Highlights

Abstract

Keywords

1. Introduction

2. The five problems of irreversibility

3. Dynamical density functional theory

4. First problem: The source of irreversibility in thermodynamics

5. Second Problem: The Definition of “Equilibrium” and “Entropy”

6. Third problem: The justification of coarse-graining

7. Fourth problem: The (irreversible) approach to equilibrium

8. Fifth problem: The arrow of time

9. Conclusion

Declaration of Competing Interest

Acknowledgments

References

Abstract

Thermodynamics has a clear arrow of time, characterized by the irreversible approach to equilibrium. This stands in contrast to the laws of microscopic theories, which are invariant under time-reversal. Foundational discussions of this “problem of irreversibility” often focus on historical considerations, and do therefore not take results of modern physical research on this topic into account. In this article, I will close this gap by studying the implications of dynamical density functional theory (DDFT), a central method of modern nonequilibrium statistical mechanics not previously considered in philosophy of physics, for this debate. For this purpose, the philosophical discussion of irreversibility is structured into five problems, concerned with the source of irreversibility in thermodynamics, the definition of equilibrium and entropy, the justification of coarse-graining, the approach to equilibrium and the arrow of time. For each of these problems, it is shown that DDFT provides novel insights that are of importance for both physicists and philosophers of physics.

1. Introduction

The temporal asymmetry of thermodynamics is one of the central problems in philosophy of physics. If a cup of hot coffee stands in a room, it will cool down until it has room temperature, but it will not spontaneously heat up by extracting heat from its environment. This is commonly seen as a consequence of the second law of thermodynamics, which assigns to each of these systems a quantity known as “entropy” that increases in these processes and that, most importantly, cannot decrease. Often, this is considered one of the most fundamental laws of physics (Callender, 2001, p. 540).

However, as is also well-known, there is a conflict with the microscopic laws governing the motion of the individual particles that a macroscopic system consists of. These laws are invariant under timereversal,1 which means that if a process can occur in one direction of time, it can also occur in the other direction. Thus, a cup of coffee at room temperature that spontaneously heats up would be in perfect agreement with the microscopic laws of physics, which makes it very difficult to explain why such a behavior is never observed.

An intense discussion on this problem has emerged in philosophy of physics. It has evolved into a variety of sub-debates concerned with different explananda that, in this article will be classified into five problems. Often, foundational discussions of statistical mechanics focus on historical aspects. Moreover, there has been a growth of interest in formal approaches to coarse-graining based on the projection operator formalism (Mori, 1965; Zwanzig, 1960). There is, however, a lack of work that considers the implications of modern research on nonequilibrium statistical mechanics for foundational problems (Wallace, 2015).

1- Introduction

2- Calculation details

3- Results and discussion

4- Conclusion

References

Abstract

High spin-polarized materials are expected for the development of spintronic devices. In this work, we are aiming to find new spintronic materials in Mn-based binary, ternary and quaternary Heusler alloys by using the first-principles calculations. We investigated structures, electronic properties, magnetic, tetragonal distortion and mechanic properties of Mn3Ga, Mn2YGa (Y = V, Nb, Ta) and ScMnVGa. The results show that Mn3Ga, ScMnVGa type-I, and type-II have lower energy in antiferromagnetic (AFM) states than ferromagnetic (FM) and paramagnetic (NM). Mn2YGa (Y = V, Nb, Ta) compounds are more stable in FM states. The results of electronic and magnetic properties indicate that Mn3Ga is a gapless half-metallic antiferromagnet (Gapless HM-AFM). Mn2VGa and Mn2NbGa belong to gapless half-metallic ferrimagnets (Gapless HM-FE). Mn2TaGa is ferrimagnets. ScMnVGa type-I is half-metallic antiferromagnets (HM-AFM) and type-II belongs to spin gapless semiconductors with AFM (SGSs-AFM). Inspired by Ferromagnetic shape memory alloys (FAMAs), we performed tetragonal deformation of those compounds, and we predicted that Mn3Ga, Mn2YGa (Y = V, Nb, Ta) have possible martensitic transformations. Finally, the mechanical stability and elastic properties of above-mentioned in both cubic and tetragonal structures were discussed in detail.

