A new method for reconstructing a full spectrum from under-sampled magnetic resonance spectrum data by using a deep learning network. First, the exponential function is used to generate a time-domain signal of the magnetic resonance spectrum, and a zero-filling time-domain signal is obtained after the under-sampled operation is completed in the time domain. The zero-filling time-domain signal and the full spectrum corresponding to the full sampling are combined to form a training data set. Then, a data verification convolutional neural network model is established for magnetic resonance spectrum reconstruction, where the training data set is used to train neural network parameters to form a trained neural network. Finally, the under-sampled magnetic resonance time-domain signal is input to the trained data verification convolutional neural network, and the full magnetic resonance spectrum is reconstructed.

Multi-dimensional spectra associated with a specimen are reconstructed using lower dimensional spectra as constraints. For example, a two-dimensional spectrum associated with diffusivity and spin-lattice relaxation time is obtained using one-dimensional spectra associated with diffusivity and spin-lattice relaxation time, respectively, as constraints. Data for a full two dimensional spectrum are not acquired, leading to significantly reduced data acquisition times.

Multi-dimensional spectra associated with a specimen are reconstructed using lower dimensional spectra as constraints. For example, a two-dimensional spectrum associated with diffusivity and spin-lattice relaxation time is obtained using one-dimensional spectra associated with diffusivity and spin-lattice relaxation time, respectively, as constraints. Data for a full two dimensional spectrum are not acquired, leading to significantly reduced data acquisition times.

A method for automatically quantifying an analyte in a measurement sample includes providing a 1D-NMR spectrum and a 2D-NMR spectrum, providing at least one information item in relation to at least one analyte to be quantified, establishing a chemical shift of the NMR signal of the analyte to be quantified from the measured 2D-NMR spectrum using the at least one information item provided, establishing expected peak positions of the NMR signal of the analyte to be quantified, establishing measured peak positions from the measured 1D-NMR spectrum, and establishing disturbance signal peak positions using the expected peak positions and the actual peak positions. The method further includes modelling the 1D-NMR spectrum using the established disturbance signal peak positions using the established chemical shift and using the at least one information item provided, integrating the modelled 1D-NMR spectrum, and quantifying the analyte by internal or external referencing.

Methods of assessing biosimilarity of proteins, e.g., therapeutic antibodies, are described.

A device for NMR spectroscopy includes a magnet arrangement, configured to produce a magnetic probe field within a magnet field of view external to the magnet arrangement. In a embodiment, the device includes a coil arrangement, configured to generate an electromagnetic excitation field within a coil field of view and a controller, configured to control the coil arrangement. The device includes a magnet adjustment arrangement, configured and arranged to modify at least one parameter of the magnet arrangement to change a spatial position of the magnet field of view.

Methods for determining a volume of stored gas within a rock sample includes loading a rock sample into an overburden cell. A hydrocarbon gas at a gas pressure is applied to the rock sample and a confining fluid at a confining pressure is applied to the overburden cell. The confining pressure and the gas pressure are increased until a first pressure and temperature condition is met. With the rock sample maintained at the first temperature and pressure condition, a nuclear magnetic resonance spectrometer is used to scan the rock sample and measure a hydrocarbon gas volume within the rock sample. This measured hydrocarbon gas volume is then corrected using a Real Gas Index to determine the volume of stored gas within the rock sample.

A protocol to determine chemical shift-specific Ti constants in inhomogeneous magnetic fields is provided. Based on intermolecular double-quantum coherences and spatial encoding techniques, the method can resolve overlapped NMR spectral peaks in inhomogeneous magnetic fields acquired using conventional methods. With inversion recovery involved, the amplitude of spectral peak will be modulated by inversion recovery time. After fitting the spectral peak amplitude variation curve, the corresponding longitudinal relaxation time can be achieved. With the measured T.sub.1 values in inhomogeneous magnetic fields, insights into chemical exchange rates, signal optimization, and data quantitation can be obtained.

A system, method and computer program product for detecting indicators for structural changes of NMR active test molecules in a test sample, or indicators for structural changes of the environment of said test molecules in relation to a reference molecule. Initial local similarity values are obtained, using a similarity function and representing a local similarity between a reference spectrum and a test spectrum within corresponding similarity regions (SRR, SRT). The initial local similarity values represent a similarity map (SM1) in which contours of a first shape type are indicators (I1) for structural changes of the test molecule, and in which contours of a second shape type are indicators (I2) for structural changes of the environment of said test molecule in relation to the reference molecule.

Various embodiments for system and methods for cyber-enabled structure elucidation are disclosed.