PSI
  • Berlin, Germany
Recent publications
One of the biggest obstacles to developing better zeolite-based catalysts is the lack of methods for quantitatively locating light heteroatoms on the T-sites in zeolites. Titanium silicalite-1 (TS-1) is a Ti-bearing zeolite-type catalyst commonly used in partial oxidation reactions with H2O2, such as aromatic hydroxylation and olefin epoxidation. The reaction mechanism is controlled by the configuration of titanium sites replacing silicon in the zeolite framework, but these sites remain unknown, hindering a fundamental understanding of the reaction. This study quantitatively determines heteroatoms within the zeolite-type framework using anomalous X-ray powder diffraction (AXRD) and the changes in the titanium X-ray scattering factor near the Ti K-edge (4.96 keV). Two TS-1 samples, each with approximately 2 Ti atoms per unit cell, were examined. Half of the titanium atoms are primarily split between sites T3 and T9, with the remainder dispersed among various T-sites within both MFI-type frameworks. One structure showed significant non-framework titanium in the micropores of a more distorted lattice. In both samples, isolated titanium atoms were more prevalent than dinuclear species, which could only potentially arise at site T9, but with a significant energy penalty and were not detected.
Hydrogen will play a key role in decarbonizing economies. Here, we quantify the costs and environmental impacts of possible large-scale hydrogen economies, using four prospective hydrogen demand scenarios for 2050 ranging from 111–614 megatonne H2 year⁻¹. Our findings confirm that renewable (solar photovoltaic and wind) electrolytic hydrogen production generates at least 50–90% fewer greenhouse gas emissions than fossil-fuel-based counterparts without carbon capture and storage. However, electrolytic hydrogen production could still result in considerable environmental burdens, which requires reassessing the concept of green hydrogen. Our global analysis highlights a few salient points: (i) a mismatch between economical hydrogen production and hydrogen demand across continents seems likely; (ii) region-specific limitations are inevitable since possibly more than 60% of large hydrogen production potentials are concentrated in water-scarce regions; and (iii) upscaling electrolytic hydrogen production could be limited by renewable power generation and natural resource potentials.
X-ray Computed Tomography (XCT) is a validated and frequently used tool to verify part geometry and to perform a non-destructive inspection of additive manufacturing parts. However, the acquisition of a large number of X-ray projections generates long inspection times. This conflicts with a high throughput of the production process and hinders the integration of XCT as an in-line quality control procedure for low-end parts. In this paper, we propose a method to obtain 3D information of the internal pores from a limited view or limited angle scan. The method combines a forward projection model of a cone-beam X-ray system and a deep learning neural network to directly classify each individual voxel, based on the X-ray projections in order to avoid the reconstruction and segmentation step. Accompanying reconstruction artefacts for limited view and limited angle XCT scans are thereby reduced, while preserving 3D information of the pores, defects or inclusions inside the material. The method is validated on real X-ray projections of polymer laser sintered industrial parts and shows a significant reduction in the required X-ray projections, hence acquisition time.
In the scope of its project on the assimilation and reproduction of experiments for the evaluation of stainless-steel nuclear data HARVEST-X, the LRS launches a pile-oscillation experimental program in the CROCUS reactor: BLOOM. For this program, an oscillator called POLLEN originally developed to be used as a vibrating absorber to compensate the fuel rods oscillator COLIBRI was reworked as a standalone pile-oscillator called. The oscillator operates with an arbitrary periodical shape, an amplitude of 1 m and a frequency ranging from the mHz to the Hz. An emphasis was put in the development of an interface for pseudo-square oscillations for BLOOM. This interface also allows independent adjustment of the ramping time and dwell time of the pseudo-square. The qualification of POLLEN was performed by video analysis of sinusoidal oscillations, using a 4K 30fps camera. With the current system, a precision of 0.2 mm was achieved during slow sinusoidal oscillation and a precision of 0.17 mm was obtained for pseudo square oscillations with a 500 g load. Whereas the results are satisfactory with respect to the current system and fulfill the requirement of the BLOOM program, it is planned to upgrade the system with the addition of a mechanical reference in the system. It is also in consideration to upgrade the acquisition card and controller to 16 bits systems to allow the use of POLLEN in setups where larger displacements are needed. The first in-core oscillation experiments are planned for early 2024.
This paper investigates the finite sample performance of a range of parametric, semi-parametric, and non-parametric instrumental variable estimators when controlling for a fixed set of covariates to evaluate the local average treatment effect. Our simulation designs are based on empirical labor market data from the US and vary in several dimensions, including effect heterogeneity, instrument selectivity, instrument strength, outcome distribution, and sample size. Among the estimators and simulations considered, non-parametric estimation based on the random forest (a machine learner controlling for covariates in a data-driven way) performs competitive in terms of the average coverage rates of the (bootstrap-based) 95% confidence intervals, while also being relatively precise. Non-parametric kernel regression as well as certain versions of semi-parametric radius matching on the propensity score, pair matching on the covariates, and inverse probability weighting also have a decent coverage, but are less precise than the random forest-based method. In terms of the average root mean squared error of LATE estimation, kernel regression performs best, closely followed by the random forest method, which has the lowest average absolute bias.
A series of ZSM-5 zeolite materials were synthesized from organic structure-directing agent (OSDA)-free seeded systems, including nanosized silicalite-1 (12 wt % water suspension or in powder form) or nanosized ZSM-5 (powder form of ZSM-5 prepared at 100 or 170 °C). The physicochemical characterization revealed aggregated species in the samples based on silicalite-1. Contrarily, the catalysts based on ZSM-5 seeds revealed isolated copper species, and thus, higher NO conversion during the selective catalytic reduction of NOx with NH3 (NH3–SCR-DeNOx) was observed. Furthermore, a comparison of the Cu-containing ZSM-5 catalysts, conventionally prepared in the presence of OSDAs and prepared with an environmentally more benign approach (without OSDAs), revealed their comparable activity in NH3–SCR-DeNOx.
Background Continuous distribution channels are effective methods to deliver malaria interventions such as insecticide treated nets (ITNs) to pregnant women attending antenatal care clinics and children under five attending immunization visits. Facility-based and provider-based checklists were used during supportive supervision visits to measure the quality of facility-based services and interventions. This study looks at ITN distributions at health facilities in Ghana, with the aim of providing insights on how quality can be measured and monitored. Methods Various quality improvement approaches for malaria services occur in Ghana. Selected indicators were analysed to highlight the similarities and differences of how the approaches measured how well the channel was doing. Generally, the approaches assessed (1) service data management, (2) logistics data management, and (3) observation of service provision (ITN issuance, malaria education, ITN use and care education). Two approaches used a binary (Yes/No) scale, and one used a Likert scale. Results Results showed that most data reported to the national HMIS is accurate. Logistics data management remained an issue at health facilities, as results showed scores below average across facility stores, antenatal care, and immunization. Though the supervision approaches differed, overall results indicated that almost all eligible clients received ITNs, data were recorded accurately and reported on-time, and logistics was the largest challenge to optimal distribution through health facilities. Conclusion The supervision approaches provided valuable insights into the quality of facility-based ITN distribution. Ghana should continue to implement supportive supervision in their malaria agenda, with additional steps needed to improve reporting of collected data and increase the number of facilities visited for supportive supervision and the frequency. There were various supervision approaches used with no clear guidance on how to measure quality of facility-based ITN distribution, so there is also need for the global community to agree on standardized indicators and approaches to measuring quality of facility-based ITN distribution. Additionally, future studies can review the effect of multiple rounds of supervision visits on the quality of ITN distribution as well as understand the facilitators and barriers to scaling up supervision of facility-based ITN distribution.
Background Global efforts to reduce malaria burden include distribution of insecticide-treated mosquito nets through mass campaigns and routine channels. Ghana’s National Malaria Elimination Programme (NMEP) distributes insecticide-treated bed nets (ITNs) through various channels, including to pregnant women at antenatal care (ANC) visits and children at vaccination visits through child welfare clinics (CWC). This study assessed historical ITN distribution throughout ANCs and CWCs across Ghana and the characteristics of high performing facilities. Methods Monthly data on routine ITN distribution was provided from Ghana’s national health information management system for the years 2016–2021. Analyses were conducted to assess the performance of ITN distribution at ANC and CWC across time, ecological zone, regions, districts, facility ownership, and facility type. Univariate and multivariate logistic regressions were performed to predict the odds of ANC and CWC issuing rates greater or equal to 80% for a given facility type or ownership. Results In 2021, 93% of women who attended their first antenatal care visit and 92% of children under five who received their second dose of the measles-rubella vaccine (MR2) had received an ITN. At the regional level, 94% of regions (n = 15/16) maintained the NSP target issuing rate of 80% throughout 2020 and 2021. While there were no clear differences in issuing rates between ecological zones, district-level differences were present across the six years. All health facility types performed at or above 80% in 2021 for both ANC and CWC. Odds ratios demonstrated differences in the likelihood of meeting the 80% issuing rate goal among different facility types as well as private versus public ownership when comparing ANC and CWC. Conclusion By 2021, Ghana had improved its ITN issuing rates since the initial year of analysis, surpassing the 80% target by issuing nets to over 90% of pregnant women and young children attending ANC and CWC. Future work can explore the reasons for national and subnational differences in issuing rates as well as help understand additional characteristics of high performing facilities. Additionally, it is necessary to identify and expand on the drivers for improved performance over the time period.
Background: Vaccination plays an imperative role in protecting public health and preventing avoidable mortality. Yet, the reasons for vaccine hesitancy in African countries are not well understood. This study investigates the factors associated with the acceptance of COVID-19 vaccine in Mozambique, with a focus on the role of institutional trust. Methods: The data came from the three waves of the COVID-19 Knowledge, Attitudes and Practices (KAP) survey which followed a cohort of 1,371 adults in Mozambique over six months (N = 3809). We examined vaccine acceptance based on three measurements: willingness to take vaccine, perceived vaccine efficacy, and perceived vaccine safety. We conducted multilevel regression analysis to investigate the trajectories of, and the association between institutional trust and vaccine acceptance. Results: One third of the survey participants (37%) would definitely take the vaccine. Meanwhile, 31% believed the vaccine would prevent the COVID-19 infection, and 27% believed the vaccine would be safe. There was a significant decrease in COVID-19 vaccine acceptance between waves 1 and 3 of the survey. Institutional trust was consistently and strongly correlated with different measures of vaccine acceptance. There was a greater decline in vaccine acceptance in people with lower institutional trust. The positive correlation between institutional trust and vaccine acceptance was stronger in younger than older adults. Vaccine acceptance also varied by gender and marital status. Conclusions: Vaccine acceptance can be volatile even over short periods of time. Institutional trust is a central driver of vaccine acceptance and contributes to the resilience of the health system. Our study highlights the importance of health communication and building a trustful relationship between the general public and the institutions in the context of a global pandemic.
To investigate the processing of speech in the brain, commonly simple linear models are used to establish a relationship between brain signals and speech features. However, these linear models are ill-equipped to model a highly-dynamic, complex non-linear system like the brain, and they often require a substantial amount of subject-specific training data. This work introduces a novel speech decoder architecture: the Very Large Augmented Auditory Inference (VLAAI) network. The VLAAI network outperformed state-of-the-art subject-independent models (median Pearson correlation of 0.19, p < 0.001), yielding an increase over the well-established linear model by 52%. Using ablation techniques, we identified the relative importance of each part of the VLAAI network and found that the non-linear components and output context module influenced model performance the most (10% relative performance increase). Subsequently, the VLAAI network was evaluated on a holdout dataset of 26 subjects and a publicly available unseen dataset to test generalization for unseen subjects and stimuli. No significant difference was found between the default test and the holdout subjects, and between the default test set and the public dataset. The VLAAI network also significantly outperformed all baseline models on the public dataset. We evaluated the effect of training set size by training the VLAAI network on data from 1 up to 80 subjects and evaluated on 26 holdout subjects, revealing a relationship following a hyperbolic tangent function between the number of subjects in the training set and the performance on unseen subjects. Finally, the subject-independent VLAAI network was finetuned for 26 holdout subjects to obtain subject-specific VLAAI models. With 5 minutes of data or more, a significant performance improvement was found, up to 34% (from 0.18 to 0.25 median Pearson correlation) with regards to the subject-independent VLAAI network.
Introduction: We conducted an assessment in Malawi, Nepal, Niger, and Uganda to document access-related reasons for not using contraceptive methods during the COVID-19 pandemic that led to unintended pregnancies, describe use of modern contraception among women in potential need of contraception compared to before the pandemic, examine method choice, and describe barriers to contraceptive access and use. Methods: Between December 2020 and May 2021, we conducted an opt-in phone survey with 21,692 women, followed by an outbound survey with 5,124 women who used modern nonpermanent contraceptive methods or who did not want to get pregnant within 2 years but were not using a modern contraceptive method. The surveys examined current behaviors and documented behaviors before the pandemic retrospectively. We used multivariable logistic regression models to examine factors associated with contraceptive use dynamics during COVID-19. Results: Pregnant women surveyed reported that the pandemic had affected their ability to delay or avoid getting pregnant, ranging from 27% in Nepal to 44% in Uganda. The percentage of respondents to the outbound survey using modern contraception decreased during the pandemic in all countries except Niger. Fear of COVID-19 infection was associated with discontinuing modern contraception in Malawi and with not adopting a modern method among nonusers in Niger. Over 79% of surveyed users were using their preferred method. Among nonusers who tried obtaining a method, reasons for nonuse included unavailability of the preferred method or of providers and lack of money; nonusers who wanted a method but did not try to obtain one cited fear of COVID-19 infection. Conclusion: We found evidence of surveyed women attributing unintended pregnancies to the pandemic and examples of constraints to contraceptive access and use on the supply and demand side. The effects of the pandemic must be interpreted within the local contraceptive, health system, and epidemiological context.
Background Malaria in Cambodia has decreased by 90.8% between 2010 and 2020, driven by the commitment of the National Center for Parasitology, Entomology and Malaria (CNM) and the achievements of the roll-out of a village malaria worker programme. However, in the first seven months of 2018, CNM identified a 207% increase (11,969 to 36,778) in confirmed malaria cases compared to the same months in the previous year. To address this increase, CNM developed the “Intensification Plan” (IP), implemented between October 2018 and December 2020. Methods The structure of the IP was summarized, including the selection of sites, the interventions implemented in the selected health facility catchment areas (HFCAs) and the monitoring and evaluation process. Data on IP interventions were collected by CNM and civil society organisations. Data on malaria cases and tests from all HFCAs in Cambodia from January 2018 to December 2020 were sourced from the Cambodia Malaria Information System (MIS) and WHO Malaria Elimination Database. Malaria data from IP HFCAs and non-IP HFCAs was analysed and compared to present the changes in malaria testing and confirmed cases before and during implementation of the IP. Results Between October 2018 and December 2020, through the IP 16,902 forest packs and 293,090 long-lasting insecticide treated nets were distributed. In the 45 HFCAs included in the IP, 431,143 malaria tests were performed and 29,819 malaria cases were diagnosed, 5364 (18%) of which were Plasmodium falciparum /mixed cases. During the intervention period, over all HFCAs included in IP, P. falciparum /mixed cases declined from 1029 to 39, a 96.2% decrease, and from 25.4 P. falciparum /mixed cases per HFCA to 0.9. HFCAs not included in IP declined from 468 to 43 cases, a 90.8% decrease, showing that routine malaria activities in Cambodia were also playing an important contribution to malaria control. Conclusions Over the course of IP implementation there was a substantial increase in malaria testing and both overall malaria cases and P. falciparum /mixed cases decreased month on month. The initiative yields lessons learned for Cambodia to reach the final stage of elimination as well as for other countries aiming to accelerate their malaria control programmes.
Background HIV self-testing (HIVST) has the potential to increase coverage of HIV testing, but concerns exist about intended users’ ability to correctly perform and interpret tests, especially in poor communities with low literacy rates. We assessed the clinical performance of the 2016 prototype OraQuick® HIV Self-Test in rural and urban communities in Zambia to assess the sensitivity and specificity of the test compared to the national HIV rapid diagnostic test (RDT) algorithm and a laboratory reference standard using 4th generation enzyme immunoassays and HIV RNA detection. Methods Participants were recruited from randomly selected rural and urban households and one urban health facility between May 2016 and June 2017. Participants received a brief demonstration of the self-test, and then self-tested without further assistance. The research team re-read the self-test, repeated the self-test, drew blood for the laboratory reference, and conducted RDTs following the national HIV testing algorithm (Determine™ HIV1/2 (Alere) confirmed using Unigold™ HIV1/2 (Trinity Biotech)). Selected participants (N = 85) were videotaped whilst conducting the testing to observe common errors. Results Initial piloting showed that written instructions alone were inadequate, and a demonstration of self-test use was required. Of 2,566 self-test users, 2,557 (99.6%) were able to interpret their result. Of participants who were videoed 75/84 (89.3%) completed all steps of the procedure correctly. Agreement between the user-read result and the researcher-read result was 99.1%. Compared to the RDT algorithm, user-conducted HIVST was 94.1% sensitive (95%CI: 90.2–96.7) and 99.7% specific (95%CI: 99.3–99.9). Compared to the laboratory reference, both user-conducted HIVST (sensitivity 87.5%, 95%CI: 82.70–91.3; specificity 99.7%, 95%CI: 99.4–99.9) and the national RDT algorithm (sensitivity 93.4%, 95%CI: 89.7–96.1%; specificity 100% (95%CI: 99.8–100%) had considerably lower sensitivity. Conclusions Self-testers in Zambia who used OraQuick® HIV Self-Test achieved reasonable clinical performance compared to the national RDT algorithm. However, sensitivity of the self-test was reduced compared to a laboratory reference standard, as was the national RDT algorithm. In-person demonstration, along with the written manufacturer instructions, was needed to obtain accurate results. Programmes introducing self-care diagnostics should pilot and optimise support materials to ensure they are appropriately adapted to context.
