Publication

Cellulose phosphorylation comparison and analysis of phosphorate position on cellulose fibers

Publications associées (31)

Extensions of Peer Prediction Incentive Mechanisms

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

A continuous-wave and pulsed X-band electron spin resonance spectrometer operating in ultra-high vacuum for the study of low dimensional spin ensembles

Giovanni Boero, Fabio Donati, Soyoung Oh

We report the development of a continuous-wave and pulsed X-band electron spin resonance (ESR) spectrometer for the study of spins on ordered surfaces down to cryogenic temperatures. The spectrometer operates in ultra-high vacuum and utilizes a half-wavele ...

Aip Publishing2024

129Xe Dynamic Nuclear Polarization Demystified: The Influence of the Glassing Matrix on the Radical Properties

Rolf Gruetter, Jean-Noël Hyacinthe, Andrea Capozzi, Thanh Phong Kevin Lê, Emma Linnea Wiström

129Xe dissolution dynamic nuclear polarization (DNP) is a controversial topic. The gold standard technique for hyperpolarized xenon magnetic resonance imaging (MRI) is spin exchange optical pumping, which received FDA approval in 2022. Nevertheless, the ve ...

2024

Room-temperature quantum optomechanics using an ultralow noise cavity

Tobias Kippenberg, Nils Johan Engelsen, Alberto Beccari, Guanhao Huang

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Nature Portfolio2024

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Tobias Kippenberg, Nils Johan Engelsen, Alberto Beccari

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

Nature Portfolio2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Quantification of Native Lignin Structural Features with Gel-Phase 2D-HSQC0 Reveals Lignin Structural Changes During Extraction

Jeremy Luterbacher, Stefania Bertella

Our ability to study and valorize the lignin fraction of biomass is hampered by the fundamental and still unmet challenge of precisely quantifying native lignin's structural features. Here, we developed a rapid elevated-temperature H-1-C-13 Heteronuclear S ...

Wiley-VCH Verlag GmbH2024

Optimal sensitivity for 1H detected relayed DNP of organic solids at fast MAS

David Lyndon Emsley, Pierrick Berruyer, Saumya Badoni

Dynamic nuclear polarization (DNP) combined with high magnetic fields and fast magic angle spinning (MAS) has opened up a new avenue for the application of exceptionally sensitive 1H NMR detection schemes to study protonated solids. Recently, it has been s ...

Academic Press Inc - Elsevier Science2024

Data-driven statistical optimization of a groundwater monitoring network

Andrea Rinaldo, Gianluca Botter

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites

Paul Joseph Dyson, Farzaneh Fadaei Tirani, Mouna Hadiji

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Amer Chemical Soc2024

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Giorgia Chinazzo

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

Pergamon-Elsevier Science Ltd2024

A compact approach to higher-resolution resonant inelastic x-ray scattering detection using photoelectrons

Henrik Moodysson Rønnow, Markus Scholz

The detection of inelastically scattered soft x-rays with high energy resolution usually requires large grating spectrometers. Recently, photoelectron spectrometry for analysis of x-rays (PAX) has been rediscovered for modern spectroscopy experiments at sy ...

Iop Publishing Ltd2024

Rational combination platform trial design for children and young adults with Diffuse Midline Glioma: a report from PNOC

Sebastian Martin Waszak

Diffuse midline glioma (DMG) is a devastating pediatric brain tumor unresponsive to hundreds of clinical trials. Approximately 80% of DMGs harbor H3K27M oncohistones, which reprogram the epigenome to increase the metabolic profile of the tumor cells. We ha ...

2023

Mitochondrial matrix protein LETMD1 maintains thermogenic capacity of brown adipose tissue in male mice

Johan Auwerx, Maroun Bou Sleiman, Jun Yong Kim, Xiaoxu Li

Brown adipose tissue (BAT) has abundant mitochondria with the unique capability of generating heat via uncoupled respiration. Here, Park et al. identify LETMD1 as a mitochondrial matrix protein enriched in brown adipose tissue (BAT) and reveal a crucial ro ...

Nature Portfolio2023

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Panayiotis Danassis, Ljubomir Rokvic

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

EPFL2023

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Boi Faltings, Naman Goel

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

2023

Deuterated TEKPol Biradicals and the Spin-Diffusion Barrier in MAS DNP

Dominik Józef Kubicki, David Lyndon Emsley, Yu Rao, Amrit Venkatesh, Federico De Biasi

The sensitivity of NMR spectroscopy is considerably enhanced by dynamic nuclear polarization (DNP). In DNP polarization is transferred from unpaired electrons of a polarizing agent to nearby proton spins. In solids, this transfer is followed by the transpo ...

Wiley-VCH Verlag GmbH2023

SLC25A46 promotes mitochondrial fission and mediates resistance to lipotoxic stress in INS-1E insulin-secreting cells

Loïc Dayon, Andreas Wiederkehr

Glucose sensing in pancreatic D-cells depends on oxidative phosphorylation and mitochondria-derived signals that promote insulin secretion. Using mass spectrometry-based phosphoproteo-mics to search for downstream effectors of glucose-dependent signal tran ...

COMPANY BIOLOGISTS LTD2023

Two-dimensional Pure Isotropic Proton Solid State NMR

Manuel Cordova, David Lyndon Emsley, Pinelopi Moutzouri, Bruno Simões de Almeida, Daria Torodii

One key bottleneck of solid-state NMR spectroscopy is that H-1 NMR spectra of organic solids are often very broad due to the presence of a strong network of dipolar couplings. We have recently suggested a new approach to tackle this problem. More specifica ...

Wiley-VCH Verlag GmbH2023