Concepts and microstructure design for multicaloric cooling using Ni-Mn-based Heusler compounds

The world’s rising population as well as environmental and economic changes go hand in hand with an increasing need for sustainable and energy-efficient cooling solutions. The most promising alternative to currently used vapor-compression technology is solid-state caloric cooling which utilizes the giant thermal response to an external field in vicinity of first-order phase transitions. However, there are still several limitations such as irreversibilities and energy losses during cyclic operation as well as the necessity of a rather large external field which hamper its application. The utilization of more than one external field which is known as multicaloric cooling, promises to overcome these limitations. For this purpose, materials with a pronounced cross-response to multiple stimuli are required. In this work, metamagnetic Ni-Mn-based Heusler compounds are investigated with respect to their multicaloric properties under magnetic fields and uniaxial stress. Different combinations of the two external stimuli are explored and the influence of microstructure on the caloric response and mechanical stability is investigated. It is demonstrated that a suitable combination of magnetic field and uniaxial stress can enable a significant improvement of the magnitude and reversibility of the caloric effect as compared to its single caloric counterparts. Moreover, a strong influence of microstructural features like precipitates, grain diameter and texture on the functional and mechanical performance is revealed. It is shown that a tailored microstructure design in metamagnetic Ni-Mn-based Heusler allows to simultaneously achieve excellent caloric and mechanical properties

Multicaloric effects in metamagnetic Heusler Ni-Mn-In under uniaxial stress and magnetic field

The world's growing hunger for artificial cold, on the one hand, and the ever more stringent climate targets, on the other, pose an enormouschallenge to mankind. Novel, efficient, and environmentally friendly refrigeration technologies based on solid-state refrigerants can offer away out of the problems arising from climate-damaging substances used in conventional vapor-compressors. Multicaloric materials standout because of their large temperature changes, which can be induced by the application of different external stimuli such as a magnetic, elec-tric, or a mechanical field. Despite the high potential for applications and the interesting physics of this group of materials, few studies focuson their investigation by direct methods. In this paper, we report on the advanced characterization of all relevant physical quantities thatdetermine the multicaloric effect of a Ni-Mn-In Heusler compound. We have used a purpose-designed calorimeter to determine the isother-mal entropy and adiabatic temperature changes resulting from the combined action of magnetic field and uniaxial stress on this metamag-netic shape-memory alloy. From these results, we can conclude that the multicaloric response of this alloy by appropriate changes of uniaxialstress and magnetic field largely outperforms the caloric response of the alloy when subjected to only a single stimulus. We anticipate thatour findings can be applied to other multicaloric materials, thus inspiring the development of refrigeration devices based on the multicaloriceffect

Tailoring magnetocaloric effect in all-d-metal Ni-Co-Mn-Ti Heusler alloys: a combined experimental and theoretical study

Novel Ni-Co-Mn-Ti all-d-metal Heusler alloys are exciting due to large multicaloric effects combined with enhanced mechanical properties. An optimized heat treatment for a series of these compounds leads to very sharp phase transitions in bulk alloys with isothermal entropy changes of up to 38 J kg$^{-1}$ K$^{-1}$ for a magnetic field change of 2 T. The differences of as-cast and annealed samples are analyzed by investigating microstructure and phase transitions in detail by optical microscopy. We identify different grain structures as well as stoichiometric (in)homogenieties as reasons for differently sharp martensitic transitions after ideal and non-ideal annealing. We develop alloy design rules for tuning the magnetostructural phase transition and evaluate specifically the sensitivity of the transition temperature towards the externally applied magnetic fields ($\frac{dT_t}{\mu_0dH}$) by analyzing the different stoichiometries. We then set up a phase diagram including martensitic transition temperatures and austenite Curie temperatures depending on the e/a ratio for varying Co and Ti content. The evolution of the Curie temperature with changing stoichiometry is compared to other Heusler systems. Density Functional Theory calculations reveal a correlation of T$_C$ with the stoichiometry as well as with the order state of the austenite. This combined approach of experiment and theory allows for an efficient development of new systems towards promising magnetocaloric properties. Direct adiabatic temperature change measurements show here the largest change of -4 K in a magnetic field change of 1.93 T for Ni$_{35}$Co$_{15}$Mn$_{37}$Ti$_{13}$

High‐Throughput Design of Magnetocaloric Materials for Energy Applications: MM´X alloys

Magnetic refrigeration offers an energy efficient and environmental friendly alternative to conventional vapor‐cooling. However, its adoption depends on materials with tailored magnetic and structural properties. Here a high‐throughput computational workflow for the design of magnetocaloric materials is introduced. Density functional theory calculations are used to screen potential candidates in the family of MM'X (M/M’ = metal, X = main group element) compounds. Out of 274 stable compositions, 46 magnetic compounds are found to stabilize in both an austenite and martensite phase. Following the concept of Curie temperature window, nine compounds are identified as potential candidates with structural transitions, by evaluating and comparing the structural phase transition and magnetic ordering temperatures. Additionally, the use of doping to tailor magnetostructural coupling for both known and newly predicted MM'X compounds is predicted and isostructural substitution as a general approach to engineer magnetocaloric materials is suggested

How Unique do we Move? : Understanding the Human Body and Context Factors for User Identification

Past work showed great promise in biometric user identification and authentication through exploiting specific features of specific body parts. We investigate human motion across the whole body, to explore what parts of the body exhibit more unique movement patterns, and are more suitable to identify users in general. We collect and analyze full-body motion data across various activities (e.g., sitting, standing), handheld objects (uni- or bimanual), and tasks (e.g., watching TV or walking). Our analysis shows, e.g., that gait as a strong feature amplifies when carrying items, game activity elicits more unique behaviors than texting on a smartphone, and motion features are robust across body parts whereas posture features are more robust across tasks. Our work provides a holistic reference on how context affects human motion to identify us across a variety of factors, useful to inform researchers and practitioners of behavioral biometric systems on a large scale

Tailoring Negative Thermal Expansion via Tunable Induced Strain in La–Fe–Si-Based Multifunctional Material

Zero thermal expansion (ZTE) composites are typically designed by combining positive thermal expansion (PTE) with negative thermal expansion (NTE) materials acting as compensators and have many diverse applications, including in high-precision instrumentation and biomedical devices. La(Fe1–x,Six)13-based compounds display several remarkable properties, such as giant magnetocaloric effect and very large NTE at room temperature. Both are linked via strong magnetovolume coupling, which leads to sharp magnetic and volume changes occurring simultaneously across first-order phase transitions; the abrupt nature of these changes makes them unsuitable as thermal expansion compensators. To make these materials more useful practically, the mechanisms controlling the temperature over which this transition occurs and the magnitude of contraction need to be controlled. In this work, ball-milling was used to decrease particles and crystallite sizes and increase the strain in LaFe11.9Mn0.27Si1.29Hx alloys. Such size and strain tuning effectively broadened the temperature over which this transition occurs. The material’s NTE operational temperature window was expanded, and its peak was suppressed by up to 85%. This work demonstrates that induced strain is the key mechanism controlling these materials’ phase transitions. This allows the optimization of their thermal expansion toward room-temperature ZTE applications

Altered grey matter networks in young patients with MS at genetic risk for Alzheimer's disease [Abstract]

Background: The Apolipoprotein E (APOE) ε4 is the major susceptibility factor for cognitive impairment and Alzheimer’s disease. Cognitive decline is also a concern in patients with multiple sclerosis (MS). Whether APOE ε4 exerts an effect on brain structure and grey matter (GM) networks in MS patients that could potentiate the long-term cognitive disabilities is unclear. Moreover the description of the exact link between genetic markers and MR driven measures of brain integrity are of essential importance to study cognition in patients with MS and for interventions to prevent longitudinal deterioration. Methods: MS Patients with no immunomodulatory treatment were enrolled in the “Krankheitsbezogene Kompetenznetz Multiple Sclerosis (KKNMS)”. From this multicenter dataset 37 heterozygous APOE ε4 carriers (i.e. having the genotype ε3/ε4) and 37 non-carriers (ε3/ε3) were matched for demographics (mean age: 38.4±9.2 yrs, mean EDSS 1.23±0.99) from one site. A replication study was performed in a cohort (n=46) from a second site. Cortical thickness (CT) was derived from 3T MRI using FreeSurfer. GM connectivity networks were reconstructed from the CT correlation between the 68 regions of the Desikan-Killiany atlas. Cortical integrity and network connectivity -derived from graph theoretical approaches- were compared between the groups in both cohorts. Results corrected for multiple comparisons were considered (p< 0.05 FDR). Results: No regional or global cortical atrophy differences were attested between the two groups in both cohorts. In the network connectivity analysis a decreased local connectivity pattern (reduced transitivity, t=-3.24 p=0.008) was evident in APOE ε4 carriers. Regions with decreased connectivity were consistently seen in the medial part of the left temporal lobe. APOE ε4 status was further associated with raised whole brain connectivity, reflected by increased global efficiency (t=4.34 p=0.005) and reduced modularity (t=-2.84 p=0.02). This network pattern was shown in the frontal, parietal and lateral temporal associative cortices. The results were entirely replicated in the second cohort. Conclusion: We found that MS patients at genetic risk for cognitive decline have significant abnormalities of local GM networks and possibly compensatory increased long-range connectivity patterns. Chronic or focal neuroinflammation could lead to behaviourally relevant memory impairments in these patients through a specific break-down of the long-range paths

K(2P)18.1 translates T cell receptor signals into thymic regulatory T cell development

It remains largely unclear how thymocytes translate relative differences in T cell receptor (TCR) signal strength into distinct developmental programs that drive the cell fate decisions towards conventional (Tconv) or regulatory T cells (Treg). Following TCR activation, intracellular calcium (Ca2+) is the most important second messenger, for which the potassium channel K(2P)18.1 is a relevant regulator. Here, we identify K(2P)18.1 as a central translator of the TCR signal into the thymus-derived Treg (tTreg) selection process. TCR signal was coupled to NF-kappa B-mediated K(2P)18.1 upregulation in tTreg progenitors. K(2P)18.1 provided the driving force for sustained Ca2+ influx that facilitated NF-kappa B- and NFAT-dependent expression of FoxP3, the master transcription factor for Treg development and function. Loss of K(2P)18.1 ion-current function induced a mild lymphoproliferative phenotype in mice, with reduced Treg numbers that led to aggravated experimental autoimmune encephalomyelitis, while a gain-of-function mutation in K(2P)18.1 resulted in increased Treg numbers in mice. Our findings in human thymus, recent thymic emigrants and multiple sclerosis patients with a dominant-negative missense K(2P)18.1 variant that is associated with poor clinical outcomes indicate that K(2P)18.1 also plays a role in human Treg development. Pharmacological modulation of K(2P)18.1 specifically modulated Treg numbers in vitro and in vivo. Finally, we identified nitroxoline as a K(2P)18.1 activator that led to rapid and reversible Treg increase in patients with urinary tract infections. Conclusively, our findings reveal how K(2P)18.1 translates TCR signals into thymic T cell fate decisions and Treg development, and provide a basis for the therapeutic utilization of Treg in several human disorders.Peer reviewe

On the Automaticity of Language and Instruction

There is an ongoing debate on how the meaning of words is retrieved in a newly-learned language L2. Two processes are assumed: L2 words retrieve underlying concepts via associations with the corresponding words in the first language, L1, (word association hypothesis) or L2 words gain direct access to underlying concepts (concept mediation hypothesis). It is commonly shown that a higher language proficiency is needed to access word meanings directy via concepts. However, evidence for newly learning words and novices is scarce. Using an item-specific priming paradigm, we demonstrated that classes and actions (e.g., “small, right!”) merely instructed during an item’s prime led to repetition priming effects (i. e., reduced reaction times for class/action mapping repetitions) in the item’s subsequent probe (lag 2-7 trials). Crucially, this was the case to a comparable degree both when participants were instructed in L1 and when they were instructed in an L2 which they had no knowledge of prior to a brief practice phase at the beginning of the experiment. These findings provide clear support that the direct route to concepts can be accessed already in the very beginning of language learning and highlight how fast newly-learned words become able to automatize behavior

Evaluating Investments in Flexible On-Demand Production Capacity. A Real Options Approach

Ongoing digitalization of production accelerates trends like mass customization, ever shorter lead times, and shrinking product life cycles. Thereby, industrial companies face increasingly volatile demand that complicates an appropriate production capacity planning. On the other hand, the comprehensive digitalization of production environments favors, amongst others, the dynamic integration of flexible external on-demand production capacity provided by specialized external capacity providers (ECPs). To enable the usage of on-demand production capacity, industrial companies may require significant upfront investments (e.g., for inter-organizational information systems, planning and organizational processes, employee training). The objective of this paper is to develop a model that evaluates such enabling upfront investments from the perspective of a manufacturing company. To consider flexibility of action, we apply real options analysis in a discrete-time binomial tree model and weigh these so-called expansion options to related cash outflows. In addition, we evaluate our model by means of a simulation and sensitivity analyses and derive insights for both researchers and practitioners. The insights gained by our model present a profound economic basis for investment decisions on upfront investments in flexible on-demand production capacity