Introduction

Spintronics is considered to be one of the most promising subjects in the information age because spintronic devices use not only the state of charge but electronic spin to transfer and store information, which speeds up information transmission and reduces energy losses. The findings of Giant Magnetoresistance (GMR), Colossal Magnetoresistance (CMR) and Tunnel Magnetoresistance (MGR) accelerate the development of spintronics. Despite great potential advantages, spintronics still faces some challenges, such as, generate high spin injectors. However, the discovery of half-metallic ferrimagnet has improved this problem, which is an ideal semiconductor spin-injection source due to it has 100% spin polarizability. Among different halfmetallic materials, Heusler alloys are prominent especially owing to high Curie temperature and flexible electronic structures [1,2]. Since De Groot et al. [3] discovered the half-metallic ferromagnets of NiMnSb, while they were calculating the energy band using the planewave method, this intermetallic materials with unusual electronic structures arouse people’s attention. In the big family of Heusler alloys, Co-based Heusler alloys [4–6] usually show magnetism, and the source of this property is direct interaction between Co-Co atoms. Cu-based Heusler alloys [7–9] are typical representative of non-magnetic elements show ferromagnetic after high-ordered, Pd-based Heusler alloys [10,11] which contain rareearth elements is superconducting, Ni2Mn-based Heusler alloys [12–17] have both ferromagnetic properties and thermoelastic martensitic transformation, which realizing magnetic-field-induced strain, shape memory effect, magnetoresistance effect and other application functions. At present, most research focuses on ternary Mn-based Heusler alloys, and they usually behave ferromagnetic or ferromagnetic [18–21]. Actually, besides half-metallic ferromagnets and ferrimagnets, half-metallic antiferromagnets also worthy of study. Not only it has 100% spin polarizability, but its total magnetic moment is zero. Thus, it means that when HM-AFMs are applied to spintronic devices, and those alloys will get the feature of the low-stray field and low energy loss. HM-AFMs were discovered in Heusler alloys [22] and perovskite compounds [23]. Besides, the martensitic transformation was found in some Mn-based Heusler alloys [24–26].

7-1- Non-Power Applications

7-2- Scientific Applications

7-3- Medical and Biological Applications

7-4- Industrial Applications

7-5- Food Processing and Agriculture

References

Abstract

Non-power applications of nuclear energy are briefly reviewed. Scientific applications are noted such as dating geological formations, minerals and historical artefacts, and radionuclide labelling to study biological, chemical and physical processes. Medical applications are considered with unsealed and sealed sources of radiation used both in therapy and diagnosis. Utilisation of nuclear energy is described in various industrial applications and food processing.

NON-POWER APPLICATIONS

Nuclear energy is an important source of CO2-free baseload electricity providing an excellent alliance with renewables which need underpinning baseload for when the wind does not blow or the sun shine. However, nuclear applications are not just limited to power generation. The nonpower uses of nuclear energy include many useful applications in science, medicine, industry, food preservation and agriculture. Applications use either radiations such as in accelerators and gamma irradiators or a combination of chemical properties and radiations emitted by radionuclides such as in radioactive tracers and radiopharmaceuticals (Tsoulfanidis, 2018). During the use of nuclear energy radioactive waste can be generated, which must be managed with particular care owing to its inherent radiological, biological, chemical and physical hazards. Producers and users of radioactive materials must be sure that a waste management strategy exists prior to the start of waste generation (IAEA, 2017a).