Phosphorus (P) is essential for plant growth. Arbuscular mycorrhizal fungi (AMF) aid its uptake by acquiring P from sources distant from roots in return for carbon. Little is known about how AMF colonise soil pore‐space, and models of AMF‐enhanced P‐uptake are poorly validated. We used synchrotron X‐ray computed tomography to visualize mycorrhizas in soil and synchrotron X‐ray fluorescence/X‐ray absorption near edge structure (XRF/XANES) elemental mapping for P, sulphur (S) and aluminium (Al) in combination with modelling. We found that AMF inoculation had a suppressive effect on colonisation by other soil fungi and identified differences in structure and growth rate between hyphae of AMF and nonmycorrhizal fungi. Our results showed that AMF co‐locate with areas of high P and low Al, and preferentially associate with organic‐type P species over Al‐rich inorganic P. We discovered that AMF avoid Al‐rich areas as a source of P. Sulphur‐rich regions were found to be correlated with higher hyphal density and an increased organic‐associated P‐pool, whilst oxidized S‐species were found close to AMF hyphae. Increased S oxidation close to AMF suggested the observed changes were microbiome‐related. Our experimentally‐validated model led to an estimate of P‐uptake by AMF hyphae that is an order of magnitude lower than rates previously estimated – a result with significant implications for the modelling of plant–soil–AMF interactions.
There is a long-standing controversy on nuclear data uncertainty assessment for general purpose nuclear data libraries. On the one hand, nuclear data users would like the libraries to predict uncertainties for selected integral quantities consistent with the integral experimental uncertainties, while on the other hand, doing so could make evaluations dependent on selected integral datasets breaking the general applicability of the library to any existing or future applications. This article studies the hypothesis that certain correlations between nuclear data, which come from the immutable nature of the reactor physics in the integral experiment used as benchmarks, and can be estimated almost independently of the choice of selected integral experiments, nuclear data library, or evaluation methodology. This article reports the findings of an international computational inter-comparison study carried out under the auspices of the Working Party on International Nuclear Data Evaluation Co-operation. The participants represented 5 different organizations, on three different continents and used different initial nuclear data libraries and different calculation methodologies. This study focused on estimating the correlation coefficients between fission, capture and nu-bar for Pu-239 which would arise in the final evaluated nuclear data library if a plutonium metal fast-neutron-spectrum critical experiment with typical integral-measurement uncertainty of 100 pcm was used in the validation and feedback to compile the nuclear data library. The additional knowledge of the correlation coefficients can effectively reduce the propagated uncertainty on criticality experiments from the extended library. This exercise helped to improve understanding the different approaches used, to identify weaknesses and provide indications where further work is required to develop a scientifically rigorous method. This article does not aim at recommending these methods as standards. It aims at honoring the effort of Massimo Salvatores, who was instrumental in pushing studies that should lead to development of uncertainty estimation and by participating in them.
The triangular lattice with Ising magnetic moments is an archetypical example of geometric frustration. In the case of dipolar-coupled out-of-plane moments, the geometric frustration results in a disordered classical spin-liquid state at higher temperatures while the system is predicted to transition to an anti-ferromagnetic stripe ground state at low temperatures. In this work we fabricate artificial triangular Ising spin systems without and with uniaxial in-plane compression to tune the nature and temperature of the correlations. We probe the energy scale and nature of magnetic correlations by grazing-incidence small-angle neutron scattering. In particular, we apply a newly-developed empirical structure-factor model to describe the measured short-range correlated spin-liquid state, and find good agreement with theoretical predictions. We demonstrate that grazing-incidence neutron scattering on our high-quality samples, in conjunction with detailed modeling of the scattering using the Distorted Wave Born Approximation, can be used to experimentally quantify the spin-liquid-like correlations in highly-frustrated artificial spin systems.
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25 members
Romain Ganter
  • Department Large Research Facilities (GFA)
Julia König
  • Electrical Energy
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Berlin, Germany