Fast Neutron Spectroscopy with C7LYC Scintillators · Learning with Purpose •Eliminate 6Li(n,a)...

Learning with PurposeLearning with Purpose

FastNeutronSpectroscopywithC7LYCScintillators

ParthaChowdhuryUniversityofMassachusettsLowell

WorksupportedbyU.S.DepartmentofEnergy

Learning with Purpose

Cs2LiYCl6 (CLYC):noveldualn-g scintillator

Chowdhury Neutron Detector Workshop- TAMU May 11, 2018

Sample Number0 50 100 150 200 250 300 350 400 450 500

Am

plitu

de (

V)

-0.1

-0.08

-0.06

-0.04

-0.02

0

Neutron

A1 A2

-rayγ

g•GammaresolutionbetterthanNaI

• Excellentn-gpulse-shapediscrimination

Pu(Be) source reactor thermal column

< 5%

reactor thermal column

gammas

6Li(n,a)3H,Q=+4.8MeV

gammas

neutronsneutrons

CLYC

Thermalneutronresponse

SBIRGrantwithRMDInc.


Energy (MeV)0 2 4 6 8 10 12

A1/A

2

00.5

11.5

22.5

33.5

44.5

5total

Entries 57168Mean x 2.033Mean y 1.552RMS x 2.302RMS y 0.4949

0

20

40

60

80

100

120

140

160

180

200

220total

Entries 57168Mean x 2.033Mean y 1.552RMS x 2.302RMS y 0.4949

neutron_xEntries 14783Mean 4.797RMS 1.733

Energy (MeV)0 2 4 6 8 10 12

Cou

nts

0

100

200

300

400

500neutron_x

Entries 14783Mean 4.797RMS 1.733

=1.10 MeVnE

R = 9%CLYC

Monoenergetic neutrons from 7Li(p,n) FastneutronresponseatVandeGraaff

Cs2LiYCl6 (CLYC):fastneutronresponse



Cs2LiYCl6 (CLYC):fastneutronresponse

Time Resolution

Linearity



• Eliminate6Li(n,a)thermalpeakvia7Li-enrichedC7LYC• Explorefastneutronspectroscopypotential(NNSAgrants)• A16-elementarrayof1”x1”C7LYC(largestcrystalsavailableatthetime)

SCANS :SmallC7LYCArrayforNeutronSpectrocopy

• NuclearsciencewithSCANS(C7LYC)•Elastic/inelasticneutronscatteringatLosAlamos• Beta-delayedneutronspectroscopyatCARIBU

VMEStruckDigitizers•16Ch – 250MS/s•14bitADC•n/g firmware

•~10%neutronpulseheightresolution!!• NolongToF armneeded• Geometricalefficiencycanbeenhancedbyplacingclosetotarget



56Fe(n,n’)SCANSatLANSCE

•100MeVpulsedprotonsonWspallationtarget•20mflightpathtoscatteringtarget(Fe)•C7LYCdetectors17cmfromtarget• TOFtodetectorprovidesincidentenergy•PulseheightinC7LYCprovidesscatteredenergy



56Fe(n,n’)SCANSatLANSCE


Learning with PurposeLearning with Purpose

100keV slicesonincidentneutronenergy

En > 1.9 MeV

En > 1.0 MeV

56Fe(n,n’)atLANSCEChowdhury Neutron Detector Workshop- TAMU May 11, 2018


56Feelastic/inelasticrelativecross-sections

presentdata(50-keVslice)witharbitrarynormalizationcomparedwithsimulations/databaseforelasticangulardistributioncross-sections



Efficiencyestimates&35Cl(n,p)cross-sections

LANL-ledexperiment(Jan2018)

ENDF/B-VII.0(2006) ENDF/B-VII.1(2011)

1”

MCNPX



thefirst3”x3”C7LYC

Active volume SCANS X 1.7



thefirst3”x3”C7LYC

3” x 3” C7LYC

1” x 1” C7LYC

3” x 3” C7LYC (blue)

3” x 3” NaI (red)

C7LYC Efficiency 98% of NaIC7LYC FWHM 5.8%

NaI FWHM 7.8% 137Cs

661 keV



UMassLowellRadiationLaboratory:Facilities5.5 MV CN singleendedVan de Graaff

1 MW research reactor

p,d,a beams;100μA DCbeam;Mobleybuncher;

sub-nspulsing;mono-energeticpulsedneutrons

via7Li(p,n);neutronbeamline;protonmicroprobe;scatteringchamber

openpool;LEUfuel;3horizontalbeamports;in-coresample (~1013 n/cm2/s);thermalcolumn(~106 n/cm2/s);digitalneutronradiographyhotcellwithremotemanipulators



C7LYCmeasurementsatUMassLowell

✦DirectlymeasureC7LYCefficiencyataccelerator✦Mono-energeticneutronsvia7Li(p,n)7Be✦Neutronproductionratevia7Beassay(52-dayhalf-life)✦One7Beperneutron,10%b-decaybranch,479-keVg-ray

1” x 1

3”x 3”

In-situ lithium target evaporator



C7LYCtestsatUML

7Li(p,n)7Be (g.s)

7Li(p,n)7Be*

Neutronspectrumfrom7Li(p,n)7Be

3”x3”Neutronenergy(keV)

En = 2 MeV

En = 1.5 MeV

En = 1 MeV

En = 0.5 MeV

En = 0.25 MeV

Inprogress!

