Secondary Electron Emission Beam Loss Monitor for LHC

Beam Loss Monitoring (BLM) system is a vital part of the active protection of the LHC accelerators' elements. It should provide the number of particles lost from the primary hadron beam by measuring the radiation field induced by their interaction with matter surrounding the beam pipe. The LHC BLM system will use ionization chambers as standard detectors but in the areas where very high dose rates are expected, the Secondary Emission Monitor (SEM) chambers will be employed because of their high linearity, low sensitivity and fast response. The SEM needs a high vacuum for proper operation and has to be functional for up to 20 years, therefore all the components were designed according to the UHV requirements and a getter pump was included. The SEM electrodes are made of Ti because of its Secondary Emission Yield (SEY) stability. The sensitivity of the SEM was modeled in Geant4 via the Photo-Absorption Ionization module together with custom parameterization of the very low energy secondary electron production. The prototypes were calibrated by proton beams in CERN PS Booster dump line, SPS transfer line and in PSI Optis line. The results were compared to the simulations

Classification of the LHC BLM Ionization Chamber

The LHC beam loss monitoring (BLM) system must prevent the super conducting magnets from quenching and protect the machine components from damage. The main monitor type is an ionization chamber. About 4000 of them will be installed around the ring. The lost beam particles initiate hadronic showers through the magnets and other machine components. These shower particles are measured by the monitors installed on the outside of the accelerator equipment. For the calibration of the BLM system the signal response of the ionization chamber is simulated in GEANT4 for all relevant particle types and energies (keV to TeV range). For validation, the simulations are compared to measurements using protons, neutrons, photons and mixed radiation fields at various energies and intensities. This paper will focus on the signal response of the ionization chamber to various particle types and energies including space charge effects at high ionization densities

LHC Beam Loss Detector Design: Simulations and Measurements

The Beam Loss Monitoring (BLM) system is integrated in the active equipment protection system of the LHC. It determines the number of particles lost from the primary hadron beam by measuring the radiation field of the shower particles outside of the vacuum chamber. The LHC BLM system will use ionization chambers as its standard detectors but in the areas where very high dose rates are expected, the Secondary Emission Monitor (SEM) chambers will be additionally employed because of their high linearity, low sensitivity and fast response.The sensitivity of the SEM was modeled in Geant4 via the Photo-Absorption Ionization module together with custom parameterization of the very low energy secondary electron production. The prototypes were calibrated by proton beams. For the calibration of the BLM system the signal response of the ionization chamber is simulated in Geant4 for all relevant particle types and energies (keV to TeV range). The results are validated by comparing the simulations to measurements using protons, neutrons, photons and mixed radiation fields at various energies and intensities

Generation of 1.5 Million Beam Loss Threshold Values

CERN's Large Hadron Collider will store an unprecedented amount of energy in its circulating beams. Beamloss monitoring (BLM) is, therefore, critical for machine protection. It must protect against the consequences (equipment damage, quenches of superconducting magnets) of excessive beam loss. About 4000 monitors will be installed at critical loss locations. Each monitor has 384 beam abort thresholds associated; for 12 integrated loss durations ($40\mu$s to 83 s) and 32 energies (450GeV to 7 TeV). Depending on monitor location, the thresholds vary by orders of magnitude. For simplification, the monitors are grouped in 'families'. Monitors of one family protect similar magnets against equivalent loss scenarios. Therefore, they are given the same thresholds. The start-up calibration of the BLM system is required to be within a factor of five in accuracy; and the final accuracy should be a factor of two. Simulations (backed-up by control measurements) determine the relation between the BLM signal, the deposited energy and the critical energy deposition for damage or quench (temperature of the coil). The paper presents the strategy of determining 1.5 million threshold values

The LHC Beam Loss Measurement System

An unprecedented amount of energy will be stored in the circulating beams of LHC. The loss of even a very small fraction of a beam may induce a quench in the superconducting magnets or cause physical damage to machine components. A fast (one turn) loss of 3 . 10-9 and a constant loss of 3 . 10-12 times the nominal beam intensity can quench a dipole magnet. A fast loss of 3 . 10-6 times nominal beam intensity can damage a magnet. The stored energy in the LHC beam is a factor of 200 (or more) higher than in existing hadron machines with superconducting magnets (HERA, TEVATRON, RHIC), while the quench levels of the LHC magnets are a factor of about 5 to 20 lower than the quench levels of these machines. To comply with these requirements the detectors, ionisation chambers and secondary emission monitors are designed very reliable with a large operational range. Several stages of the acquisition chain are doubled and frequent functionality tests are automatically executed. The failure probabilities of single components were identified and optimised. First measurements show the large dynamic range of the system

18-Crown-6 Coordinated Metal Halides with Bright Luminescence and Nonlinear Optical Effects