A novel clustering algorithm by fast search and find of density peaks (DP) was proposed in Science, 2014. It has attracted much attention from researchers. It can easily select clusters centers with decision graph. However, it cannot be used to cluster manifold data sets as the existing distance measurement is not suitable to evaluate the dissimilarity between objects on manifold structure. Some researchers use graph-based distance to measure the dissimilarity between objects on manifold clusters, but computing the graph-based distance on the original data set is time consuming. An improved density peaks clustering algorithm based on shared-neighbors between local cores, SLORE-DP, is proposed in this paper. First, it finds local cores to represent the data set and redefines the graph-based distance between local cores with sharedneighbors-based distance. Then natural neighbor-based density and the new defined graph-based distance are used to construct decision graph on local cores and DP algorithm is employed to cluster local cores. Finally, the remaining points are assigned to the same cluster as their local cores belong to. Since we use the new defined graph-based distance to estimate the dissimilarity between local cores, SLORE-DP can be used to cluster manifold data sets and at the same time it only calculates the shortest path between local cores, which greatly reduces the running time of the algorithm. We do experiments on several synthetic data sets containing manifold clusters and several real data sets from UCI. The results show that SLORE-DP is more effective and efficient than other algorithms when clustering manifold data sets.

Introduction

As an unsupervised learning, clustering is an important method for data analysis. It has been widely used in the field of pattern recognition, image processing, and information retrieval. It is designed to divide objects into multiple clusters, so that similar objects are in the same cluster while different objects are in different clusters. Many clustering algorithms have been proposed over the past few decades. According to different strategies, these algorithms can be roughly grouped into partitioning methods, density-based methods, hierarchical methods, model-based methods and grid-based methods. Among them, partitioning, density-based and hierarchical algorithms, due to their simple principle, are the most popular. K-means [1] and K-medoids [2] are typical partitioning algorithms. However, their performance depends on the selection of initial cluster centers. To avoid selecting cluster centers, AP algorithm [3] treats all objects as potential centers. K-AP [4] is an improved AP algorithm. It uses the immediate result of K clusters by introducing a constraint in the process of message passing. However, since each point is always allocated to the nearest center, these algorithms cannot discover arbitrary-shaped clusters. DBSCAN [5] is a typical density-based clustering algorithm. It defines clusters as dense regions separated by sparse regions. Dcore [6] is a hybrid decentralized approach which is based on finding density cores instead of centroids.

1. Introduction

2. Experimental fatigue tests on scotch yokes

3. Fatigue test results

4. FE stress analyses

5. Methodologies for fatigue strength assessment of scotch yokes

6. Conclusions

7. Acknowledgments

8. References

Aim of this work is the fatigue assessment of a main component, termed scotch yoke, of a valve actuator used for oil & gas, power and chemical industries, in order to comply with its heavy-duty applications. To do this, full-scale specimens of the scotch yoke made of structural steel have been fatigue tested under nominal axial loading. All specimens have been tested under stress-relieved conditions by adopting a nominal load ratio R=-1. After experimental tests, the fatigue crack paths have been analysed by means of liquid penetrant inspections. The fatigue strength class of the considered scotch yoke has been determined by statistically re-analysing the experimental results, expressed in terms of range of the nominal applied load, and it has been compared with the design condition required by the relevant European Standard, EN 15714-3/4. Finally, two methodologies for fatigue strength assessment of the considered scotch yokes have been proposed, which are based on experimental fatigue data derived from smooth or sharp V-notched specimens, respectively, made of the same yoke material. The assessment capability of the proposed methodologies has been evaluated and discussed by comparing theoretical estimations with the experimental fatigue results of the scotch yokes.

Introduction

Pneumatic scotch yoke valve actuators are commonly used in many industrial sectors for different applications. High-cycle applications are among the most challenging scenarios for heavy-duty actuation, which impose high frequency of operation often at relatively high operating speed. The LPS actuator series, see an example in Fig. 1, are mainly adopted in the Oil&Gas field and are able to provide a very high torque output. They are currently designed by FLOWSERVE – Limitorque according to the relevant European Standard, i.e. EN 15714-3/4 [1], which requires actuators to operate for a minimum number of cycles as a function of the nominal output torque. The required minimum number of cycle could be very different, even by some orders of magnitude. As an example, dealing with the Limitorque actuator model LPS-15, which is designed for a nominal output torque of 6000 Nm, the minimum number of cycles required by the Standard [1] is equal to 105 . However, in high-cycle applications sometimes required also from chemical sector, customers frequently ask for actuators operating at least for 2 million cycles. Accordingly, the adoption of standard actuator series for a wide range of applications inevitably leads to an oversize and an increase of the cost of the project, which corresponds to a decrease of the competitiveness on the global market. This issue can be addressed by adopting a validated design and by optimizing the actuator construction features, in order to guarantee the number of cycles required by Standards while avoiding an oversizing of the actuator.

