Phase Diagram of the One Dimensional S=1/2S=1/2 XXZXXZ model with Ferromagnetic nearest-neighbor and Antiferromagnetic next-nearest neighbor interactions

We have studied the phase diagram of the one dimensional $S=1/2$ $XXZ$ model with ferromagnetic nearest-neighbor and antiferromagnetic next-nearest neighbor interactions. We have applied the quantum renormalization group (QRG) approach to get the stable fixed points and the running of coupling constants. The second order QRG has been implemented to get the self similar Hamiltonian. This model shows a rich phase diagram which consists of different phases which possess the quantum spin-fluid and dimer phases in addition to the classical N\'{e}el and ferromagnetic ones. The border between different phases has been shown as a projection onto two different planes in the phase space

Dualities in Spin Ladders

We introduce a set of discrete modular transformations $T_\ell,U_\ell$ and $S_\ell$ in order to study the relationships between the different phases of the Heisenberg ladders obtained with all possible exchange coupling constants. For the 2 legged ladder we show that the $RVB$ phase is invariant under the $S_\ell$ transformation, while the Haldane phase is invariant under $U_\ell$. These two phases are related by $T_\ell$. Moreover there is a "mixed" phase, that is invariant under $T_\ell$, and which under $U_\ell$ becomes the RVB phase, while under $S_\ell$ becomes the Haldane phase. For odd ladders there exists only the $T_\ell$ transformation which, for strong coupling, maps the effective antiferromagnetic spin 1/2 chain into the spin 3/2 chain.Comment: REVTEX file, 5 pages, 2 EPS figure

Recently fixed carbon fuels microbial activity several meters below the soil surface

This data file (Scheibe_2022.xlsx) contains radiocarbon data of bulk soil carbon and CO2 respired in incubations from soil profiles in three climate zones (arid, mediterranean, and humid) of the Costal Cordillera of Chile down to a depth of six meters. Variable descriptions are provided in Template Info File. The data are part of a study, which investigates how soil microbial carbon cycling affects soil formation especially in the critical zone by understanding the carbon source of microbial activity in deep soil. The study was conducted within the framework of the Deep EarthShape priority program funded by the German Science Foundation (DFG-SPP 1803)

Developing the framework for multi-criteria assessment of smart local energy systems

In response to the climate emergency, energy landscapes are rapidly shifting to cleaner, decentralised smart local energy systems (SLESs). SLES will facilitate connection of transport, heat and power through flexible energy supply, demand and storage options supported by digital technology. SLESs are expected to contribute to tackling the energy trilemma (cost, security and sustainability), but there is also scope for them to offer many co-benefits aligned with the United Nations (UN) Sustainable Development Goals (SDGs). These benefits may drive for ongoing political and financial investment in SLES; therefore, there’s a need to indicate how a SLES is performing over time relative to each of them. Currently, there is no standardised approach to evaluate SLES and most of the existing techno-socio-economic tools have limited scope to assess the complex multiple performance indices, scenarios and stakeholders. The Innovate UK-funded EnergyREV research consortium is developing a multi-criteria assessment tool (MCA) for SLES. This paper describes the first step in this process – developing a simplified and standardised framework for assessing the performance of the system and the realization of benefits. It explores existing protocols and stakeholder opinion to identify 50 potential factors that are important in monitoring the system performance. These are clustered into 10 key themes to create a taxonomy for SLES performance that are aligned with relevant UN SDGs to track wider co-benefits. The resulting MCA tool will be instrumental to project stakeholders in providing evidence to support performance claims and identifying potential benefits beyond targeted key performance indicators