assisted by gate teleportation. It establishes additional connectivity using gate teleportation paths through available unused qubits, termed auxiliary qubits, within the topology. To optimize this approach, we have developed an algorithm to identify the best gate teleportation connections, considering their potential to reduce the depth of the circuit and address possible errors that may arise from the teleportation paths. Finally, we demonstrate depth reduction with gate teleportation-assisted routing in various benchmark algorithms, including case studies on the compilation of the Deutsch–Jozsa algorithm and the quantum approximation optimization algorithm for heavy-hexagon topology used in IBM 127-qubit Eagle r3 processors. Our benchmark results show a 10%–25% depth reduction in the routing of selected algorithms compared to regular routing without using teleported gates.Abstract
The limited qubit connectivity of quantum processors poses a significant challenge in deploying practical algorithms and logical gates, necessitating efficient qubit mapping and routing strategies. When implementing a gate that requires additional connectivity beyond the native connectivity, the qubit state must be moved to a nearby connected qubit to execute the desired gate locally. This is typically achieved using a series of SWAP gates creating a SWAP path. However, routing methods relying on SWAP gates often lead to increased circuit depth and gate count, motivating the need for alternative approaches. This work explores the potential of teleported gates to improve qubit routing efficiency, focusing on implementation within specific hardware topologies and benchmark quantum algorithms. We propose a routing method that is assisted by gate teleportation. It establishes additional connectivity using gate teleportation paths through available unused qubits, termed auxiliary qubits, within the topology. To optimize this approach, we have developed an algorithm to identify the best gate teleportation connections, considering their potential to reduce the depth of the circuit and address possible errors that may arise from the teleportation paths. Finally, we demonstrate depth reduction with gate teleportation-assisted routing in various benchmark algorithms, including case studies on the compilation of the Deutsch–Jozsa algorithm and the quantum approximation optimization algorithm for heavy-hexagon topology used in IBM 127-qubit Eagle r3 processors. Our benchmark results show a 10%–25% depth reduction in the routing of selected algorithms compared to regular routing without using teleported gates
Circular entrepreneurial ecosystem: a hybrid review and research agenda
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The importance of circular economy and entrepreneurial ecosystems are continuously growing. Despite the proliferation of related literature in recent years, there is a lack of systematic and holistic review that consolidates and provides intersectional perspective on circular economy and entrepreneurial ecosystems. Therefore, the present hybrid review combines bibliometric analysis and systematic literature review methods. By collecting relevant scholarly articles from the Web of Science database platform, this study explores the interconnected themes of the circular economy and entrepreneurial ecosystem, and based on this, the concept of the circular entrepreneurial ecosystem emerged. This intersectional view advances the understanding of the actors who collaborate to enhance resource efficiency and minimise waste generation by emphasising repair, reuse, refurbishment, sharing and recycling as key strategies for sustainable development. The study identifies three dominant research themes and sheds light on the significance of the entrepreneurial ecosystem in the transition towards a circular economy.Abstract
The importance of circular economy and entrepreneurial ecosystems are continuously growing. Despite the proliferation of related literature in recent years, there is a lack of systematic and holistic review that consolidates and provides intersectional perspective on circular economy and entrepreneurial ecosystems. Therefore, the present hybrid review combines bibliometric analysis and systematic literature review methods. By collecting relevant scholarly articles from the Web of Science database platform, this study explores the interconnected themes of the circular economy and entrepreneurial ecosystem, and based on this, the concept of the circular entrepreneurial ecosystem emerged. This intersectional view advances the understanding of the actors who collaborate to enhance resource efficiency and minimise waste generation by emphasising repair, reuse, refurbishment, sharing and recycling as key strategies for sustainable development. The study identifies three dominant research themes and sheds light on the significance of the entrepreneurial ecosystem in the transition towards a circular economy
Opiskelijaohjausverkkokoulutuksen vaikutus terveydenhuollon ammattilaisten opiskelijaohjausosaamiseen – kvasikokeellinen interventiotutkimus
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Terveysalan opiskelijoiden ammattitaitoa edistävien harjoittelujen ohjaus on keskeinen osa terveysalan ammattilaisten työtä. Tämä edellyttää ohjaajalta erityisosaamista, joka ei sisälly terveysalan tutkintojen osaamisvaatimuksiin. Opiskelijaohjauksen tueksi terveydenhuollon ammattilaiset tarvitsevat koulutusta. Tutkimuksen tarkoituksena oli arvioida verkkokoulutuksena toteutetun opiskelijaohjauskoulutuksen vaikutusta terveydenhuollon ammattilaisten opiskelijaohjausosaamiseen sekä kuvailla terveydenhuollon ammattilaisten tyytyväisyyttä ja kokemuksia opiskelijaohjausverkkokoulutuksen toteutuksesta. Verkkokoulutuksena järjestetty opiskelijaohjauskoulutus pohjautui eurooppalaiseen opiskelijaohjaajien osaamismalliin ja konstruktivistiseen oppimisteoriaan.