Separation becomes a bottleneck of dealing with the enormous stream of waste plastics, as most of the extant methods can only handle binary mixtures. In this paper, a novel method that based on magnetic levitation was proposed for separating multiple mixed plastics. Six types of plastics, i.e., polypropylene (PP), acrylonitrile butadiene styrene (ABS), polyamide 6 (PA6), polycarbonate (PC), polyethylene terephthalate (PET), and polytetrafluoroethylene (PTFE), were used to simulate the mixed waste plastics. The samples were mixed and immersed into paramagnetic medium that placed into a magnetic levitation configuration with two identical NdFeB magnets with like-poles facing each other, and Fourier transform infrared (FTIR) spectroscopy was employed to verify the separation outputs. Unlike any conventional separation methods such as froth flotation and hydrocyclone, this method is not limited by particle sizes, as mixtures of different size fractions reached their respective equilibrium positions in the initial tests. The two-stage separation tests demonstrated that the plastics can be completely separated with purities reached 100%. The method has the potential to be industrialised into an economically-viable and environmentally-friendly mass production procedure, since quantitative correlations are determined, and the paramagnetic medium can be reused indefinitely.

Introduction

Massive global production of plastics, e.g., 322 M tonnes in 2015, has resulted in an ever-increasing stream of waste plastics (PlasticsEurope, 2016). Owning to less environmental burdens and economic feasibility, mechanical recycling of waste plastics or plastic recycling is becoming a promising practise in dealing with this particular waste stream (see Gu et al., 2014, 2016a,b, 2017a; Biganzoli et al., 2015; Wäger and Hischier, 2015; Ripa et al., 2017; Zheng et al., 2017). Recycled plastics possess comparable performance and advantageous prices to their virgin counterparts (Gu et al., 2016a), and have already been applied in the manufacturing sector (Gu et al., 2016b, 2017a). Plastic recycling is also one of the major sources of environmental benefits in waste management systems (Biganzoli et al., 2015; Wäger and Hischier, 2015; Ripa et al., 2017). However, although plastic recycling enjoys a rapid growth in recent years, most of waste plastics are still sent to landfill or incineration (PlasticsEurope, 2016). In reported cases of plastic recycling, only waste plastics of certain types and sources are recycled. For example, in the municipal solid waste (MSW) management system of Naples, only polyethylene (PE), polypropylene (PP) and polyethylene terephthalate (PET) get mechanically recycled while the mix plastics are recovered as fuels or directly end up in landfill (Ripa et al., 2017). Some Chinese plastic recycler only takes sorted waste plastics from factories or dismantling sites (Gu et al., 2017a). From a brief review of the extant literature, it can be deduced that the technology of separating mixed waste plastics is highly desirable for promoting the rate of plastic recycling, as most current practises cannot handle this particular type of MSW. Since separation of mixed plastics poses a difficult challenge to promoting mechanical recycling of plastics, the field thereby attracts a great deal of attention from academics. Froth flotation is one intensively studied plastic separation technology (see Guney et al., 2013; Wang et al., 2014, 2015, 2017a,b; Zhao et al., 2015; Censori et al., 2016; Truc and Lee, 2016, 2017; Pita and Castilho, 2017; Salerno et al., 2018; Wang and Wang, 2017). Froth flotation exploits tiny density differences between materials (Censori et al., 2016), yet, this technology primarily focuses on separating desirable types of plastics from binary mixtures, e.g., separating polyvinyl chloride (PVC) from mixtures like PVC/polystyrene (PS) (Salerno et al., 2018), PVC/PET (Guney et al., 2013), PVC/acrylonitrile butadiene styrene (ABS) (Wang et al., 2017b; Wang and Wang, 2017), PVC/polycarbonate (PC) or PVC/polymethylmethacrylate (PMMA) (Wang et al., 2017a), or separating PS from PS/PMMA, PS/PET, and PS/PVC (Pita and Castilho, 2017).