429keV



b-delayedneutronemittersatCARIBUCAlifornium RareIsotopeBreederUpgradewww.phy.anl.gov/atlas/

caribu/index.html

SATURN (ScintillatorAndTapeUsingRadioactiveNuclei)

1-2Ci252CfsourceGas

catcher1:20000isobar

separator

X-Array

A.J.Mitchellatal.,NIMA763,232(2014)



94Rbà 94Sr

CLYCresultsinconclusive,toberepeatedinnewlow-backgroundCARIBUhall

Measuredt1/2 2.75(2)s(comparewith2.76(6)s)



machinelearningn-g discrimination• n/γPSDabinaryclassificationproblem• Commontargetofmachinelearningalgorithms• Artificialneuralnetworkspromisingforn/g PSDinliquidscintillators• “Supervisedlearning”– requirespre-classifiedtrainingdata• Feedforwardneuralnetwork• Interconnected“hidden”layersof‘artificialneurons’• Eachneuronhasmanyinputs𝑥i andoneoutput𝑧• Theoutputisaweightedsumofitsinputs• Passedthroughan‘activationfunction’𝑓



machinelearningn-g discrimination• Tracepresentedtonetworkasinputs• Passedthroughasinglehiddenlayer• Activationfunctiontanh 𝑥• Varyweightsandbiasesofeachneuron• Maximizeaccuracyovertrainingdata• OutputofANN1or0(norg)

• ~500linesofPythonandC++,classifierisinPython,usingKeras• Keras - wrapperaroundTensorflow machinelearninglibrary• Optimizationalgorithmis‘stochasticgradientdescent’• 544inputs,544neuronhiddenlayer,1neuronoutputlayer

• Trainingdata:20kg and20kneutronsbetween1.5and5MeV• Onecompleteoptimizationpassovertrainingdata--‘epoch’• Forthedatasetsandnetworksused,eachepochtook3-4s



ANN:SupervisedLearning

Energy

Classification

Separationincreaseswithmoretraining

1epoch 5 epochs

10epochs 50epochs

ArtificialNeuralNetworkSupervisedlearning

gamma

neutron

gamma

neutron



Unsupervisedlearning:K-meansclustering• Clusteranalysisalgorithmsdonotrequirepre-classifiedtrainingdata• C++ implementationofkmeans++ algorithm• K=2forn/g discrimination• Perpendiculardistancefromhyperplanebetweencentroidsprovidesseparation• Trainingdatasethad~28Kneutronsand~1.5Mgammarays

K-meansClustering:Unsupervisedlearning

Machinelearningalgorithmscapableofseparatingneutronsandgamma-raysinCLYCscintillators intheenergyrangeinvestigated

neutron

gamma



ChargecomparisonGeneratestrainingdata

ArtificialNeuralNetworkSupervisedlearning

K-meansClusteringUnsupervisedlearning

Machinelearningalgorithmscapableofseparatingneutronsandgamma-raysinCLYCscintillators intheenergyrangeinvestigated

WORKINPROGRESS!!n/g discriminationatenergies<1MeVneedsimprovement

neutronneutronneutron

gamma gamma gamma


machinelearningn-g discrimination


• C7LYC:emergingscintillatorforfastneutronspectroscopy• Rightenergywindowforb-delayedandfissionneutrons• LANL56Fe(n,n’)proof-of-principleexperimentasuccess• EfficiencyandlowenergyresponseatUMLVandeGraaff• 35Cl(n,p)cross-sectionsawaitedforMCNPXsimulations• b-delayedneutronemittersatCARIBU• Machinelearningn-g discrimination• AuxiliarydetectorcandidateforFRIBdecaystation?

Summary

WorksupportedbyU.S.DepartmentofEnergyNNSA-SSAPGrantDE-NA0002932 and

OfficeofScienceGrantDE-FG02-94ER40848



UMassLowellcollaborators

Thankyouforyourattention!Chowdhury Neutron Detector Workshop- TAMU May 11, 2018

UndergradsThomasHarringtonMichaelD’Eon

GraduatestudentsTristanBrownEmeryDoucetNathanD’OlympiaEmilyJacksonPatrickCopp

Post-docsA.J.MitchellGemmaWilsonChrisMorseEdwardLamere

FacultyKimListerAndrewRogersPeterBender

Fast Neutron Spectroscopy with C7LYC Scintillators · Learning with Purpose •Eliminate 6Li(n,a)...

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