Kvasikokeellisen interventiotutkimuksen vaikuttavuutta arvioitiin ennen-jälkeen-tutkimusasetelmalla. Tutkimusjoukko muodostui opiskelijaohjausverkkokoulutuksen suorittaneista terveydenhuollon ammattilaisista (n=56). Opiskelijaohjausosaamista arvioitiin Opiskelijaohjausosaaminen (MCI)- ja Kulttuurinen osaaminen opiskelijaohjauksessa (MCCI)-mittareilla. Aineisto analysoitiin tilastollisilla menetelmillä ja avoimet kysymykset narratiivisella analyysimenetelmällä. Terveydenhuollon ammattilaisten yleinen opiskelijaohjausosaaminen vahvistui tilastollisesti merkitsevästi jokaisella osaamisalueella: käytännöt työyksikössä, ohjaajan ominaisuudet, ohjaajan motivaatio, ohjauksen tavoitteellisuus, reflektiivinen ohjauskeskustelu, opiskelijalähtöinen arviointi ja kehittävä palaute. Kulttuurinen osaaminen opiskelijaohjauksessa kasvoi tilastollisesti merkitsevästi kulttuurisen vuorovaikutuksen ja turvallisuuden sekä kulttuuristen taitojen osaamisalueilla. Terveydenhuollon ammattilaisten opiskelijaohjausosaamista voidaan vahvistaa itsenäisesti suoritettavan verkkokoulutuksen avulla. Opiskelijaohjauskoulutukseen osallistuminen tulisi mahdollistaa kaikille terveydenhuollon ammattilaisille. Verkkokoulutustoteutus voi edistää koulutukseen osallistumisen mahdollisuuksia.Abstrakti
Terveysalan opiskelijoiden ammattitaitoa edistävien harjoittelujen ohjaus on keskeinen osa terveysalan ammattilaisten työtä. Tämä edellyttää ohjaajalta erityisosaamista, joka ei sisälly terveysalan tutkintojen osaamisvaatimuksiin. Opiskelijaohjauksen tueksi terveydenhuollon ammattilaiset tarvitsevat koulutusta. Tutkimuksen tarkoituksena oli arvioida verkkokoulutuksena toteutetun opiskelijaohjauskoulutuksen vaikutusta terveydenhuollon ammattilaisten opiskelijaohjausosaamiseen sekä kuvailla terveydenhuollon ammattilaisten tyytyväisyyttä ja kokemuksia opiskelijaohjausverkkokoulutuksen toteutuksesta. Verkkokoulutuksena järjestetty opiskelijaohjauskoulutus pohjautui eurooppalaiseen opiskelijaohjaajien osaamismalliin ja konstruktivistiseen oppimisteoriaan.
Kvasikokeellisen interventiotutkimuksen vaikuttavuutta arvioitiin ennen-jälkeen-tutkimusasetelmalla. Tutkimusjoukko muodostui opiskelijaohjausverkkokoulutuksen suorittaneista terveydenhuollon ammattilaisista (n=56). Opiskelijaohjausosaamista arvioitiin Opiskelijaohjausosaaminen (MCI)- ja Kulttuurinen osaaminen opiskelijaohjauksessa (MCCI)-mittareilla. Aineisto analysoitiin tilastollisilla menetelmillä ja avoimet kysymykset narratiivisella analyysimenetelmällä. Terveydenhuollon ammattilaisten yleinen opiskelijaohjausosaaminen vahvistui tilastollisesti merkitsevästi jokaisella osaamisalueella: käytännöt työyksikössä, ohjaajan ominaisuudet, ohjaajan motivaatio, ohjauksen tavoitteellisuus, reflektiivinen ohjauskeskustelu, opiskelijalähtöinen arviointi ja kehittävä palaute. Kulttuurinen osaaminen opiskelijaohjauksessa kasvoi tilastollisesti merkitsevästi kulttuurisen vuorovaikutuksen ja turvallisuuden sekä kulttuuristen taitojen osaamisalueilla. Terveydenhuollon ammattilaisten opiskelijaohjausosaamista voidaan vahvistaa itsenäisesti suoritettavan verkkokoulutuksen avulla. Opiskelijaohjauskoulutukseen osallistuminen tulisi mahdollistaa kaikille terveydenhuollon ammattilaisille. Verkkokoulutustoteutus voi edistää koulutukseen osallistumisen mahdollisuuksia
Ligninolytic Enzymes for Biofuel Applications
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Lignocellulosic biomass is an abundantly available, renewable, and inexpensive resource for biofuel production. The main constituents of lignocellulosic biomass are cellulose, hemicellulose, and lignin. Converting lignocellulosic biomass into biofuels requires pretreatment to separate these fractions. However, lignin, a complex polymer, hinders biomass conversion due to its recalcitrant nature and presents many challenges. Ligninolytic enzymes can transform the lignin component of lignocellulosic biomass. This chapter provides an overview of major ligninolytic enzymes, including laccases, lignin peroxidases, manganese peroxidases, and versatile peroxidases, which are effective in lignin degradation. Additionally, it highlights different sources for ligninolytic enzyme production and the mechanisms by which these enzymes break down lignin components. It also discusses the challenges and future perspectives of ligninolytic enzymes.Abstract
Lignocellulosic biomass is an abundantly available, renewable, and inexpensive resource for biofuel production. The main constituents of lignocellulosic biomass are cellulose, hemicellulose, and lignin. Converting lignocellulosic biomass into biofuels requires pretreatment to separate these fractions. However, lignin, a complex polymer, hinders biomass conversion due to its recalcitrant nature and presents many challenges. Ligninolytic enzymes can transform the lignin component of lignocellulosic biomass. This chapter provides an overview of major ligninolytic enzymes, including laccases, lignin peroxidases, manganese peroxidases, and versatile peroxidases, which are effective in lignin degradation. Additionally, it highlights different sources for ligninolytic enzyme production and the mechanisms by which these enzymes break down lignin components. It also discusses the challenges and future perspectives of ligninolytic enzymes