Abstract

An exploration into the origin of chemoselectivity in the NHC-catalyzed cross-benzoin reaction reveals several key factors governing the preferred pathway. In the first computational study to explore the cross-benzoin reaction, a piperidinonederived triazolium catalyst produces kinetically controlled chemoselectivity. This is supported by 1 H NMR studies as well as a series of crossover experiments. Major contributors include the rapid and preferential formation of an NHC adduct with alkyl aldehydes, a rate-limiting carbon−carbon bond formation step benefiting from a stabilizing π-stacking/π-cation interaction, and steric penalties paid by competing pathways. The energy profile for the analogous pyrrolidinone-derived catalyst was found to be remarkably similar, despite experimental data showing that it is less chemoselective. The chemoselectivity could not be improved through kinetic control; however, equilibrating conditions show substantial preference for the same cross-benzoin product kinetically favored by the piperidinone-derived catalyst.

Introduction

Originally reported in 1832 by Wö hler and Liebig, the benzoin reaction is the coupling of two aldehydes to form an acyloin. The groups of Ukai and Breslow described how thiazolium salts could also catalyze this reaction in the presence of base. Much later, other N-heterocyclic carbene (NHC) catalysts were shown to effect the same transformation. Breslow proposed the currently accepted mechanism, based on analogy to Lapworth’s mechanism for the cyanide-catalyzed benzoin reaction (Scheme 1).

First, deprotonation of the salt (I) generates the active carbene catalyst (II). This nucleophilic species then attacks 1 equiv of aldehyde, generating an intermediate (III) that is rapidly protonated to form a carbene−aldehyde adduct (IV). Deprotonation of this adduct generates a resonance-stabilized zwitterion now referred to as the Breslow intermediate (V). This species is crucial to the reaction, as it induces a reversal of polarity (umpolung), making the previously electrophilic carbonyl carbon nucleophilic. The Breslow intermediate then attacks another 1 equiv of aldehyde and undergoes a proton transfer that is either concerted or stepwise ([V-VI]). Collapse of this species (VI) releases the benzoin (acyloin) product and reintroduces the catalyst into the cycle.

Sugar cane molasses is most important raw materials for production of alcohols and amino acids in fermentation industries. However, after use of raw materials, a large quantity (8–15 L of wastewater for every liter of alcohol production) of wastewater is discharged which creates serious environmental issues [1]. The molasses based distillery industries wastewater contains high organic matter in terms of Chemical Oxygen Demand (COD: 65,000–13,0000 mg/L), high concentration of minerals, dark brown color, and burnt sugar odor [2]. Several methods includes chemical, electrochemical, biological (aerobic and anaerobic) methods have been exploited for the treatment and disposal of molasses wastewater [3]. Conventionally, an anaerobic digestion method is used for treating such waste and generates methane gas followed by an aerobic treatment prior to disposal [4]. An intensive conventional wastewater treatment system are required to develop an alternative technology which should be reliable, cost effective and also energy recovery. Microbial fuel cell (MFC) is a novel bio-electrochemical system that generates bioelectricity and simultaneously removes pollutant such as COD, color, salinity etc. from wastewater which is one of the most advantageous [5–7]. The MFC consists of biotic anode and abiotic cathode chamber separated by a proton exchange membrane (PEM). The potential developed between metabolic respiration on electron donors and electron acceptors conditions in the anode and cathode generates electricity and water [8]. Earlier, the MFC was operated using pure organic matter such as glucose, acetate and lactose as a substrate to understand the fundamental of process [9,10]. Nowadays more complex substrates (dairy, domestic, starch processing, and paper recycling wastewater etc.) have been used to improve the performance and exploiting the waste into useful product [11–14]. Though, the molasses based distillery wastewater containing high organic matter that provides a great potential source for electricity generation. Additionally, the MFC used sulfide (that generated during the anaerobic process) as a fuel to generate electricity and oxidize sulfide into elemental sulfur [15]. In recent year, the MFC performance was enhanced by varying the operational and design parameters such as reactor configuration, electrode material, electrode distance, pH, microbial communities and substrate concentration etc. [16–19]. Nevertheless, the wastewater feed pH played a significant role on overall performance in dual chamber MFC, because it controls not only bacterial growth and also supports an efficient movement of protons through PEM. Generally, bacteria respond to change internal and external pH by adjusting their activity associated with many different processes, including proton translocation, amino acid degradation, adaptation to acidic or basic conditions [20]. Since, the wastewater pH in anode chamber should be identified to enhance power generation in the MFC. Mohanakrishna et al. [21] evaluated the MFC performance with distillery wastewater by keeping at acidic environment. Ha et al. [22] adjusted the distillery wastewater at pH 7 using buffer for evaluating the performance using bacteroidetes dominant thermophilic MFC.

The fundamental diagram (FD), that is bivariate equilibrium relationships of traffic flow (q), speed (v), and density (ρ), is of great importance in analysis of traffic flow and modeling of traffic behavior. For example, the concept of level of service for a highway relies on input from the speed–flow relationship (TRB 2010). The flow–density relationship is central in many investigations associated with traffic flow dynamics (Daganzo 1995). In high-order traffic flow models (Messmer and Papageorgiou 1990; Kotsialos et al. 2002), the speed–density relationship plays an important role. However, among the three ‘pairwise’ relationships (e.g. speed–density, flow–density, and speed–flow), the speed–density relationship appears to be challenging as it encapsulates a direct connection to everyday driving behavior. Traffic flow in the real world is characterized by heterogeneous driving experience, i.e. perturbation in speed choice influenced by the surrounding vehicles. Therefore, a speed–density model that better captures these effects is demanded for traffic flow analysis and efficient traffic control. Modeling of the speed–density relationship began with the Greenshields’ linear model in the seminal paper: A Study in Highway Capacity (Greenshields 1935). This seminal work has inspired a slew of new models (Greenberg 1959; Underwood 1961; Pipes 1967; Drew 1968) which propose a variety of mathematical models containing several parameters. The values of these parameters are estimated by fitting these models to empirical traffic data. A comprehensive explanation of the parameters in terms of traffic flow dynamics is then developed to endow the mathematical model with a phenomenological interpretation. However, these models are limited in the sense that they try to fit the traffic dynamics to a definite shape (i.e. logarithmic, exponential, and exponential to the quadratic and various forms of polynomials). Nevertheless, a live transportation system is dictated by traffic streams with dynamical randomness effects, which result from heterogeneity in both vehicle attributes and driver preferences. For example, in a multimodal system, passenger cars, trucks, and public transportation travel in the same right-of-way. The difference in vehicle dynamics necessarily endows them with heterogeneous gap maintaining behavior, lateral movement and longitudinal motion, and lanes to travel on. As another example, drivers demonstrate heterogeneous driving behavior, e.g. minimum headway distances to keep when following leading vehicles, frequency in applying brakes, fluctuation in arrival pattern, etc. These lead to a complex traffic dynamics, which cannot be replicated by conventional speed–density models. To address this phenomenon, the proposed model must have sufficient shape flexibility to be fitted accurately to the measured field data (MacNicholas 2008). A number of studies suggest that changes in behavior of the leading vehicle cause fluctuations in the reaction of drivers; this phenomenon causes traffic flow instability (Chandler, Herman, and Montroll 1958; Kometani and Sasaki 1961). At low densities, vehicle interactions are occasional and the drivers travel at their most comfortable speed. This leads to a stable traffic flow and, therefore, there are no substantial speed drops. This type of traffic flow pattern corresponds to a density range from 0 to 32 vehicle/mile/lane (del Castillo 2001). Near critical density, the interaction between drivers becomes pivotal to maintain stability of traffic flow. In particular, it has been observed that drivers vary their choice in speed and spacing selection somewhat randomly between two branches in the flow–density FD. It is assumed that drivers continuously vary their spacing and seek for lane-changing opportunities (Kerner 2004).