The crown-ether coordination compounds ZnX$_{2}$(18-crown-6), EuX$_{2}$(18-crown-6) (X: Cl, Br, I), MnI$_{2}$(18-crown-6), Mn$_{3}$Cl$_{6}$(18-crown-6)2, Mn$_{3}$I$_{6}$(18-crown-6)$_{2}$, and Mn$_{2}$I$_{4}$(18-crown-6) are obtained by ionic-liquid-based synthesis. Whereas MX$_{2}$(18-crown-6) (M: Zn, Eu) show conventional structural motives, Mn$_{3}$Cl$_{6}$(18-crown-6)$_{2}$, Mn$_{3}$I$_{6}$(18-crown-6)$_{2}$, and Mn$_{2}$I$_{4}$(18-crown-6) exhibit unusual single MnX$_{4}$ tetrahedra coordinated to the crown-ether complex. Surprisingly, some compounds show outstanding photoluminescence. Thus, rare Zn$^{2+}$-based luminescence is observed and unexpectedly efficient for ZnI$_{2}$(18-crown-6) with a quantum yield of 54%. Unprecedented quantum yields are also observed for Mn$_{3}$I$_{6}$(18-crown-6)$_{2}$, EuBr$_{2}$(18-crown-6), and EuI$_{2}$(18-crown-6) with values of 98, 72, and 82%, respectively, which can be rationalized based on the specific structural features. Most remarkable, however, is Mn$_{2}$I$_{4}$(18-crown-6). Its specific structural features with finite sensitizer–activator couples result in an extremely strong emission with an outstanding quantum yield of 100%. Consistent with its structural features, moreover, anisotropic angle-dependent emission under polarized light and nonlinear optical (NLO) effects occur, including second-harmonic generation (SHG). The title compounds and their optical properties are characterized by single-crystal structure analysis, X-ray powder diffraction, chemical analysis, density functional theory (DFT) calculations, and advanced spectroscopic methods

Freshwater monitoring by nanopore sequencing.

While traditional microbiological freshwater tests focus on the detection of specific bacterial indicator species, including pathogens, direct tracing of all aquatic DNA through metagenomics poses a profound alternative. Yet, in situ metagenomic water surveys face substantial challenges in cost and logistics. Here, we present a simple, fast, cost-effective and remotely accessible freshwater diagnostics workflow centred around the portable nanopore sequencing technology. Using defined compositions and spatiotemporal microbiota from surface water of an example river in Cambridge (UK), we provide optimised experimental and bioinformatics guidelines, including a benchmark with twelve taxonomic classification tools for nanopore sequences. We find that nanopore metagenomics can depict the hydrological core microbiome and fine temporal gradients in line with complementary physicochemical measurements. In a public health context, these data feature relevant sewage signals and pathogen maps at species level resolution. We anticipate that this framework will gather momentum for new environmental monitoring initiatives using portable devices

Development, Production and Testing of 4500 Beam Loss Monitors

Beam-loss monitoring (BLM) [1] is a key element in the LHC machine protection. 4250 nitrogen filled ionization chambers (IC) and 350 secondary emission monitors (SEM) have been manufactured and tested at the Institute for High Energy Physics (IHEP) in Protvino, Russia, following their development at CERN. Signal speed and robustness against aging were the main design criteria. Each monitor is permanently sealed inside a stainless-steel cylinder. The quality of the welding was a critical aspect during production. The SEMs are requested to hold a vacuum of $10^{-7}$ bar. Impurity levels from thermal and radiationinduced desorption should remain in the range of parts per million in the ICs. To avoid radiation aging (up to $2·10^{8}$ Gy in 20 years) production of the chambers followed strict UHV requirements. IHEP designed and built the UHV production stand. Due to the required dynamic range of $10^{8}$, the leakage current of the monitors has to stay below 2 pA. Several tests during and after production were performed at IHEP and CERN. A consistently high quality during the whole production period was achieved and the tight production schedule kept at the same time

Freshwater monitoring by nanopore sequencing.

While traditional microbiological freshwater tests focus on the detection of specific bacterial indicator species, including pathogens, direct tracing of all aquatic DNA through metagenomics poses a profound alternative. Yet, in situ metagenomic water surveys face substantial challenges in cost and logistics. Here, we present a simple, fast, cost-effective and remotely accessible freshwater diagnostics workflow centred around the portable nanopore sequencing technology. Using defined compositions and spatiotemporal microbiota from surface water of an example river in Cambridge (UK), we provide optimised experimental and bioinformatics guidelines, including a benchmark with twelve taxonomic classification tools for nanopore sequences. We find that nanopore metagenomics can depict the hydrological core microbiome and fine temporal gradients in line with complementary physicochemical measurements. In a public health context, these data feature relevant sewage signals and pathogen maps at species level resolution. We anticipate that this framework will gather momentum for new environmental monitoring initiatives using portable devices

Genomic structural variations lead to dysregulation of important coding and non-coding RNA species in dilated cardiomyopathy

The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as non-coding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genome-wide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 non-protein-coding elements of the genome are deleted or duplicated by SVs, containing 3,758 long non-coding RNAs and 1,756 protein-coding transcripts. 65.3% of the SV-eQTLs do not harbor a significant SNV-eQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted protein-coding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike