VITO

This document describes a method for enhancing bubble evacuation in electrochemical systems by integrating flow channels into porous electrode materials. These channels are engineered during the manufacturing process using techniques such as phase separation micro molding or sacrificial molds. The flow channels facilitate forced electrolyte flow, improving mass transport and preventing gas bubble accumulation, which can block active catalyst sites. This method also mitigates gas crossover risks, optimizes electrode performance, and contributes to system reliability and longevity. The porous electrode materials with integrated flow channels can be used in electrochemical cells to increase the electrochemical active surface area and are applicable in membrane electrode assemblies and alkaline water electrolyzers.

The present invention relates to a method and system for characterizing objects in a material stream using an indexed repository of recurring object types. It involves providing an indexed repository that contains consolidated representations of recurring object types. Each consolidated representation is derived from sensor data collected from multiple instances of the same object type. Sensor data of at least one object instance in the material stream is acquired through one or more sensing modalities. The acquired sensor data is then compared to the stored consolidated representations in order to match the object instance with at least one of these representations. Once a match is established, the method performs a characterization of the object instance by referencing the matched consolidated representation. Finally, an output is generated reflecting the result of this characterization. The invention provides for an accurate characterization of object types within material streams, providing a comprehensive framework with an indexed repository of recurring object types. The invention also relates to building an indexed representation of recurring objects in a physical material stream.

The invention relates to a method for preparing a phosphorous and nitrogen modified depolymerized lignin. This method involves providing a depolymerized lignin and treating it with a phosphorylation agent and an amine reagent to enhance its thermal stability compared to polymerized lignin. The depolymerized lignin is characterized by specific molecular weight ranges and polydispersity index. The modified lignin contains specific percentages of phosphorous and nitrogen and can be used as a flame retardant additive in blends with polymers having higher melting points. The phosphorylation agent and amine reagent are selected from specific groups, and the depolymerized lignin is obtained through reductive catalytic depolymerization, which can be performed in batch or continuous fashion using specific conditions and catalysts.

Disclosed is a computer-implemented method and system for detecting operational irregularities in a thermal energy exchange system comprising a substation between a first (upstream) side and a second (downstream) side. The method obtains time-series measurement data indicative of the substation's operational conditions, segments the data into intervals representing recurring operational behavior, and generates an aggregate fault signature emphasizing short-term variations relative to baseline conditions. This fault signature is then provided to a machine-learning-based fault detection model configured to distinguish faulty behavior from normal operation. A fault condition is identified when the signature deviates from normal operational behavior beyond a predefined criterion, thereby enabling timely and accurate detection of operational faults in the substation and/or downstream heating or cooling systems.

A computer implemented method and system is provided for detecting operational irregularities in a thermal energy exchange system. The system comprises a first side that generates heating/cooling, a second side that consumes heating/cooling, and an interface formed by one or more substations that facilitate thermal energy exchange between the two sides. The method includes obtaining operational data from one or more sensors monitoring a district heating substation over a plurality of time intervals, and utilizing a machine learning model that is pre-trained on mechanical fault signature data to extract features indicative of fault conditions. The model is then fine-tuned with fault-indicative data obtained from the district heating substation to adapt it to the specific operating domain. Subsequently, the fine-tuned machine learning model is applied to feature vectors extracted from the operational data to determine whether the substation and/or any coupled downstream heating/cooling systems are in a faulty or normal operational state, and an indication of a fault is output when a faulty state is detected.

The disclosure relates to a system and computer-implemented method for diagnosing faults in a thermal energy exchange system. It includes a first side generating heating/cooling, a second side consuming it, and at least one district heating substation facilitating energy transfer. The method processes time-series sensor data, generating augmented data by identifying fault-related segments, selecting references, aligning additional segments, and creating synthetic fault representations. A machine learning model is pre-trained on this data, then fine-tuned with real operational data. The refined model is applied to new data for fault diagnosis in the substation and downstream systems. Further, the invention relates to a computer-implemented method of training a fault classification model for diagnosing operational irregularities.

The invention relates to an improvement on the removal of the Fmoc N-terminal protecting group in the synthesis of peptides; in particular in the synthesis of peptides using Solid Phase Peptide Synthesis (SPPS) or using discriminating membrane technology to separate out byproducts and excess reagents from the reaction mixture; more in particular in the synthesis of peptides using discriminating membrane technology to separate out byproducts and excess reagents from the reaction mixture.

The method involves recovering Bisphenol A (BPA) monomer from a thermoset BPA-epoxy resin through alcoholysis using a C1-C3 alcohol and a hydroxide as a reaction promoter. This process is conducted under an inert atmosphere at a pressure of at least 10 bar and a temperature between 200-225°C for a minimum of 5 hours. The method allows for high yields of BPA monomer with reduced reaction times and less base usage compared to existing methods. The process includes loading 2-10 wt.% of the resin in the alcohol and can involve further steps such as crystallization and recrystallization for purification.

The method involves identifying tumor-specific antigens in non-small cell lung cancer (NSCLC) by obtaining tumor and non-tumor tissue samples from patients and performing RNA sequencing to identify genomic variants. Patient-specific databases are generated, and mass spectrometry-based immunopeptidomics is used to detect MHC class I-bound and MHC class II-bound variant peptides in tumor tissue samples. A subset of these peptides, exclusive to tumor samples, is identified and confirmed for strong association with patient-specific MHC molecules using MHC allotype predictions. This subset is recognized as tumor-specific antigens in NSCLC.

The present invention is related to a process for reduction of carbon oxides and to materials and devices for performing the said process. In particular, the present invention is related etched electrochemically active particles and a method of production thereof, an electrode comprising the etched electrochemically active particles, a method of production of the electrode, a flow cell electrolyzer including the electrode and the process for reduction of carbon oxides using the flow cell electrolyzer.